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Analysis of physical and bio-optical variability in the Arabian Sea during the northeast monsoon of 1994
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Analysis of physical and bio-optical variability in the Arabian Sea during the northeast monsoon of 1994
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INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter free, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely afreet reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. Each original is also photographed in one exposure and is included in reduced form at the back of the book. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6” x 9” black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. UMI A Bell & Howell Information Company 300 North Zeeb Road, Ann Arbor MI 48106-1346 USA 313/761-4700 800/521-0600 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. ANALYSIS OF PHYSICAL AND BIO-OPTICAL VARIABILITY IN THE ARABIAN SEA DURING THE NORTHEAST MONSOON OF 1994. By David Eric Sigurdson A Thesis Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment o f the Requirements for the Degree MASTER OF SCIENCE (Ocean Sciences) December, 1996 Copyright 1996 David Eric Sigurdson Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. UMI Number: 1383546 UMI Microform 1383546 Copyright 1997, by UMI Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. UMI 300 North Zeeb Road Ann Arbor, MI 48103 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. UNIVERSITY O F S O U T H E R N C A LIFO R N IA THE GRADUATE SCHOO L U NIVERSITY RARK LOS ANGELES. CA LIFO RN IA * 0 0 0 7 This thesis, 'written by David Eric Sigurdson under the direction of kJtfL.JThesis Committee, and approved by all its members, has been pre sented to and accepted by the Dean of The Graduate School, in partial fulfillment of the requirements for the degree of Masters of Science T in t0 November-20, 1996 Dtsm 1 iis c o m m : Ckurmtm ^ X ////T Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Acknowledgments I would like to send my deepest appreciation to Professor Tommy Dickey for all the advice and assistance he has given me to make this happen. He has also provided me funding, given me lab space and computers, and turned over a unique data set for me to work with, and for this I am truly grateful. I would also like to thank the Office of Naval Research for the ONR ASSERT grant that got me started at USC, and the ONR Forced Upper Ocean Dynamics Project grant numbers N00014-94-1-0463, and N00014-96- 1-0505 for a great program. I also appreciate captain G. Gomes and the crew of the R/V Thompson for their professionalism and good humor. Derek Manov has been a tremendous asset to my work; he never sent me away even with my constant barrage of questions. Burt Jones and Charlie Sammis have been a great help in the editing of my thesis. I am very grateful to Bob Weller, John Marra, Charlie Eriksen, Dan Rudnick, Chris Kinkade, Lakshmi Kantha, Jim Hendricks, Mark Baumgartner, John Kindle, and Charlie Flagg for providing data. I appreciate Bob Arnone, Jerry Wiggert and Chris Langdon for their useful discussions and Sharon Smith for directing a program which provided such great institutional interaction. ii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The staff at UCSB has been very helpful to me and Joel Michaelsen and Ray Smith have my gratitude for allowing me to finish my thesis work at their institution. Kathy Scheidemen, Claudia Kashin, and Bill Trusten have put up with loads of paperwork from me and I appreciate their patience and signatures. All the OPL members have been gracious to me and I am much obliged. They include: Anne Petrenko, Dave Foley, Jerry Wiggert, Margaret Stramska, Joe McNeil, Grace Chang, Sarah Zedler and Erin Lutrick. Erik Fields also deserves thanks for allowing me to be his Matlab pupil. My family and friends have been very supportive of me. My parents have always supported me in achieving whatever I have strived for. I will never be able to repay them but I will always cherish what they have bestowed upon me. My good buddies Mike Johnson, Greg Anderson, Brad Witt, Jim Gassaway and Gerald Wong have always kept my spirits high. My wife Marin and my newly bom son Jon have made this time in my life very special and my hopes for the future tremendous. tii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Table of Contents Acknowledgments ......................................................................................ii List of Figures ...............................................................................................vi List of Tables ..................................................................................................x Abstract ........................................................................................................ xi Chapter 1 Introduction .............................................................................1 Chapter 2 Arabian Sea Overview ............................................................9 Chapter 3 Methods Overview .................................................................20 3.1 Mooring Description ..................................................20 3.2 Multi-variable Moored System (MVMS) ...............25 3.3 TOPEX Data Description ............................................ 31 3.4 Other Complementary Data Sources ....................... 34 Chapter 4 Description of Annual Time Series ......................................41 iv Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Chapter 5. Description of Mesoscale Activity October 15 - December 25 1994 ..............................................................................65 5.1 TOPEX Results ........................................................... 65 5.2 Mooring Results .........................................................80 Chapter 6 Summary & Conclusion ..................................................... 106 Appendix I Description of MVMS Data Conversions .......................... 113 Appendix II Data Processing Description ................................................116 References ....................................................................................................120 V Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. List of Figures Figure 1.1 Map of the Arabian Sea ....................................................... 5 Figure 1.2 Schematic of time and space scales relevant to physical and biological processes found in the Arabian Sea ............7 Figure 2.1 Distribution of high and low pressure systems for the two monsoonal seasons .......................................................11 Figure 2.2 Findlater Jet axis during the four seasons over the Indian Ocean ..........................................................................13 Figure 2.3 Monthly climatological mixed layer depth contours during the NE and SW monsoons ..................................... 17 Figure 3.1 Central WHOI mooring diagram .........................................23 Figure 3.2 Multi-variable moored system configuration .....................26 Figure 3.3 Timeline listing functioning sensors for Deployment 1 ...30 Figure 3.4 Timeline listing functioning sensors for Deployment 2 ...30 Figure 3.5 Schematic of TOPEX satellite ................................................32 Figure 3.6 Map of TOPEX passes over the Arabian Sea ......................33 Figure 3.7 ADCP velocity data from TN042 ......................................... 36 Figure 3.8 ADCP velocity data from TN042 ......................................... 37 Figure 3.9 Map of wind curl and wind stress for Nov. 1994 ............... 39 Figure 3.10 Map of wind curl and wind stress for July 1994 ................. 40 vi Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 4.1 Time series of wind speed and direction, net heat flux and wind stress ......................................................................42 Figure 4.2 Time series of air and sea surface temperature, barometric pressure, relative humidity, and PAR ............43 Figure 4.3 Time series of latent and sensible heat flux and net shortwave and longwave radiation .................................... 44 Figure 4.4a Time series of temperature contour and MLD 0.1 °C ........48 Figure 4.4b Time series of temperature contour and MLD 1.0°C 49 Figure 4.5 Time series of velocity vectors ...........................................52 Figure 4.6 Time series of vertical shear (east) .................................... 54 Figure 4.7 Time series of vertical shear (north) .................................55 Figure 4.8 Time series of shear at UW-S .............................................56 Figure 4.9 Time series of buoyancy frequency at UW-S ...................57 Figure 4.10 Time series of sigma-theta at UW-S ..................................58 Figure 4.11 Time series of temperature and salinity at UW-S ........... 62 Figure 4.12 Time series of Richardson number at UW-S ...................63 Figure 4.13 Time series of chlorophyll a ...............................................64 Figure 5.1 TOPEX SSH Sept. 16 - Sept. 26 1994 ..................................... 66 Figure 5.2 TOPEX SSH Sept. 26 - Oct. 6 1994 .........................................67 Figure 5.3 TOPEX SSH Oct. 6 - Oct. 16 1994 .......................................... 68 Figure 5.4 TOPEX SSH Oct. 16 - Oct. 26 1994 .........................................69 vii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.5 TOPEX SSH Oct. 26 - Nov. 5 1994 ......................................... 70 Figure 5.6 TOPEX SSH Nov. 5 - Nov. 15 1994 .......................................71 Figure 5.7 TOPEX SSH Nov. 15 - Nov. 25 1994 .....................................72 Figure 5.8 TOPEX SSH Nov. 25 - Dec. 5 1994 ........................................ 73 Figure 5.9 TOPEX SSH Dec. 5 - Dec. 151994 ..........................................74 Figure 5.10 TOPEX SSH Dec. 15 - Dec. 25 1994 ...................................... 75 Figure 5.11 TOPEX SSH Dec. 25,1994 - Jan. 41995 ................................76 Figure 5.12 TOPEX SSH Aug. 10 - Aug. 20 1995 ................................... 77 Figure 5.13 Time series of wind speed and direction and net heat flux .........................................................................................81 Figure 5.14 Time series of air and sea surface temperature, wind stress, relative humidity, and latent heat flux ....................82 Figure 5.15 Time series of velocity vectors ............................................ 84 Figure 5.16 Time series of velocity components at 35m...........................85 Figure 5.17 Time series of current speed and direction at 35m and 80m .................................................................................86 Figure 5.18 Time series of velocity vectors, temperature contour, and MLD .................................................................87 Figure 5.19 Time series of temperature, salinity, and density ............. 88 Figure 5.20 Time series of density contour ............................................89 viii Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.21 Time series of velocity vectors, temperature, PAR and chlorophyll a at 35m 94 Figure 5.22 Time series of PAR, Kpar, and chlorophyll a ...................99 Figure 5.23 Time series of chlorophyll a and Kpar.............................. 100 Figure 5.24 Time series of PAR ............................................................101 Figure 5.25 Time series of MLD and 1% light level depth ................. 102 Figure 5.26 Log of PAR vs. Depth ......................................................... 104 Figure A2.1 Block diagram description of data processing procedure .118 ix Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. List of Tables Table 3.1 Sensor functionality summary for deployment #1 28 Table 3.2 Sensor functionality summary for deployment #2 29 Table A2.1 Description of raw hexadecimal data line ...........................116 x Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Abstract A mooring time series of physical and bio-optical variables and complimentary data were collected during the Arabian Sea Process Study in 1994-1995. The mooring data-set was collected continuously for one year. This allowed observation of two mixed layer (ML) deepening events, during the NE monsoon and the SW monsoon. Prior to this experiment, there were relatively few interdisciplinary observations in the Arabian Sea. The results show that NE monsoon ML deepening was driven by convection, and that the SW monsoon ML deepening was driven by mechanical mixing. Advection of mesoscale features was evident, as mesoscale features caused an interruption during both the NE monsoonal ML deepening, and the SW monsoonal ML shoaling. TOPEX satellite altimetry data were used to derive spatial scales and geostrophic current directions of mesoscale features. Special focus of this work is on the mesoscale feature that interrupted the NE monsoon deepening. This feature passed directly over the mooring. Bio-optical variables such as KPAR and chlorophyll fluorescence (phytoplankton concentrations) correlated well during the period of mesoscale activity in winter. Also, light limitation likely resulted when a biologically rich mesoscale feature advected past the mooring site. xi Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1. Introduction The Arabian Sea is one of the most interesting and unique regions of the world oceans (Figure 1.1). For example, the seasonal variability (monsoons) expressed in the Arabian Sea is the greatest of any ocean basin. The Findlater Jet is the strongest of the tropospheric jets. The wind forcing is both intense and quite regular, with alternating wind direction associated with the winter Northeast Monsoon (NE; winds toward the southwest) and the summer Southwest Monsoon (SW; winds toward the northeast) which result in current reversals for the basin (counterclockwise during NE monsoon and clockwise during SW monsoon). The Somali Current which develops during the SW monsoon is reported to be the fastest open ocean current (i.e., -350 cm/sec). The net heat flux at the surface is at times positive (heating of the ocean) and at times negative (heating of the atmosphere), thus it is critical to accurately measure the contributing surface heat flux components (including evaporative and rainfall effects) as well as the penetrative component of solar radiation, which is dependent on phytoplankton biomass and distributions. In addition, two cycles of mixed layer shoaling and deepening occur each year. The difference between the two is of special interest not only for the physical significance, but also for biological productivity and bio geochemical fluxes. The regular forcing belies the complexity of the oceanography of the region which is characterized by high horizontal spatial variability resulting from intense coastal upwelling and likely open ocean divergences and convergences associated with 1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. horizontal gradients in wind stress curl and remote forcing (e.g. Rossby waves). One of the interesting issues concerns the upper ocean dynamics and thermodynamics which are three-dimensional in nature. Another is the role of advection of differing water masses for all processes. It is evident that any comprehensive study of the Arabian Sea requires a host of platforms and sensors which can be used to study complex processes spanning ten orders of magnitude in space and time (e.g., Dickey, 1991; figure 1.2). The Indian Ocean is the smallest and one of the least studied oceans in the world. It is also unique in that it is bordered to the north by a major mid latitude land mass, unlike the Atlantic and Pacific Oceans. Few nations with large oceanographic programs lie on its borders. As a result, little information was available for this ocean or the Arabian Sea which lies at its northwestern end until the early 1960's. From 1959 to 1965 the International Indian Ocean Expedition (HOE) involved 25 nations, employing 44 research vessels. Data compiled from this experiment can be found in Wrytki et al. (1976), which has remained one of the major references for the region up to this point. Because of complexity in the water structure, a clear picture of the hydrography and currents was not available even then. From 1976-1979, the INDEX campaign deployed long-term moored current meters in the Indian Ocean. Until then, surface currents were documented using ship drift (KNMI 1952, Swallow 1983). In the early 1990's plans were made for the present international study. Participating United States sponsoring agencies included the National Science Foundation (NSF), the Office of Naval Research (ONR), the National 2 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Aeronautics and Space Administration (NASA), and the National Oceanic and Atmospheric Administration (NOAA). Plans were made for a large scale dimatological, physical, geochemical, and biological study in the north Indian Ocean. The Bay of Bengal and the Arabian Sea were the areas considered for the study. The Bay of Bengal is characterized by stratification driven by buoyancy input from freshwater runoff, large input of runoff sediments, and geochemical and carbon cycles driven by river and estuarine inputs. The Arabian Sea, on the other hand, is far different. The regions were found to be too different to be encompassed under one process study (U.S. JGOFS Planning Document No. 13,1991). Other nations were also planning studies of the Arabian Sea in the 1990's (Belgium, The United Kingdom, Germany, Japan, and the Netherlands), and interest was shown by regional nations (India, Pakistan, and Oman). Thus, U.S. agencies chose the Arabian Sea for an intensive study during 1994 and 1995. Two of the primary goals of the NSF Joint Global Ocean Flux Study (U.S. JGOFS Planning Document No. 13, 1991) are: 1) to determine and understand processes controlling time-varying fluxes of carbon and associated biogenic elements in the ocean, and 2) to predict the response of marine biogeochemical processes to climate change. Thus, this activity required highly interdisciplinary observations. The ONR Forced Upper Ocean Dynamics study focused on questions concerning the linkages between large-scale patterns of wind speed and direction, ocean circulation, and biological production in near surface waters. The premise of this work was that the position, strength, evolution, and dissipation of the atmospheric Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Findlater Jet drives mixed layer dynamics, heat flux, upwelling and other major physical processes which in turn regulate biogeochemical processes in the region. The NASA study was motivated by interest in obtaining relevant data for developing groundtruthing algorithms for color imaging satellites such as SeaWiFS. The NOAA efforts were multi-faceted and concerned measurements of greenhouse gases and compounds such as C 0 2, zooplankton and fish, and hydrography for general circulation studies (World Ocean Circulation Experiment; WOCE). The U.S. Arabian Sea Process Study encompassed institutions throughout the U.S. (e.g., University of California, Santa Barbara, University of Southern California, University of Washington, Scripps Institution of Oceanography, Woods Hole Oceanographic Institution, Lamont-Doherty Earth Observatory, University of Miami, Naval Research Laboratory, etc.). Several process cruises were conducted, gathering geochemical, physical, and biological data. Satellites (for winds, sea surface temperature or SST, sea surface height, SSH), dust particle samplers, moored sediment traps, drifters, airplanes for ocean color and temperature, ship-mounted acoustic Doppler current profilers (ADCP), and ship-based instruments were all used during various time periods of the year-long study. This document presents data collected primarily as part of the ONR Forced Upper Ocean Dynamics Project, which utilized an array of five deep ocean moorings placed beneath the axis of the Findlater Jet. The central 4 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Five Mooring Positions During the Arabian Sea Study Central Mooring Position 15 deg 30 min N 61 deg 30 min E Longitude E Figure 11 Map showing the Arabian Sea and five mooring locations occupied during the Arabian Sea Process study. The moorings were deployed from October 15, 1994 to October 20,1995. The MVMS's deployed by the Ocean Physics Laboratory were on the central mooring at 15°30'N and 61 °30'E. (Woods Hole Oceanographic Institution, WHOI) mooring was located at 15° 30'N, 61° 30% the center of a 50km square with four other moorings placed at the comers (Figure 1.1). Water depth for the site was about 4000-4030m. Two moorings were placed at the eastern comers by a group from the Scripps Institution of Oceanography (SIO) and two moorings were placed at the western comers by a group from the University of Washington (UW). The exact locations of the moorings and times of deployment and recovery are given by Trask et al. (1995). The observations of primary interest for the present work were collected from instruments deployed on the central 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (WHOI) mooring, in particular data from the multi-variable moored systems (MVMS). Data were collected during two separate deployments (October 15, 1994-April 20,1994 and April 22,1995-October 20,1995). Technical details are presented in Sigurdson et al. (1995, 1996). The MVMS is designed to measure physical, bio-optical, and chemical variables every few minutes for months (Dickey etal., 1991a, 1993). Resulting observations permit studies of cyclic (e.g., diurnal, tidal, seasonal, etc.), episodic (e.g. synoptic weather events, advective transport of matter, phytoplankton blooms, etc.), and general changes in the physical and bio- optical environment. Variability takes place over ten orders of magnitude in time and space (figure 1.2) in the highly complex environment of the Arabian Sea. Due to the lack of long time series high resolution observations in the Arabian Sea, short term small scale events have not been observed or documented in the past. Climatological averaging of annual data over many years tends to remove evidence of small scale features. Thus, high frequency, long-term sampling is essential to provide data relating to all event scales (Dickey, 1991). This document focuses on variability of the physical, bio- optical, and chemical parameters and provides required inputs for interdisciplinary models of heat budgets, mixed layer dynamics, primary production, and carbon flux. 6 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 1mm 1 cm 1dm 1m 10 m 100 m 1 Km lOkm 100 km 1000 km Figure 1.2 Schematic diagram illustrating time and space scales relevant to physical and biological processes that are found in the Arabian Sea. ( Dickey, 1991) Two questions are addressed in this thesis. The first question posed is "What processes cause variability in the physics and the biology during our study period?" The second question addressed in this thesis is "Is there coupling between the physics and biology on time scales of days to weeks and space scales of 10's to 100's of kilometers?" An overview of Arabian Sea bathemetry, meteorology, physical oceanography, current structures, mixed layer dynamics, and bio- optical/biogeochemical structure is given in Chapter 2. A detailed description of the five deep ocean moorings used in this study is given in 7 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Chapter 3 as well as a description of the MVMS, TOPEX satellite, and other complementary data sources. Chapter 4 describes results horn our year-long mooring time series. A mesoscale feature advected by the mooring array between October 17,1994 and December 25, 1994. This event is discussed in Chapter 5 in terms of the driving forces which cause the fluctuations of currents, temperature, salinity, photosynthetically available radiation (PAR), and chlorophyll. 8 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 2. Arabian Sea Overview The Indian Ocean is bordered to the south by the Antarctic circumpolar current and is the only ocean to be completely non- communicative to the north due to land blockage. The Arabian Sea lies in the northwestern portion of this ocean basin, and with an annual net heat flux into the ocean, it is considered to be one of the crucial regions for understanding climate dynamics. The Arabian Sea is bordered to the north and east by Iran and India, respectively. Its southern border is marked by the North Equatorial Current running east to west at the surface, with seasonally changing position and magnitude. The Arabian Peninsula forms its western border. Most of the Arabian Sea is greater than 3000m in depth, with areas in the Arabian Basin, to the south, exceeding 4000m. A seasonal reversal of atmospheric forcing drives a bi-annual reversal of currents in the Arabian Sea. This effect, known as the monsoons, changes weather from Somalia to India and currents from the Arabian gyre to the equator. Seasonal monsoonal periods vary depending on choice of atmospheric or oceanic criteria. Brock et al. (1992) describe the four seasons using mean oceanographic data. They define the fall intermonsoon period to be September-November, with the NE monsoon 9 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. period December-February (when a wind from the northeast drives a southwestward current in the western portion of the Arabian Sea). March-May is defined as the spring intermonsoonal period, and June- August is defined as the SW monsoon (where wind from the southwest drives a northeastward current). There is interannual variability in this cycle, which is relevant to our observations (discussed in Chapter 4). Krishnamurti et al. (1989) suggest this may be related to El Nino-Southern Oscillation (ENSO) events. During the northern hemisphere winter, a high pressure forms over the Asian continent and northeasterly winds develop (roughly 60° with respect to true North) over the tropics and northern subtropics (figure 2.1). 1 0 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. January w a r r ir ■ * m * qr a nr w Ju ly m s r m m * v m w r so* o r o r i r s i n r i r Figure 2.1 Distribution of high and low pressure systems for the two monsoonal seasons. (Tchemia, 1980) The NE monsoonal winds carry drier air and are less intense than those of the moist SW monsoon as observed in our data set. The SW monsoon results from a deep heat driven low over northern Arabia and Pakistan (figure 2.1). The horizontal pressure gradient driving the SW monsoon is in the opposite direction (roughly 240° from true North) of the NE 11 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. monsoon and generally results in wind speeds which are over three times greater than those of the NE Monsoon. The SW Monsoonal air is more humid as well. It should also be noted that a 30-50 day wind oscillation can force upper ocean thermal structure on this time scale as well (Hastenrath, 1991). The Findlater Jet, which is akin to a western ocean boundary current, blows during the SW Monsoon and generally extends from about Cape Guardafi, Somalia (12°N, 51°E) to the Gulf of Cambay, India (21°N, 71°E). The Findlater Jet varies in strength and position (see depiction in Figure 2.2). This effect has important implications for the region's upper ocean dynamics and thermodynamics, as the distribution of wind stress and wind stress curl shift as well. 12 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 2.2 Findlater jet axis during the four seasons over the Indian Ocean (Hastenrath 1991) The heat and moisture budgets for the Indian Ocean have been studied and summarized by Hastenrath and Lamb (1979a, and 1979b). For our site, incident shortwave radiation is fairly steady seasonally although modulated by cloudiness and atmospheric dust. The seasonal variability of the net heat flux is affected primarily by changes in the latent heat flux and net shortwave radiation. Brock et al. (1992) and Hastenrath and Lamb 1 3 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (1979b) state that generally net heat flux is positive (into the ocean) during the intermonsoonal times and negative (out of the ocean) during both the winter and summer monsoons. This is not what we observed at our mooring site. In fact, the heat flux was positive all year except during the late fall intermonsoon, and early in the winter monsoon (October- December). This effect has important implications for upper ocean mixing and stratification. Climatological current data from geostrophic (dynamic height) and shipdrift determinations provide some indication of the Arabian Sea general circulation (e.g., Swallow, 1984 and Hastenrath and Greischar, 1991). A few general circulation models have also provided insights into the processes which affect the current patterns (e.g., McCreary and Kundu, 1989 and Simmons et al., 1988). During the NE monsoon, these summary data show that a counterclockwise gyre sets up in the Arabian Sea which severely dampens the Somali Current, and may form Ekman convergence along the coast of Arabia. The SW monsoon sets up a clockwise circulation pattern in the basin. These currents are generally much larger, flowing generally parallel to the axis of the Findlater Jet, which has the effect of: strengthening the Somali current, strengthening currents running northward along Arabia, and strengthening the North Equatorial Current which runs east at zero degrees. Importantly, conditions are such 14 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. that strong upwelling exists along the Arabian coast. This process is clearly important to the productivity of the region and mesoscale features observed in the open Arabian Sea. These cool, nutrient rich waters form filaments along the Arabian coastline. These waters can potentially advect past our moorings a distance of 550km offshore. Also during the S W monsoon, the wind stress curl is counterclockwise on the northwest side of the Findlater Jet leading to regional upwelling, again potentially bringing nutrient rich waters into the euphotic zone. On the southeast side of the Jet axis, the wind stress curl is clockwise leading to regional downwelling. The mixed layer dynamics of the Arabian Sea are generally more complicated than those of most open ocean regions because of the occurrence of a variety of processes. These include: 1) mechanical stirring by winds, 2) Ekman pumping (induced up- and downwelling) arising from wind stress curls of opposing senses, 3) net heat fluxes which change sign seasonally leading to alternating periods of convection and enhanced static stability, 4) advection of mesoscale features such as filaments and eddies originating from coastal regions or the open ocean through remote forcing processes (e.g., Rossby waves), and 5) variations in the penetrative component of heat induced by phytoplankton blooms and busts. Climatologies of mixed layer depth have been compiled by Hastenrath 1 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (1989) and Molinari et al. (1986). The general distributions of mixed layer depth have been summarized by Bauer et al. (1991) and are illustrated in figure 2.3. This figure indicates that the mixed layer depth during the NE monsoon is relatively uniform over the Arabian Sea and on order of 50m. In distinct contrast, the mixed layer depth distribution is highly skewed across the Findlater Jet axis during the SW monsoon when the Jet is well- developed. According to these summaries, maximum mixed layer depths do not lie beneath the axis of the Jet. Mixed layers on order of 100 m are found to the southeast of the axis of the Jet and less than about 50-60m to the northwest of the axis of the Jet. 16 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. p t DEC U S 20 N I m i x e o l a y e r s ^ DEPTH (m) i 5 0 E 60'E 70’E H i AUG m MIXED LAYER DEPTH (m ) 40 20N ’ 80 80 10N 30 •7 0 60 Figure 2.3 Monthly dimatological mixed layer depth (MLD) contours during the NE and SW monsoons (in meters, Mounari et al., 1986). The solid arrow indicates wind maximum and direction (From Bauer et al., 1991) During the SW monsoon, the wind stress curl is counterclockwise on the northwest side of the Jet leading to upwelling (and rising isotherms and nutrient concentrations) due to Ekman pumping and clockwise on the southeast side of the Jet causing downwelling (descending isotherms). 17 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Bauer et al. (1991) have used a 2-dimensional mixed layer model to study the asymmetry of the mixed layer. The capability of accurately measuring heat fluxes (e.g., Weller et al., 1990, Hosom et al., 1995) within the present study allows us to analyze and model the local heating and cooling effects which are likely critical for heat budget, mixed layer, and thermal structure analyses and models. The effect of biological productivity on optical attenuation has been of great interest and concern for several years (e.g., Dickey and Simpson, 1983). Sathyendranath et al. (1991) have developed a coupled bio-optical/physical model for the Arabian Sea. Their intriguing results suggest that the maximum rate of "biological heating" in the Arabian Sea is ~4°C/month from August to September which is highly significant when compared with a maximum observed cooling rate Quly) due to upwelling of ~2.5°C/month according to climatology. They point out that the phytoplankton effect is in fact asymmetric as it diminishes the rate of cooling during upwelling season and enhances the heating rate during the heating season. Finally, they suggest that increased stratification (caused by phytoplankton) may affect large scale net meridional heat transport. These model results are compelling; however, it should be noted that the Arabian Sea has been data poor with few data relevant to bio-optics and carbon cycling, particularly on key time scales (days to months). Again, bio-optical 18 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. measurements made during our study should allow quantification of this effect for the annual cycle at our site. Brock et al. (1992) have used climatological data and models for the Arabian Sea to examine relationships between primary productivity, phytoplankton biomass, and the physics of the region. Their results suggest the following scenarios: 1) during the intermonsoons (November and May), the open Arabian Sea is a classic unperturbed tropical ocean with a shallow oligotrophic mixed layer and a strong subsurface chlorophyll maximum, 2) the NE and SW Monsoons lead to mixed layer deepening and eutrophication in the central and northern Arabian Sea, 3) seasonal changes in mixed layer depth and phytoplankton concentration cause major fluctuations in the depth of penetration of light, 4) the euphotic zone is in the thermocline at the close of the intermonsoons, 5) the euphotic layer rises into the mixed layer of the northern Arabian Sea during winter and summer monsoons, 6) primary production peaks primarily during the southwest monsoon and secondarily during the northeast monsoon, 7) primary production in the thermocline exceeds that in the mixed layer during intermonsoons, and 8) the subsurface chlorophyll maximum present in the spring intermonsoon is a precursor for the summer phytoplankton bloom of the region. Our data sets are used to address some of these key issues. 19 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3. Methods Overview 3.1 Mooring Description The present bio-optical/physical time series study greatly benefited from previous and current research involving high temporal resolution/long-term, interdisciplinary measurements from moorings (e.g., reviews by Dickey, 1991, and Dickey et al., 1993a). This work has provided information concerning atmospheric and oceanic physical/biological coupling on temporal scales as short as a few minutes and as long as two years. Previous bio-optical time series programs conducted by our group, the Ocean Physics Laboratory (OPL), includes: 1) the Biowatt program in the Sargasso Sea (e.g., Dickey et al., 1991; 1993a; Marra et al., 1992; Stramska and Dickey, 1992), 2) the Marine Light in the Mixed Layer (MLML) program south of Iceland (e.g., Dickey et al., 1994; Stramska et al., 1995), 3) the JGOFS Equatorial Pacific program at (Foley et al., 1996), 4) the NOAA sponsored Los Angeles Outfall program (Dickey and Manov, 1991; Dickey et al., 1993b), 5) the Mediterranean Flux study (Taupier-Letage et al., in prep.), and 6) the Bermuda Testbed Mooring program (Dickey, 1995; Dickey et al., 1996). Five moorings were placed beneath the climatological axis of the Findlater Jet by collaborating institutions. General mooring designs and 20 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. placements of instruments are illustrated in figure 3.1 (after Trask et al., 1995). The two SIO moorings (principal investigator, Dan Rudnick; SIO-N, 15°44'N, 61°16rE; SIO-S, 15°17'N, 61°16/E) were instrumented with surface meteorological systems, temperature sensors placed at 10 depths in the upper 150m (10m spacing from the surface down to 50 m and 20m spacing from 50 down to 150m), and a buoy-mounted, downlooking acoustic Doppler current profiler or ADCP (300kHz). Meteorological measurements included wind speed and direction, barometric pressure, air temperature, shortwave radiation, and sea surface temperature. All meteorological data were collected with two systems on each buoy for redundancy. The raw ADCP current data were 3-minute averages of 1- second pings taken every 7.5 minutes. The vertical resolution was 4 m down to a nominal depth of 120m. The two UW moorings (principal investigator, Charlie Eriksen; UW-N, 15°44'N, 61°45'E; UW-S, 15°16'N, 61°14,E) were subsurface moorings and thus did not include meteorological instrumentation. They utilized an autonomous profiling system (PCM) which measured horizontal currents, temperature, depth, and conductivity (for salinity). The PCM, which is described in several publications (e.g., Eriksen, 1982), was programmed to complete vertical profiles every 4 hours in the nominal depth range of 20 to 200m. The PCM data were taken at 1 Hz and 2 1 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. averaged over 5m vertical bins. Estimates of all quantities were made on a 5m depth bin grid; however quantities used for vertical derivatives such as Brunt-Vaisala frequency, shear, and Richardson number use the 5 meter data with centered first differences over 10m. Five WHOI vector measuring current meters (VMCMs; principal investigator, Bob Weller) were placed at depths of 300, 500, 750, 1500, and 3000m depths on UW-S only. The sampling rate was 7.5 minutes for these VMCMs In addition, a multi-frequency acoustic system (principal investigators, Van Holliday and Rick Pieper) designed to measure backscatter from zooplankton was placed on the UW-N mooring, but no data were recovered. Unfortunately, a mooring failure occurred for UW-N and the PCM was not recovered. The central (WHOI) mooring (principal investigator, Bob Weller) was the most heavily instrumented of the moorings (figure 3.1) with 37 recording instruments and 95 sensors and is described in detail by Trask et al. (1995). Two primary meteorological systems were deployed from the buoy. The Vector Averaging Wind Recorder (VAWR) measured wind speed and direction, shortwave and longwave radiation, relative humidity, barometric pressure, and air and sea surface temperature. These data were recorded at 7.5 minutes intervals. The Improved Meteorological system (IMET) measured the same suite of variables, but some with 22 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. M 3 m Discus Buoy (VAW R,ARGOS,IMET) 5m 10m 15m 20m 25m 30m 35m 40m A V \ * A V \ * A * A VMCM (WHOI)) MVMS (LOGO) VMCM (WHOI) TPOD VMCM (WHOI) TPOD MVMS (UCSB) Acoustic Zooplankton Counter & TPOD (Tracor) 45m | VMCM (WHOI) 50m • TPOD 55m | VMCM (WHOI) 60m i TPOD 65m MVMS (LDGO) ONR ARABIAN 72.5m i TPOD SEA MOORING 80m MVMS (UCSB) 90m 1 tp00 O ctober 15,1994-October 20, 1995 100m SEACAT (WHOI) Anchor Position 125m i TPOD 15° 30’N 150m SEACAT (WHOI) 61 ° 30' E 175m 'i TPOD 200m SEACAT (WHOI) 225m TPOD 250m I SEACAT (WHOI) 300m TPOD ghSLDepth Manov Q UCSB 96 Figure 3.1 ONR Arabian Sea Process study mooring diagram often referred to as the WHOI central mooring. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. different sensors and sampling schemes. Another independent system recorded relative humidity and temperature. All meteorological data were collected by WHOI (Hosom et al., 1995). Conductivity and temperature recording systems (SeaCats, Sea-Bird Inc.) were deployed by WHOI at 100,150,200, and 250m and recorded every 7.5 minutes. Internally recording temperature recorders (TPODS, Branker, Inc.) were deployed at 18 depths ranging from 0.25 to 300 m. These systems recorded data every 15 min. Another miniature temperature recorder (MTR, Pacific Marine Environmental Lab) was deployed at 3.5 meters and recorded every 7.5 min. Placement of these sensors is indicated in figure 3.1. A separate dissolved oxygen measurement system (principal investigator, Chris Langdon) was deployed on the buoy bridle at a depth of 1.5m. Current measurements were done at 9 depths using VMCMs (Weller and Davis, 1980). VMCMs were deployed at depths of 5, 15, 25, 45, and 55m by WHOI. The VMCMs recorded average horizontal components of currents and temperature every 3.75min. Two multi- variable moored systems (MVMS, Dickey et al., 1991a, figure 3.2) were deployed by our group (principal investigator, Tommy Dickey) at 35 and 80m. The MVMS utilizes a VMCM (EG&G) to measure currents (Weller and Davis, 1980). The MVMS also includes a suite of bio-optical 24 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. instruments (described below); the entire package samples at 3.75 m inute intervals (figure 3.2). Two other MVMSs were deployed by Lamont- Doherty Earth Observatory, (LDEO; principal investigator, John Marra) at depths of 10 and 65m. The sensor suite was similar to that of the UCSB MVMSs, however, currents were measured at 7.5 minute intervals and the remaining variables were measured at 4 minutes interval. A Tracor Applied Science bio-acoustic transceiver array (principal investigators, Van Holliday and Rick Pieper) was deployed at 40m, but no data were retrieved. 3.2 Multi-variable Moored System (MVMS) The multi-variable moored system (MVMS; e.g., see Dickey, 1991, Dickey et al., 1991, 1993a) is a high resolution sampling system which collects physical and bio-optical data every few minutes (see figure 3.2). The fundamental component of the MVMS is the EG&G vector measuring current meter (VMCM). The VMCM measures vector averaged currents with two orthogonal rotors (Weller and Davis, 1980) and temperature with a pressure case mounted thermistor. Inside this pressure case is a micro-controller, hard drive, and sensor interfacing circuitry. The micro-controller commands the VMCM as well as the other 25 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. PARSENSOR VMCM ORTHOGONAL CURRENT ROTORS FLUOROMETER TRANSMISSOMETER DISSOLVED OXYGEN SENSOR 683 SENSOR CONDUCTIVITY SIDE VIEW TOP VIEW ManovSUCSB 96 ONR MVMS UCSB OCEAN PHYSICS LAB Figure 3.2 Multi-variable moored system (MVMS) deployed by the Ocean Physics Laboratory of the University of California, Santa Barbara during the Arabian Sea Process study on the ONR central mooring (Figure 3.1). 26 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. attached sensors. These sensors include: a photosynthetic available radiation (PAR, Biospherical Instruments) or scalar irradiance sensor (Booth, 1976), a natural chlorophyll fluorescence or upwelled radiance 683nm sensor (Biospherical Instruments), a beam transmissometer at 660nm (Bartz et al., 1978, SeaTech), a pulsed fluorometer (Bartz et al., 1988, SeaTech), a dissolved oxygen sensor (based on Langdon, 1984), and a conductivity sensor (Sea-Bird). Derived quantities may include: chlorophyll concentration, beam attenuation coefficient or beam c, primary productivity from several variables and models, and diffuse attenuation coefficient of PAR (KPAR). The data return from the central mooring was good considering the harshness of the environment for underwater sensors and electronics, and considering the very long (six month) deployments. All nine of the VMCM's collected velocity and temperature data for the entire year. The MVMS's worked well except for the one at the 80m depth during Deployment 1. The bio-optical data return is summarized in tables 3.1 and 3.2, and shown as timelines in figures 3.3 and 3.4. 27 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 35m Sensor list Estimate of failure Date Reason for failure or comments VMCM SN 500501 NO FAILURE NA Transmissometer. SN200 JD 380 Bio - fouling after JD350, may be useful data up to JD 400 Fluorometer SN 16 JD 378 Bio - Fouling DO SN 201 NO FAILURE NA Conductivity SN 041401 NO FAILURE NA 683 nm SN 7021 NO FAILURE NA PAR SN4216 JD 360 Par ball sensor broke off 80m Sensor list Estimate of failure Date Reason for failure or comments VMCM SN 500601 NO FAILURE Transmissometer. SN 195 NO FAILURE Bio - fouling look to affect signal after JD360 Fluorometer SN 145 NO FAILURE Very low values still being investigated, after JD400 Bio-fouling affect signal. DO SN 114 NO FAILURE NA Conductivity SN 041405 ? Strange variability, still being investigated 683 nm SN 7020 NO FAILURE Very low values, still being investigated PAR SN 4217 ? Strange offset, still being investigated Table 3.1 Sensor functionality summary for Deployment #1 October 15, 1994 (JD288) to April 22, 1995 (JD 475) 28 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 35m Sensor list Estimate of failure Date Reason for failure or comments VMCM SN 200203 NO FAILURE NA Transmissometer. SN 410 JD 560 Bio - fouling trend, may be some useful data u p to JD 610 Fluorometer SN 144 JD 560 Bio - fouling trend, signal doesn’t die until end of experiment DO SN 105 NO FAILURE Some non-temperature variability shown, may be a good result. Conductivity SN 041409 JD 577 After JD577 level (trend) looks reasonable witl variability that looks unreasonable 683 nm SN 7030 JD 538 Sensor and mount tripod disjoined from MVM cage. PAR SN 4394 JD 504 Par ball sensor broke off, JD539 sensor and mount tripod disjoined from MVMS cage 80m Sensor list Estimate of failure Date Reason for failure or comments VMCM SN 200103 NO FAILURE NA Transmissometer. SN 408 JD 557 Fuse or short, still under investigation Fluorometer SN 302 JD 655 Veiy little fouling, excellent data DO SN 103 NO FAILURE Some non-temperature variability shown, may be good data. Conductivity SN 041461 NO FAILURE NA 683 nm SN 7031 559 Sensor and mount tripod disjoined from MVM cage. PAR SN 4395 515 Par ball sensor broke off, JD560 sensor and mount tripod disjoined from MVMS cage Table 32 Sensor functionality summary for deployment #2 April 22, 1995 (JD477) to October 20, 1995 (JD 658) 29 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3 5 m MVMS Inmt run n n l Timeline of Sensor Functionality Deployment # 1 VM CM Currents and Temp. 1 E SflM y 2 I PAH 3 E Lu 683nm fluorometer 5 1 Beam C 6 1 DO U-m-MY M SJpiU um tnt 0 1 V M CM Currents and Temp. Safinly 21 PAR 3 y Lu 683mn 4 I fluorometer 51 Beam C 6 | DO 7 fi 288 Julian Day Figure 33 Timeline listing functioning sensors for Deployment 1 3 5 m MVMS V M CM Currents and Temp, i Sain it y 2 PAR 3 Lu 683nm a Fkjoro meter 5 Beam C e DO 7 U m IIVU3 Irm tum ant 0 V M CM Currents and Temp. 1 Sainity 2 PAR 3 Lu 683mn 4 Fkjoro meter 5 Beam C e O O 7 Timeline of Sensor Functionality Deployment # 2 Julian Day Figure 3.4 Timeline listing functioning sensors for Deployment 2 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3.3 TOPEX Data Description The TOPEX/Poseidon satellite was launched in August of 1992 (figure 3.5). It operates a dual-frequency radar altimeter (RA) at 13.6 and 5.3 GHz. The use of two frequencies decreases the sea surface height (SSH) error associated with total electron content fluctuations in the ionosphere caused by solar activity (Ikeda and Dobson 1995). TOPEX orbits at a height of 1336km at an inclination of 66°. The orbit cycle is repeated every 10 days. Standard TOPEX altimeter data processing techniques were applied to the data shown in this document by Hendricks et al. (1996; see figure 3.5; principal investigator Lakshmi Kantha and Jim Hendricks). Briefly, some of these include: corrections for ocean loading tide, solid Earth tide, pole tide, empirical ocean tide [model based on TOPEX data computed with Joint Gravity Model JGM-3 (Desai and Wahr, 1995)], SSH corrections based on improved orbits using the JGM-3 gravity model (Marshall et al. 1995), and standard inverted barometer correction using geophysical data record. Data taken over water less than 200m in depth were discarded. Each cycle of SSH variability was interpolated to 1.4° resolution. A two-year mean of SSH anomalies was removed from the data described here. 31 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. A ltitu de co rrectio n Sensor geometry Ionosphere Dry troposphere Wet troposphere Sea surface effects SWH correction" Ocean & solid tides Barometric correction Dynamic topograghy Geoid undulations Corrected height Center of mass Radar feedhom Computed orbit height Geometric instantaneous sea level Radar instantaneous sea level Mean sea level Geoid Reference ellipsoid Figure 3.5 Schematic of TOPEX satellite with components and corrections applied for accurateF igure SSH de ^termination (Ikeda and Dobson, 1995). TOPEX tracks that lie over the Arabian Sea (and are used here) are shown in Figure 3.6. The plots shown in chapter 5 are from TOPEX cycle 74 (Sept. 16 - Sept. 26 1994) to cycle 84 (Dec. 25 1994 - Jan. 4 1995), and cycle 107 (Aug. 10 - Aug. 20, 1995). TOPEX data yield large spatial scales of SSHA's, but do not resolve the smaller O(10km) scale variability as observed with SeaSoar. Mooring data presented here shows MLD changing rapidly on scales of less than 10 days. TOPEX has a 10-day 32 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. sampling rate, thus severe aliasing results. Due to the limited spatial resolution, many of the TOPEX plots shown here presented difficulty in determining if a feature was truly an isolated ring or eddy. TOPEX data do however integrate temperature effects over the entire water column, thus resolving features that are often unobserved using AVHRR SST data due to lack of surface expressions. Most importantly TOPEX data are not lost when clouds prevail as is the case for AVHRR data. Five Mooring Positions with TOPEX Passes Overploted 20 z f f l -o 3 3 Central Mooring Position 15deg30m inN 61 deg 30 min E 45 I0 55 Longitude E Figure 3.6 Map showing TOPEX Satellite passes over the Arabian Sea and area of depressed SSH anomaly described in Chapter 5. 33 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 3.4 Other Complementary Data Sources One of the great strengths of the Arabian Sea program was the large number of collaborating scientists whose data sets complement our own and facilitate the interpretation of our observations. Shipboard data are important. In particular, vertical profiling and tow-yoing (SeaSoar) of bio- optical and physical sensors provides spatial (horizontal and vertical) information. Satellite data indicating surface features in ocean temperature and currents are quite important. In addition, airplane based observations provided near surface bio-optical and temperature data and a sediment trap mooring located (at 15°59/N, 61°30/E) near our mooring array provided information concerning fluxes of particulate matter at depth. The collective data sets are critical for bio-optical and physical modelers. Some of these complementary data sets have been utilized in this thesis. AVHRR was investigated for its possible use to determine temperature features over the entire Arabian Sea. Some data that were made available for our work were processed by Bob Amone and his group at the Naval Research Laboratory. Our primary interest in AVHRR data was to identify a mesoscale feature that appeared near the mooring site in late November. This feature exhibits very little surface temperature 34 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. expression and has proved to be very difficult to observe using AVHRR data. However, AVHRR is a rich data-set that should be investigated for other time periods. Shipboard ADCP measurements were collected throughout all cruises (TN039 - TN055, September 20,1994 to December 31, 1995; see Flagg at el., 1995). The ADCP used for this work was an RDI four beam concave 153.6 kHz hull-mounted version. Figure 3.7 shows a map section done between 2:30am on December 4 and 5:00pm on December 5, 1994 during cruise TN042. This figure indicates predominately northward flow at the mooring site which correlates well with moored current direction observations (see figure 5.15). Results from ADCP data taken in a radiator pattern east of the mooring a day later are shown in figure 3.8. This plot shows current directions changing more than 90 degrees over distance scales less that 30km. The change in current pattern (direction) over the short time interval between these two surveys indicates that time scales as well as horizontal space scales are quite short. It is evident from these data that features on scales of 10's km as far offshore as 700km are energetic and important to flow patterns. 35 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 17.0’N 16.4*N 16.0'N 1S.6'N 0.0 25.0 50.0 Velocity (cm/s) 60.4'E 60.6*E 60.8*E 61.0‘E 6 U ’E 61.4*E 61.6’E 6l.8*E 62.0*E 6Z2*E 62.4‘E Figure 3.7 ADCP current vectors measured from 20m to 50m depth during 2:30 Dec. 4 - 17:00 Dec. 5 1994 cruise TN042 (courtesy of C. Flagg at BNL). 36 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. I6.0*N 1S.0*N 0.0 25.0 50.0 Velocity (cm/s) 63.5*E 64.0’E 65.0‘E Figure 3.8 ADCP current vectors measured from 20m to 50m depth during 3:40 Dec. 6 -15:30 Dec. 8,1994 cruise TN042 (courtesy of C. Flagg at BNL). 37 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Large scale wind stress curl was hypothesized to have a major influence in the Arabian Sea, by causing regional upwelling and downwelling as described in Chapter 2. Model results showing wind stress curl and wind stress are shown in figures 3.9 and 3.10 (principal investigator, John Kindle). In these plots, the arrows indicate wind stress magnitude and directions given in units of Pascals. The color shading indicates wind stress curl in units of 10"8 Pascals per meter. Details of this model can be found in Kindle and Phoebus (1995) and Phoebus and Goerss (1992). These maps show the large scale atmospheric wind patterns during the opposing monsoons, (e.g. SW during July and NE during Dec.) and effects of the wind curl. From the map for July 1995 (figure 3.10) we can see areas of coastal upwelling, whereas during December 95 (figure 3.9) we do not see this effect. It is possible that wind stress curl patterns over the open ocean may contribute to mesoscale current and temperature features. However, preliminary inspection of concurrent TOPEX and wind stress curl maps shown here do not suggest strong correlation. 38 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 2 II III Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 3.9 Wind curl and wind stress model results Nov. 16, 1994 (courtesy of J. Kindle at NRL). II III ' S . z X y ~- y . - y ~ z; t * k\ » .\ / > ! 1 V h V K • •* ' . K I t > f c h \ h ► * * J^V v V -V x b b > V \r t * ^ ' K \ \\ w s r " * f> ' V i \h • r ; « y < \ \ \ \ ' i ■ . A * = Z tt. z z 40 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 90 4. Description of annual time series The meteorological time series collected from the three separate mooring sites are not unexpectedly quite similar because or their relatively close proximity. Thus, we have chosen to describe data collected primarily from the central mooring which included our instruments. The dominant signal results from the NE and SW monsoons. Our most obvious indication of the monsoons is the wind direction and its steadiness. The NE monsoon is characterized by winds directed toward the southwest or at about 240° (due North is 0°) and the SW monsoon has winds directed toward the northeast at about 60° (figure 4.1). For our data sets, the NE monsoon condition appears to prevail during the period October 15, 1994 through about early March 1995 with winds of about 6m/sec. From March 1, 1995 through about June 1, the winds decrease in magnitude, are quite variable, and several wind direction reversals occur, marking the spring intermonsoonal period. The SW monsoon is clearly evident from June 15, 1995 through September 1, 1995 with persistent winds of about lOm/sec or greater. After September 1, winds begin to decrease in magnitude and wind direction begins to shift. The distinction 41 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. •o c a? 300 T J. u 200 b T 3 C 100 £ 0 C M < e 200 8 X 3 0 L L to < 1 ) _ X •200 C M « 0.4 Oct27 Dec16 Feb 4 Mar26 Oct12 Oct27 Dec16 Feb 4 Mar26 Oct12 2 Day Averages Dec16 Feb 4 Mar26 Oct12 JD94 300 350 400 450 500 550 600 Figure 4.1 Wind speed, wind direction, net heat flux & wind stress at the central mooring. 65 0 ith permission o f th e copyright owner. Further reproduction prohibited without permission. AirTemp Oct27 1020 Oct27 100 ^ J D S ^ f o u u Dec16 Dec16 Feb04 Mar26 May15 July4 Feb04 Mar26 May15 July4 Aug23 Aug23 Oct12 E. 1010 Oct12 Oct27 Dec16 Feb04 Mar26 Oct12 l D ^ 1000 4 > * L O o u u obO 4 0 0 4 5 0 5 0 0 5 5 0 6 0 0 Figure 4.2 Air & sea surface temperature, barometric pressure, relative humidity, and surface PAR. ith permission o f th e copyright owner. Further reproduction prohibited without permission. Daily Averages Oct27 Dec16 Feb04 Mar26 May15 July4 Aug23 Oct12 20 Daily Averages i 0 ) » 0 -20 Oct27 Feb04 Mar26 Dec16 May15 July4 Aug23 Oct12 Daily Averages Oct27 Dec16 Feb04 Mar26 May15 July4 Aug23 Oct12 Daily Averages E £ d ) Z -5 0 -100 300 350 400 450 YD94 500 550 600 650 Figure 4.3 Latent heat flux, sensible heat flux, net shortwave radiation, and net longwave radiation i in wind effects for the SW monsoon versus all other periods is most evident in the wind stress time series as the wind stress is proportional to the square of the wind speed (figure 4.1). Barometric pressure has an annual cycle with the highest values occurring in December 1994 through January 1995 in the middle of the NE monsoon and the lowest values in late summer during the height of the SW monsoon (figure 4.2). Air and sea surface temperatures have semi-annual cycles and are generally in phase with the peak values occurring in June and late fall for our study (figure 4.2). Incident solar radiation, which is modulated by cloud cover, also has a semi-annual signal with peak values occurring during the spring intermonsoonal period (figure 4.3). Relative humidity was generally greater and steadier during the SW monsoon (values of about 80%), with drier and more variable values occurring during the NE monsoon (figure 4.2). Sea surface temperature exceeded air temperature during the NE monsoon and the spring and autumn intermonsoonal transitions; however air temperature was generally slightly greater than sea surface temperature during the SW monsoon (figure 4.2). Two periods of several days exhibited the very lowest incident solar radiation and PAR(O-) during the SW monsoon (mid-July) and one stormy day in October had the lowest values for the entire record (figures 4.2 and 4.3). 45 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Some heat fluxes were determined from direct measurements and others were computed using state-of-the-art empirical relations applied to relevant meteorological data (e.g., Weller et al., 1990, Hosom et al., 1995). The net incident shortwave radiation heat flux contribution is generally the greatest of all terms. The sensible heat flux is generally quite small (maximum values less than 20W / m2 ), but changes sign annually (with few exceptions, only positive during the SW monsoon). The latent heat flux is the second most important heat flux term (figure 4.3). The lowest persistent latent heat fluxes occur after July 20 during the SW monsoon when relative humidity is steady and high (figure 4.3). Note that after July 20, 1995, the SW monsoon winds decrease significantly (figure 4.1). The highest and most variable values of latent heat flux occur during the NE monsoon (figure 4.2). The net longwave radiation, like the latent heat flux is steady and low (about 30 W / m2 ) during the SW monsoon (figure 4.3). Following cessation of the SW monsoon, the longwave heat flux increases about three-fold with greatest values occurring during the intermonsoonal periods. Finally, the net heat flux time series is generally positive (heating of the ocean) except for the period of mid-November 1994 through mid-January 1995 when it is persistently negative (figure 4.1). This latter condition can lead to convection in the near surface layer. The highest positive heat flux conditions occur during both intermonsoonal 46 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. periods and during the latter part of the SW monsoon (figure 4.1) or just after July 20th when the wind stress decreases. The net heat flux switches sign during the NE monsoon and at times is quite small in magnitude. Several competing upper ocean heating/cooling processes complicate the interpretation of the semi-annual heating cycle at our site as described in the overview in Chapter 2. The temperature and salinity time series obtained from the different moorings are similar despite differing methodologies, resolutions, and sampling regimens. However, it is likely that significant differences in the upper ocean physics do exist as a result of advection of differing water masses. This aspect is beyond the scope of the present analysis, but is extremely interesting and important. The upper ocean temperature structure exhibits a semi-annual cycle with the warmest temperatures (over 30°C) and shallowest mixed layers (5m) occurring during the spring intermonsoonal period preceding the SW monsoon (figure 4.4a, colorbar indicating °C). The year's two heat cycles are quite different, likely because of the differing wind stress and heat flux cycles as well as differing mesoscale activity. The choice of a criterion for mixed layer depth (MLD) definition is an operational necessity, but is somewhat arbitrary. Here, MLD is defined as the depth at which temperature at depth has decreased to a value of 0.1°C below the surface temperature value, or 1.0°C below the surface temperature. Clearly 47 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. o o > CO O .C D (UJ) L |jd 9 Q ° 0 .05 48 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. a choice of 1.0°C as opposed to 0.1°C results in deeper mixed layers. The temperature contour maps shown in figures 4.4a and 4.4b illustrate MLD based on the 0.1°C and 1.0°C criteria. The mooring was deployed during a relatively shallow MLD period of the fell intermonsoon in mid-October. This first half of deployment one will be discussed in detail in chapter 5. This time period is marked by at least one major cold sea surface depression (cyclonic flow pattern) possibly originating from a coastal filament or filaments. TOPEX SSH plots (figure 5.1-5.11) show depressed regions (negative SSH anomalies) encompassing the mooring site on October 15 and November 26,1994. In December 1994, the mixed layer (using a 0.1°C criterion) deepens to about 90m during the NE monsoon which coincides with a period when the net heat flux becomes small and eventually negative until mid- January (figure 4.1). At this time, heat flux becomes positive again and reduced wind speed and restratification occurs during the spring intermonsoonal transition. This is the period when the mixed layer shoals to a minimum of 5m. The intense heating of the late spring intermonsoon is evident as SST reaches its maximum (31°C) with peak daytime shortwave radiation exceeding 1000 W /m 2 . After June 15th the SW monsoonal winds start to blow. Almost immediately, SST decreases (figure 4.2), MLD deepens (figure 4.4), and the net heat flux becomes very 50 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. small, and sometimes negative (figure 4.1). Following the peak winds of the SW monsoon, the MLD (0.1°C criterion) reaches about 70m. Winds then decrease in magnitude but remain southwesterly, and positive net heat flux increases with resultant shoaling of the mixed layer in September to depths of about 15m (figure 4.4). It is interesting to note that an interruption of shoaling occurs during late August, early September 1995. Although this phenomena is beyond the scope of this document, it is similar to the interruption occurring at the onset of the NW monsoon (during mixed layer deepening) mentioned above. We hypothesize this effect to result from a SSH depression associated with a cold mesoscale feature. The currents observed during our observational year are most interesting, particularly in view of the fact that direct current observations in the Arabian Sea are so rare. The mean current patterns reported from historical data bases (e.g., Hastenrath, 1991) for our site suggest mean flows which are relatively weak, and Swallow (1983) has suggested that a high percentage of the current energy lies in eddy fields. Our mooring current time series certainly support Swallow's interpretation. The mean current patterns (based on ship drift) reported by Hastenrath (1991) show the following current directional senses at our site: January- toward the west- northwest; April- toward the northwest; July- toward the northeast; and 51 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 100 cm/sec 2 Day Averages 5m 10m 15m 25m 35m 45m 55m S * "* y .... „\w_. X * ^ " n |K 0 * ~ MtM/ Midi < i \ r— W ., n//H / .a J / 65m 80m 300 400 * ll|i • * 1 1 ! . . » * ■ ' S ' — 200 Ln N ) YD94500 600 Oct27 Dec16 Feb 4 Mar26 May15 July4 Aug23 Oct12 Figure 4.5 Current velocity vectors at the central mooring (north is up). i 700 I October- toward the west-northwest. These patterns are interesting but not particularly relevant to our study as they represent long-term historical records only. Time series of current vectors from the WHOI mooring for the upper 80m are shown in figure 4.5. The currents are highly variable in direction and magnitude with a few periods of very high energy currents dominating the records. The currents in the upper 80 m are remarkably uniform in direction and magnitude with depth indicating barotropic flow (e.g., Pond and Pickard, 1978). Two major mesoscale features are observed. The first is in Deployment 1 during the late fall intermonsoon through the onset of the NE monsoon in November and December 1994 and the second is toward the end of Deployment 2 during the latter stage of the SW monsoon. Currents in excess of 100 cm/sec occur during the former mesoscale event and in excess of 70cm/sec during the latter mesoscale event. Both events are characterized by doming of isotherms and relatively fresh waters, indicative of cold mesoscale features such as cold eddies or filaments (figures 4.4a and 4.11). The feature observed during the first deployment is described in detail in chapter 5. The vertical shear of horizontal currents is indicated in the VMCM data collected from the WHOI mooring (figures 4.6 and 4.7) and the PCM data of the UW mooring (figure 4.8). The maximum shear appears to 53 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. (.-S fO O issH -n r a q s Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 4.6 East shear measured fro m th e central mooring (courtesy o f B. Weller at WHOI). ( , s . . o i ) ip iO M .r e s q s Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 4.7 North shear measured fro m the central mooring (courtesy o f B. Weller at WHOI). Shear (s Ueptn < m ) Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 4.8 Shear measured b y th e P C M o n th e UW-S mooring at 15° I6’N 61" 44’E (courtesy o f C. Eriksen at UW). •0.02 001 0 0.01 0.0 2 0.03 Depth (m) Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 4.9 Buoyancy I'rcq. measured b y th e P C M o n llic IJW -S mooring al 1 5 " I6’N 61" 44’R (courlcsy of C. Erikscn at UW). a „ (kg/m3) Ueptn (m > Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 4.10 Sigma-thcla measured b y the P C M o n th e UW-S mooring al 15° I6’N 61° 44’E (courtesy of C. Erikscn at UW). generally coincide with the depth of maximum stratification or Brunt- Vaisala frequency (figure 4.9), at the base of the mixed layer (ML) which tracks the a© contour (figure 4.10) of about 25kg/m3 quite well for the deeper shear maximum. Density variation is primarily controlled by temperature as indicated in time-depth contour plots derived from the UW PCM data (figure 4.11). Shear is well developed and progresses downward in the upper 75m during the onset of the SW Monsoon (figure 4.8). Shear maxima do not always coincide with the depth of the MLD based on the 0.1°C criterion. Deep shear below the ML seems unrelated to near surface mixing and is likely due to internal dynamics (e.g. Rudnick et al., 1996; figure 4.8). An important derived parameter indicative of turbulent mixing is the gradient Richardson number defined as the ratio of the Brunt-Vaisala frequency squared to the vertical shear of mean horizontal currents squared or Ri = N2 / [ (Au/Az)2 + (Av/Az)2 ] Eq. 4.1 where N is the Brunt-Vaisala frequency. The UW data set has been used by Eriksen to compute such a Richardson number over 10m depth intervals (Az) based on 5m average data. This analysis shows Richardson numbers on order of 1 or less (indicative of a strong tendency for mixing) 59 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. during the periods of December- February in 1994 through depths of roughly 90m and during the early portion of the SW monsoon down to depths of 75m (figure 4.12). This analysis has special importance for phytoplankton at the site as nutrient entrainment into the upper layers should occur during the deep mixing periods and enable new primary productivity. Several water masses with differing temperature-salinity characteristics advect past the mooring site. The observed salinity time series is illustrated in the contour time series of salinity with superimposed temperature in figure 4.11. During Deployment 1, cool and relatively fresh waters are observed during the mesoscale event seen in the current record in November and December. Salinity then increases and remains relatively constant and uniform to a depth of about 100m until early March when more saline waters appear. The highest salinity's occur in the upper layer (50m and shallower) in May and June just before the SW monsoon begins. Cool relatively fresh waters are observed beginning in August and coincide with the mesoscale feature described earlier. Relations between the bio-optical properties and water mass and nutrient characteristics should prove informative. Measurements obtained with the MVMSs show high variability associated with both monsoons and mesoscale features advecting past the 60 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. mooring. A time-depth map indicating chlorophyll concentration variability is shown in figure 4.13. The semi-annual cycle is apparent with the highest chlorophyll levels occurring during the NE monsoon and through the early portion of the spring intermonsoonal period and during the SW monsoon through the autumnal intermonsoonal period. The depths of penetration of high chlorophyll levels increase after the onset of each monsoon. The passages of energetic mesoscale features (figure 5.8 and 5.12) during each monsoon are evident in high concentrations of chlorophyll (figure 4.13) as well as high currents and doming isotherms (figure 4.5 and 4.4a). It is likely that upwelled water (associated with doming isotherms) results from mesoscale features on scales of 10-200km, according to SeaSoar surveys and TOPEX altimetry data (sea surface height anomalies). This will be discussed further in Chapter 5. 61 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 35.2 35.4 35.6 35 8 36 Salinity (PSU) 36.2 36.4 36.6 -I----1 __ L _ — I --- 1 ----1 ----1 ----1 ----1 _ _ I __ I ----1 __I_ _ u -I .-- 1 ---1 _i_i __I __,_i_L 25 - 50 - 75 - E 6 100 - 125 - 150 - 175 - 200 -> I r 0 - 25 - 60 75 - 100 - 125 - 150 - 175 _ r _., -j , 1 -- '-- '-- T ~ |--- ■ ----1 —7---1 - C T \ K > -|---.---1 ----1 --- 1 — i- | Ocl 1 Oct 31 Nov 30 Dec 30 Jnn 29 Feb 28 Mai 30 Apt 29 May 29 Jun 28 Jul 28 Aug 27 Sepl 26 Ocl 2 6 274 304 334 364 29 59 90 119 151 179 209 239 269 209 1994 • 1995 200 Figure 4 .1 1 Temp, contours and sal. from the I’CM on the UW-S mooring at 15" I6’N 61" 44’fi (courtesy of C. Erikscn at UW). ( u j ) ta d e n Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. Tan'1 (Ri) [degrees] Aug 27 Sopl 26 239 269 Figure 4.12 Richardson num. measured by the PCM on (lie UW-S ' g at 15° I6’N 61" 44’E (courtesy of C. Grikscn al IJW). fiu) uider C9C Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 450YD94 500 Mar26 May1 300 Oct27 350 Dec16 650 Oct12 Figure 4.13 Chlorophyll a measured using stimulated fluorometers at 10,35,65,and 80m at the central mooring I 5. Description of Mesoscale Event October 15 - December 25, 1994 5.1 TOPEX Results In the following discussion, current directions described from TOPEX data are interpreted from observed sea surface height anomalies (SSHA; provided by Lakshmi Kantha and Jim Hendricks). Inference of current features from TOPEX data are based on geostrophic balance (e.g., Pond and Pickard, 1978). For example, circular depressions result in counterclockwise (cyclonic) flow in the northern hemisphere. Note that relatively cool waters have negative values of SSHA whereas relatively warmer waters are characterized by positive SSHA. The following descriptions refer to features in SSHA (e.g. depressions (cold) or elevations (warm)) and directly measured VMCM current directions. Generally, mooring current measurements within the upper 80m are uniform in direction (barotropic, see figure 5.15) and are qualitatively consistent with directions inferred from TOPEX SSHA. Length estimates given for distances from the mooring to mesoscale features are defined to be to their approximate geometric centers based on images shown in this thesis. TOPEX Cycle 74 (Sept. 16 - Sept. 26 1994) is shown in figure 5.1. This represents the area one month before the mooring deployment (Oct. 20, 1994). Note the mesoscale feature (in this case a sea surface depression) 65 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. o 0 3 Qi Qi o o , ■ C D C O L T 3 C M O C M C O C M Q. © C O a C O Q. © 05 K. a & O X: UJ a . O L ia C M V C M N " I C O 03 • C O o 03 U 3 C M C M C O 03 • C O C M r- U 3 C O ■ C M U3 h U3 1-0 L O O C M Figure 5.1 TOPB( sea surface height altimetry (cm). 66 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. C D LQ C M C M t - - r - Rgure 5.2 TOPB( sea surface height altimetry (cm). 67 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. M * < 3 > Qi C O 4 m o o 4 m C O 4 m U O C O N. 8 . o X: m a. O K C M '« ■ C M % CO C O I C O o co • U > cm cm o o ■ CO CO CO CO CO C M r - * L O H CO N T • C M LO O C O I L O ^ C M o C M LiO h L O L O Rgure 5.3 TOPEX sea surface height altimetry (cm). 68 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Tf 05 05 C O C M 4 m U o o C O 4 m O O K. N. ,© O X Ul a. O O J 'f C M I " > C O C O I C O o C O LO “ M " C M C M O ' • C O C O CO C O C O C M rv L O H C D ■ M - • C M LO L O C M O C M I — LO L O LO Rgure 5.4 TOFBC sea surface height altimetry (cm). 69 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. < 3 > Oi co CO O 5 : o 4» C O C M u O co K -2 s . o X Ul e x . O O J C M % C O 03 a GO O 0 3 • LO CO O J CO S i B o n C M LO H CD • C M LO Rgure 5.5 7OP0( sea surface height altimetry (cm). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission 05 0 5 U 5 O o 4 m «5 O 0 5 N. 8 . o c: o 5 05 C O O a. J'V I * 5f C V I C O 0 3 ■ C O o 03 t U3 S i C M o a ■ C O CO C O 03 C O rv LO r C O • C M LO L O C M O C M .L O LO L O o C M Figure 5.6 TOPBC sea surface height altimetry (cm). 71 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. r \ \ C M L Q [H? % H C D V • C M LO Q G O JD £ o X; Uj a. O k C M C D O V ^ C O 0 3 C M t * • i ■ * — C O LO c\j (M -r- Rgure 5.7 TOF0C sea surface height altimetry (cm). Reproduced with permission of the copyright owner. Further reproduction prohibited without permission T — CO LQ C V J Oil t- <r- Rgure 5.8 TOFEX sea surface height altimetry (cm). 73 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. a co o 0 1 • C D C O LO C M O C M LO © CJ o » X > o Q ) Q 00 J ) R O >< Uj a. 0 K C M C M M ¥ C O co ■ C O o co • LO C M t C M C O co C O C M I s* LO C O V C M I L O LO LO O C M Figure 5.9 TOFEX sea surface height altimetry (cm). 7 4 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. O b Ob lO C m o O b o a •o o V Q C O 00 a * o V : U J C L o C M C M " i > 1 .. C O C O ■ C O o C O L O C M s C M O o • C O C O C O C O C O C M r> LO C O I • C M L O LO C M o C M LO LO LO O C M Rgure 5.10 TOPB< sea surface height altimetry (cm). 7 5 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.11 TOPB( sea surface height altimetry (cm) Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. o o C O < 3 * o 0 1 C O C O LO N T C M o a i Q C M C* 3 2 Q c» N. Q -3 > o 5S O >< UJ a. O C M C M % " 1 C O C O • CO a c o to ' ! ] C M C M C O C O C O C M 1 ^ LO C O •c • C M LO LO C O o C O LO C M o C O LO CO o LO 05 O LO C M Rgure 5.12 TOPEX sea surface height altim etry (cm). 7 7 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. approximately 250km off the coast near 16° 30'N and 58° E. Over the next 20 days this feature elongates and advects offshore toward the mooring site at 15°30'N 61°30'E (see cycles 75 and 76 in figures 5.2 and 5.3). Figure 5.3 indicates that a sea surface depression (approx. 200km across) is encompassing the mooring site, and the temperature record (figure 5.18) appears consistent with this interpretation. TOPEX cycle 77 (Oct. 16 - 26, 1994; figure 5.4) coincides with the time of deployment of the moorings at 15° 30'N and 61° 30' E. Figure 5.4 indicates that the mooring is on the south to southeast side of a SSHA depression, approximately 60km from its edge. This is consistent with moored current measurements showing eastward to northeastward flow (see figure 5.18). Ten days later (Oct. 26 - Nov. 5; depicted in figure 5.5), the feature moves north (approximately 50km) of the mooring. The mooring site is then in a less depressed region and mooring currents are then eastward to southeastward. Over the next twenty days (Nov. 5-25; figures 5.6 and 5.7), the feature's center (depression) lies approximately 125km north to northeast of the mooring site and the site is on the edge of the feature. During this period (Nov. 5 - 25), currents at the site flow southeastward. Interestingly, the mixed layer depth (MLD) reaches a relative maximum during this time (figure 5.18), which follows from TOPEX indications that SSH is increasing as the cool feature moves northward and sits north of the mooring site. During the 78 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. period November 25 through December 5, the feature is located further south, clearly encompassing the mooring (see figure 5.8). This SSHA depression is evident in the mooring time series. One indication is mixed layer shoaling, expressed by doming of the thermocline (see figure 5.18; Nov. 26). Another indicator of the passage of the depressed region is the following: 1) strong southeastward current, 2) currents then decreasing reaching a relative minimum on November 26, 1994 (YD330; figure 5.16), and 3) currents then switch to a northward direction. It appears that the extreme southeast portion of the depression passes over the mooring on November 26, 1994 (YD330), with a transitional direction toward the south. After December 5, 1994, depicted in figures 5.9, 5.10, and 5.11, the depression weakens and the feature moves toward the southwest leaving the mooring between a depression (-10cm) and an elevation (+10cm), which leads to northward geostrophic flow which is consistent with mooring currents from December 5th through December 30th, 1994. During the SW monsoon, mesoscale variability is also apparent during the shoaling of the ML about midway in the monsoon as seen in temperature contours of figure 4.4 and from TOPEX data shown in figure 5.12. The SW monsoon mesoscale activity is not the focus of this chapter, but it does reflect the importance of the high energy found in the mesoscale features observed in this region as suggested by Swallow (1983). 79 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 5.2 Mooring Results During the first deployment, a major advective event is observed between roughly October 17 and December 25,1994 (figure 5.18). The wind speed is fairly constant at about 6m/sec and the direction is about 230° (from the northeast) except on October 23 when a low pressure system passes over the site (figure 4.2). This system results in the highest winds (-17 m/sec) recorded during Deployment 1 and the NE Monsoon. The incident shortwave radiation is also relatively steady (daily peak values of about 900 W /m2 and daily average of 220 W /m 2 ) except during the day of the storm (October 23). The net heat flux is generally positive (heating of ocean) until about November 20 except for October 24 (wind event) when it is negative (figure 5.13). However, from November 20 to mid-January, the net flux is almost always negative, primarily due to increased loss of heat through latent heat flux (figure 5.14). Note that the humidity decreases on about November 21 as the typical dry NE monsoonal air (Tchemia, 1980) advects past the mooring site. This is the only extensive period of heat loss from the ocean for the entire observational year. The currents within the upper 80m start toward the east and then briefly rotated clockwise (toward the southeast, figure 5.15). They then 80 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. I T J d ) C D CL CO T 3 C 15 10 5 0 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 T J £ 100 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 100 - S * E 2 Day Averages X 3 L L -100 T 5 a > I 290 300 310 320 330 YD94 340 350 360 370 0 0 Figure 5.13 Wind speed, wind direction, and net heat flux at the central mooring. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. AirTertip SSf : ' 0 28 < 2 4 Oct27 Oct17 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 S' | 0.6 In 0 4 a) £ 0.2 I i i i !' f i..... ;...................•.....................•............... =- Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 < -100 0 - 3 0 0 0 0 ro 290 300 310 320 330 YD94 340 350 360 Figure 5.14 Air & sea surface temperature, wind stress, relative humidity, and latent heat flux. 370 slowly rotate counterclockwise from October 27 until December 25 (figure 5.16). The speeds at 35m are in excess of lOOcm/sec during October 28 to November 6, the largest values seen for the entire year (figure 5.17). Slightly higher speeds occurred at shallower depths and somewhat lower values are found at greater depths. The cross-over point for the current direction is about November 26 (YD330) when currents decrease to about 15 cm/sec before they increased again (figure 5.17). This is consistent with the current patterns inferred from the TOPEX altimetry data (see chapter 5.1). Again, current magnitudes and directions are remarkably similar through the upper 80m, characteristic of barotropic flow patterns. The vertical shear of the mean horizontal currents is modest; however some shear is evident in the vicinity of the base of the mixed layer (figure 4.8). The gradient Richardson number decreases to 0(1) around December 15 after passage of the cold feature (figure 4.12). It should be noted that the surface net heat flux is negative during this time which suggests convection may have been occurring and may be largely responsible for the deep mixed layer. Shear in the upper 100m is modest, thus the gradient Richardson number is low primarily because of low stratification (figure 4.9). Toward the end of November, southeastward currents decreased (constant with depth), and continued rotating counterclockwise. 83 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 100cm /sec 1 Day Averages w 11, / / 11 111\\\\ w \ I I V W n w / / / /// / 1 1 1 \\\ 11\\\ I t uWWWW w v \ \ \V W i v \ \W w i C x -^/ll/lull ili/l\\\\\W\ /1 1 1 1 /|\\\ n w w w w w w w w i> \ ' W i / / n i \ /i 1 1 1 /i \\ I /IWKWWWwwm (* \ W / / / , I I t l \ w i \ \ w \ llW \\\\\\\\W \V s \, k \ h i /, 11111 1 \ i\ 11\ u I M \ \ \ W i ts\ y/l\ll\ i\\W i\ u ww\ i kW W XW W vXxxs^ 11\\ _ L 290 300 310 320 330 YD94 340 350 360 370 “ Oct17 Nov 6 Nov26 Dec16 Jan 5 Figure 5.15 Current vectors m easured at the central mooring (north is up). Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 100 cm/sec 2 Day Averages 290 300 310 320 330 340 350 360 100 - < / ) o 15 Minute Averages 00 Ln 290 Oct17 300 310 320 330 YD94 340 350 360 Nov 6 Nov26 Dec16 370 Jan 5 Figure 5.16 35m MVMS velocity vectors and zonal & meridional components i w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 120 | 100 o "S 80 35m 80m Q . 40 20 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 1 Day Averages Z 300 $ 100 35m 80m 290 300 310 320 330 YD94 340 350 360 370 00 Figure 5.17 Velocity magnitude and direction at 35m and 80m central mooring. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 100 cm/sec 2 Day Averages 290 300 310 320 330 340 350 360 290 300 310 320 330 YD94 340 350 360 370 Oct17 Nov 6 Nov26 Dec16 Jan 5 Figure 5.18 35m MVMS Velocity vectors and temperature at the central mooring i I i i ith permission o f th e copyright owner. Further reproduction prohibited without permission. 0-22 35m h- 2 0 80m Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 =) 36.2 £ 35.8 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec 16 Dec26 Jan 5 =*24 E 25 o > 290 300 310 320 330 YD94 340 350 360 370 CD 00 Figure 5.19 Temperature, salinity, and density in upper 80m at the central mooring. C D C M ID in ' C M in C M in C M C M in cd C M C O C M in o co ® O C M (uu) MldQQ 89 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Figure 5.20 Density contour and 0 .1 degC M L D a t th e central mooring The transition of the meridional component from southeastward to northeastward then northward coincided with the relative minimum in current speed as weE as the peak of the subsurface isotherm doming (MLD rise to 30m) of cool, relatively fresh waters as seen in figure 5.18. Salinity increased after passage of the feature by about 0.2 PSU (figure 4.11). The mixed layer depth is controUed primarily by temperature as opposed to salinity (figure 4.11). Current shear has a relative maximum (figure 4.8) which roughly coincides with the MLD based on the 1.0°C criterion (figure 4.4b) and the 25Kg/m3 isopycnal (figure 4.10). The contour plots indicate the gross features associated with major mixing and mesoscale processes. However, water properties of the Arabian Sea are highly complex (Tchemia, 1980) as evidenced by temperature-salinity relationships (e.g., analysis by C. Eriksen not shown here). Thus, time series at some fixed depths are presented here to iHustrate the degree of variability at scales down to several hours. Temperature, salinity, and sigma-t time series (4 hour averages) are shown for the period YD 289-370 or October 17 1994 - January 5,1995 in figure 5.19. High frequency variability on the scale of a few hours is superimposed on the longer (week-month) time scale variability. The time series of temperature, and sigma-t track extremely weE through the upper 80m. The salinity time series suggest a major transition in water masses from 90 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. November 16 - November 26 (YD 320-330) which is very near the time of minimum currents (figure 5.18) and direction change from southeastward to northeastward. The mixed layer depth changes over time scales on order of 10 days. The near surface temperature (1.8m and 10m seen in figure 5.19) does not reflect the large temperature variability evident at greater depths (e.g. 35m seen in figure 5.19). These observations are noteworthy in that satellite temperature sensing (e.g., AVHRR) would not observe the subsurface feature because of lack of surface expression. However, satellite altimetry (TOPEX) which integrates the subsurface temperature effects apparently does resolve such features. Time series of bio-optical variables were limited in length because of anticipated biofouling problems. Nonetheless, interesting bio-optical variability is observed during the event. The surface shortwave measurement is used to estimate PAR just below the surface using the following empirical relationship (Siegel and Dickey, 1987) PAR(O-) = 0.117 * Ed(0+) + 3.6 Eq.5.1 91 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Time series of noontime averages (average value from 11:30 - 12:30 each day) of PAR at O ', 10m, 35m, 65m and 80m are plotted in figure 5.24. The diffuse attenuation coefficient of PAR is derived from the relation KPAR (0-35) = -[ In (PAR 35) - In (PAR 0) ] / (35 - 0) Eq. 5.2 KPAR (0-35) is shown in figure 5.22 and will be discussed shortly. KPAR was also used to calculate the depth of the one percent light level (1% LL Depth) from the relation: 1 % LL Depth = - ln(0.01) / KPAR(0-35) Eq. 5.3 which is shown in figure 5.25 with MLD. These important parameters will be discussed in the remaining sections. Note that inferences are made about primary production below. These are based on our data which do not include direct primary production measurements. However, other scientists involved in this study have collected Cu measurements, but their data are not available yet. Thus, in the future quantification will likely be possible. Chlorophyll data presented in this thesis are based on stimulated fluorometer measurements. The large community involved in this project has yet to reach agreement on the absolute values of 92 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. measured chlorophyll (U.S. JGOFS NEWS, 1996). Therefore chlorophyll values are subject to revision. Chlorophyll data presented here have been calibrated by John Marra at LDEO and full documentation on the method used can be found in Ho et al., (1996). We believe that these values may be approximately 50% low (pers. commun. Burt Jones), but for lack of a concrete solution to date, these data are presented here. Thus, the main points of the following discussion should be considered only in a relative sense. Chur data suggest that there was an interruption during the onset of the NE monsoonal response of the upper layer at our site because of an encounter with a cold core feature in late November, 1994. This is evident in the ML depth increasing in early November, shoaling in late November, and then increasing again reaching its maximum by mid- December. The next few paragraphs describe this in detail. Some of the key 35m MVMS data are shown in figure 5.21. The upper two panels show two-day average velocity vectors and 15-minute average time series of temperature. The lower two panels show PAR and chlorophyll a (chi a; as determined from a stimulated fluorometer as discussed in Appendix AI). A cool mesoscale feature encompassed the mooring site when the mooring was set on October 15, 1994 (see SSHA 93 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Reproduced w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 100 cm/sec 2 Day Averages WWWW \ W \ W 290 300 310 320 330 340 350 360 370 15 Minute Averages ©24 o © CO 9* 200 £ § 1 0 0 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 cc < CL 0 Jill Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 V O 4 ^ Dec26 T Dec26 290 300 310 320 330 YD94 340 350 360 Figure 5.21 35m MVMS Velocity vectors, temperature, PAR, and stimulated fluorescence. Jan 5 Jan 5 to 0.3 ° 0 .2 5 370 depression region in figure 5.3). This is considered the mooring's first encounter with the feature. The cool feature moved to the north of the mooring and then drifted south again encompassing the mooring site approximately 25 days later. This is considered the features second encounter. During the mooring site's first encounter with the cool feature (at the beginning of the deployment: Oct. 15 - Oct. 26 1994; figure 5.21) observations from the 35m MVMS show; 1) eastward flow, 2) relatively cool but warming water, (35m sensor is below MLD; also seen in figure 5.18), 3) reduced scalar irradiance (5-fold compared to Nov. 6 when 35m MVMS is in ML), and 4) elevated biomass concentrations (indicated by chi a levels greater than 0.3 |xg/l). The 1% LL depth during this period (before Oct. 26) is variable (see figure 5.25), starting above 50m then suddenly deepening to nearly 60m after October 23 or the day the storm arrived (the storm is the low pressure system mentioned earlier). Before October 23, chi a concentrations at 10m and 35m were greater than 0.8 and 0.3 pg/1 respectively (see figure 5.23). The 65m instrument did not measure elevated chi a, and is believed to be in a relatively light limited region. Immediately after October 23, chi a concentrations at 10m decrease (from 0.8 to 0.4 (ig/1), the 1% LL decreases to 65m and immediately the biology near 65m responds with chi a increases from 0.075 to 0.11 pg/1 (see figure 5.23). Due to the lack of light absorbers in the upper water column (just 95 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. after Oct. 23), light is allowed to penetrate deeper and presumably stimulate growth deeper, which is what we observe at our 65m MVMS (see figure 5.23). The 35m chi a values just after the storm fluctuate and decrease a small amount. As was discussed in chapter 5.1, the cool feature is observed to move northward according to TOPEX data. During the period (Nov. 1 - Nov. 16 1994; see figure 5.21) when the feature is north of the mooring site it has the following characteristics as observed at 35m: 1) southeastward flow, 2) constant and relatively warm temperature as the 35m MVMS is lying in the ML, 3) relatively high PAR, and 4) low levels of chlorophyll concentrations. Note that during this time period (Nov. 1 - Nov. 16), the 65m MVMS, which is below the ML, (figure 5.18) indicates elevated levels of biomass (see figure 5.23). The 1% LL depth descends down to 70m reaching a relative maximum during this time period (see Nov. 3, figure 5.25). Indications are that reduction in biomass (light absorbers) in the surface layer allow light to penetrate down to 65m and to stimulate growth. It is believed that organisms at 65m are relatively light limited before November 1. As we will see later, they are then again light limited after Nov. 16 (see figures 5.23 and 5.25). Another hypothesis is that the elevated chlorophyll values at 65m may result from sinking phytoplankton. 96 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. After November 16, 1994 the cool feature that has been observed for the past 20 days about 120km north of the mooring site begins to move southward toward the mooring site once again. The feature likely interrupts the bi-annual deepening of the ML associated with the NE monsoon. The 35m MVMS currents (figure 5.21) show a counterclockwise rotational sense during this period (Nov. 16 - Dec. 15). The temperature signal once again shows the ML shoaling to less than 35m (figure 5.18) with a MLD relative minimum of near 20m on November 26 (YD330). Noticeable bio-optical effects occur with the cool feature once again encompassing the mooring site (Nov. 16 - Dec. 10 1994). Changes in properties include: 1) reduced PAR below the surface (figure 5.24), 2) elevated biomass concentration to 0.3 pg/1 at and above 35m (figure 5.23), 3) shoaling of the 1 % LL depth to a relative minimum at 50m (figure 5.25), and 4) decrease in biomass concentration at 65m (values below 0.1 |ig/l; figure 5.23). Indications of the return of the feature for the second time are very similar to its first visit in late October. Once again this feature reduces the MLD, with the appearance of cool fresh water (presumably associated with upwelled water). This has the effect of increasing chi a (especially at 35m where values change from below 0.25 to about 0.30 JJ.g/1), probably due to new transport of nutrients into this region. With the elevated biomass (light absorbers) now present in the near surface region, 97 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. the 1% LL depth shallows to 50m, reducing the light necessary to sustain growth at 65m which is evident by the decrease in the 65m chi a signal (see figure 5.23). Time series of KPAR (0-35) are shown in figure 5.22 along with chlorophyll fluorescence. Dining the cool feature's first visit to the mooring site, elevated levels of chlorophyll fluorescence (>0.3 (ig/1) at 35m were observed along with reduced PAR at depth and increased values of KPAR 0-35 (greater than 0.1). The interim period (Nov. 1 - Nov. 16) is characterized by low values of Oil and KPAR which coincides with warm water and greater mixed layer depths (about 50m see figure 5.18) and 1% light level depths to 65m (from 50m during events, see figure 5.25). Importantly, this interim period was marked by higher Chi values at 65m; however KPAR (0-65) did not track this signal (see figure 5.23) likely because the KPAR (0-65m) is measuring biomass attenuation only in the waters above 65m. Unfortunately the 80m PAR sensor was not functioning so no estimates of KPAR (0-80) could be made. During the feature's second encounter, centered on November 26, again we see elevated levels of chlorophyll fluorescence (>0.3 (i.g/1, or an 80% increase) at 35m, reduced daily average PAR at depth (by 50%), and increased values of KPAR (0-35) (from 0.07 to 0.10). It is important to note that during the event, the variability in chlorophyll fluorescence at 35m and KPAR (0-35) 98 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. w ith permission o f th e copyright owner. Further reproduction prohibited without permission. 2000 C M 1 0 0 0 0 - m PAR Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 1000 10m PAR 500 Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 0.14 0.12 0.1 0.08 0.06 KparO-35 : < 0 Q. * Oct17 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Jan 5 35m Chi a 0.3 : 4 Hour Averages 290 300 310 320 330 YD94 340 350 360 370 VO Figure 5.22 Noontime averages of PAR at 0 - and 10m, KPAR(0-35), and stimulated fluorescence at 35m. i 0 0 CD o d d (l/6n) b m o L T > c o in C M in T— T— C O C D C O o o o o o o o o o o o (l/6n) b m o (|/6n) b m O dVd>l 1 0 0 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. w ith permission o f th e copyright owner. Further reproduction prohibited without permission. §2000 * £ 1000 § n EC < 1000 ~ v-----" - — vV /n tm Oct17 o 0 ) < / ) « E lD cc < CL 500 0 Oct17 200 h 100 Oct17 o © W * CM 20 10 '0 Oct17 l 2 in GC < CL 0 Oct27 Oct27 Oct27 Oct27 Nov 6 Nov16 Nov26 Dec 6 Dec16 Nov 6 Nov16 Nov26 Dec 6 Dec16 Nov 6 Nov16 Nov26 Dec 6 Dec16 Nov 6 Nov16 Nov26 Dec 6 Dec16 Dec26 Dec26 Dec26 Dec26 Jan 5 i i i 1 i i i " 1 “ i 10m Jan 5 ........................... \ ■ /V .................................. ..................... : ................. ............................................... . ............. " ................. .............: . . . ............................................... — ■ ?5m Jan 5 A 1 — . — j65m i Jan 5 1 80m r ................ i . _ L A > \ f \ 290 300 310 320 330 YD94 340 350 360 Figure 5.24 Noon values of PAR at surface(O-), 10m, 35m, 65m, and 80m at the central mooring. 370 C O ® lO C O Q . O C O C O in o CO® C O O C M C O > C O O C M C O O C O O o 00 o o C M o o C O o o C O O) c 'u o o E ( 0 u - c 0 o 0 n 0 0 > 0 £ O) " D c 0 o O ) 0 " D Q . 0 ■ O 1 — 0 > > _ 0 ~o 0 X i n C M i n £ 3 O ) i i . (tu) m d e a 1 0 2 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. track quite well (figure 5.22). It is noteworthy that from October 17 through December 16 the MLD 0.1 and the 1% light level track each other (figure 5.25). The 1% light level lies about 20 to 30 m deeper than the MLD. However, the MLD 0.1 and 1% light level depth then converge and cross each other around December 16. This occurs primarily because of the rapid deepening of the MLD while the 1% LL depth remains at approximately the same depth. This suggests that the integrated biomass (down through 65m) is remaining constant during this time. A plot of PAR (on a log scale) vs. depth is shown in figure 5.26. The colors on the plot indicate increasing time in the rough order dark blue, light blue, green, yellow orange, and red where dark blue is October 16, 1994 (YD289) and red is December 18 (YD352). The asterisks indicate data points at O ', 10, 35, or 65m. A straight line from the surface to 65m indicates that KPAR is constant over the upper 65m of the water column. The light blue lines (light blue is approximately Nov. 1 - 16) are very linear indicating KPAR is constant with depth. This correlates with the period of a homogeneous layer to 40m (MLD equal to 40m see figure 5.18) and thus, we can presume that biomass is distributed uniformly in this layer (figure 5.23). It needs to be noted that KPAR (0-10m) is biased because red light is attenuated faster than other wavelengths. However, during this period when we observe the linear region, indications are that our PAR (O ') 103 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 00 C M T “ " o o < D 0) w 0 5 C M CO C M C M T — > > > r\ r> o > co CO C M o o O O O C O O O i n o ( l U ) m d S Q 104 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. P A R (uE/(mA 2*sec)) N O T E L O G SCALE Figure 5.26 L o g o f P A R vs. Depth, colorbar indicates increasing time. estimate from the surface incoming shortwave radiation seems reasonable. After mid-November (yellow, orange, and red) the KPAR estimate is no longer constant with depth, which indicates uneven amounts of biomass from the surface to 65m. This period correlates nicely with the second passage of the feature mentioned above when the MLD shoals to 20m and the 1% LL shoals to 50m, thus indicating a non-uniform upper water column with respect to biomass distributions. 105 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. 6. Summary and Conclusions The Arabian Sea is one of the most interesting and unique regions of the world's oceans. From our study it has proved to be a very complex region. This thesis has described some of the phenomena observed during the first half of Deployment 1 (Oct. 15, 1994 - Jan 5, 1995). This chapter summarizes that period, and then answers two questions posed in Chapter 1. On October 15,1994, five moorings were deployed in the Arabian Sea in an area of sea surface depression. This feature appeared to have formed through coastal upwelling and advected offshore about 550km to the mooring site. Before October 23, the feature, likely relatively rich in nutrients, may have had stimulated growth above the 1% LL depth, while areas below the 1% LL showed reduced biomass probably due to light limitation. KPAR values were not constant with depth above 65m. This was the result of the non-uniform distribution of biomass concentrations in the upper 65m. A low pressure system passed through the area on October 23, 1994, and although it did not have profound effects on the temperature and current structure in the region, the biology was evidently greatly affected. The biomass was redistributed after this event as expressed in rapid chi a concentration changes with depth. Almost immediately, the 1% LL depth increased from 47m to 65m. Although the 35m chi a values remained relatively constant (decreasing slightly), the 10m chi a values decreased by 50% over a few days. Light, critical for primary production, was then able to penetrate as deep as the 65m MVMS, and increasing levels of biomass were 106 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. beginning to be observed at 65m. Sinking of phytoplankton may also contribute to this. The NE monsoonal ML deepening event began November 1, 1994, however waters in the mixed layer continued to warm until about November 6. This period (Nov. 1 - Nov. 20) showed indications of decreased biomass at and above 35m. This allowed light to penetrate deeper which is indicated in the 1% LL depth reaching 70m. Thus, during this period, the 65m MVMS was below the mixed layer and above the 1% LL depth, and the stimulated fluorometer at 65m indicated elevated biomass. The KPAR (0-35) tracked the 35m chi a values closely. However, KPAR (0-65) did not track the 65m chi a values. It would be helpful to examine KPAR(0-80), but PAR (80m) data were unavailable. During this case (November 1 - November 16) it seems likely that the chi a increase observed at 65m was due to light now reaching this depth. TOPEX data show the cold feature to be located north of the mooring site during the period just described. After about November 16, the feature seemed to move south, and during the period November 16 - December 15 it encompassed the mooring site. This was clearly expressed in the seasonal MLD record as an interruption in the bi-annual ML deepening as the cool feature advected over the mooring site. With its return, elevated chi a values were recorded first at 35m then at 10m as the MLD elevated. This feature likely brought with it nutrients that were essential for phytoplankton growth. As biomass increased at 35m and 10m, more light was likely attenuated in the upper water column. This is seen in the shallowing of the 1% LL depth as 107 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. well. There was no longer enough light reaching the presumably nutrient rich region at 65m; thus, chi a signals decreased during this time period (Nov. 16 - Dec. 15). KPAR (0-65), KPAR (0-35) and chi a at 35m track each other very well during this period. Apparently , coupling of physical forcing and biological productivity caused changes in die diffuse attenuation coefficient of light (KPAR). KPAR during the NE monsoon varied from about 0.07 to 0.11 m'1 . Thus, the radiant heating rate and radiative penetrative heat flux at depth was likely strongly affected by biomass concentrations on time scales of O (1 month). Since the net heat flux was at times close to zero during the NE monsoon, phytoplankton productivity may play a pivotal role in the heating rate and thermal stratification of the upper layer as well as in balancing the upper ocean heat budget. The first question posed in Chapter 1 asks what processes caused variability in the physics and the biology. The ML deepening observed during the SW monsoon showed that wind forcing over a highly stratified upper water column caused shear and thus mechanical mixing ensued. However, during the NE monsoonal bi-annual ML deepening we observed heat loss at the surface resulting in an unstable water column, and convection ensued. Historical data sets have suggested that events on seasonal scales such as monsoonal wind driven currents are dominant in the region of the Arabian Sea. This means that strong constant winds over several months drive the major flow patterns. Many studies supporting this perspective have used long-term (10 year) climatological data sets. The monsoonal seasons 108 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. have been commonly described as the fall intermonsoon as September - November, the NE monsoon as December - February (where a strong NE wind drives southwestward flow), the spring intermonsoon as March - May, and the SW monsoon as June - August (where a strong SW wind drives a constant northeastward flow). During the NE monsoon, our observations at the mooring site showed: steady northeasterly winds (less than 8 m/s), mean currents which were not southwestward, and clearly mesoscale variability dominated most of this season. It is possible that the year of our study was not a typical year, but it is more likely that mesoscale energy is almost always quite important in the Arabian Sea. During the SW monsoon our observations at the mooring site showed: strong and steady southwesterly winds (greater that 10 m/s), current flow direction during peak winds were NE but very small, and large energetic mesoscale events advected past the mooring again. These mesoscale features produced currents at the mooring site flowing southward during relative peaks of the SW monsoonal winds (winds greater than 10 m/s). The high energy that occurred at the mesoscale was not an expected outcome during the planning stages of this experiment. More specific, filaments reaching approximately 550 km offshore were not hypothesized. Advection of features dominated flow patterns at the mooring. It should be noted that our observations were for one year at one point in the Arabian Sea. Studies of average flow direction for several years would average out mesoscale features, eliminating the appearance of the mesoscale features that dominated parts of our annual time series. 1 0 9 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. It is likely that the major mesoscale event described in Chapter 5 had a coastal origin. Cool nutrient rich water in the form of first a filament appears to have advected 550km offshore and apparently transformed into a cyclonic eddy (e.g. suggested by TOPEX data). This feature dominated the area around our mooring for more than a month. Periods of time when this feature encompassed the mooring site indicate that the physics and the biology were different than when the feature shifted northward or southwestward past the mooring site. The mesoscale and bi-annual are scales observed at our site and likely over much of the Arabian Sea dominated during this experiment. The second question asks whether there is coupling between the physics and biology on time scales of days to weeks and on space scales of 10's to 100's of kilometers. A strong correlation between temperature and biomass was seen during October 1994 - January 1995. This was the period studied in detail in Chapter 5 which was dominated by the advection of a mesoscale feature past the mooring site. November 16 - December 15,1994 was a period when a mesoscale feature dominated the variability of the physics and biology in the upper water column. During this period, temperatures decreased 4 degrees and chi a values increased 75% at 35m depth. KPAR (0 - 35) was also observed to increase (by 55%) tracking the increasing chi a values well. A feature with an approximate diameter of 250km, estimated from TOPEX SSH data, advected past the mooring site, over a 20 day period This caused a dramatic effect on the physics and the 110 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. biology of the region. The physical processes and the biological response were apparently very closely coupled during this time period. We observed a storm which passed over the mooring site (October 23) that resulted in an increase in the 1% LL depth by 20 meters and a decrease in the chi a levels by 75% in a time period of one day. This storm had an initial dramatic effect over about a 24 hour period. Temperature decreased slightly, but the euphotic zone deepened and phytoplankton were re-distributed with depth after the passage of this one day-event. Again, observations support the close coupling of the physics and the biology on time scales of days in the Arabian Sea. In Chapter 4 we showed a chi a time series for one year. It shows clear evidence of two blooms where chi a levels increased during the bi-annual ML deepening (ME and SW monsoons). The bloom associated with the NE monsoon is likely related to ML deepening via convection and to a lesser extent wind forcing. Through the deepening process, nutrients are entrained into the upper ML (euphotic zone) providing near optimal conditions for primary production. The bloom associated with the SW monsoon was driven by both advection of coastal waters (rich in nutrients and phytoplankton) and vertical transport of nutrients into the euphotic layer through shoaling of isopycnal surfaces and possibly ML deepening. Thus, time series observations of physics and chi a results show that there was coupling on a bi-annual scale as well. The physics in the Arabian Sea region are quite complex, with mesoscale features at times traveling over large distances and occurring on 1 11 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. many different spatial scales (e.g. 10's of km to 100's of km). These large features were sometimes quasi-stationary, but changed in size and shape. Our mooring site experienced features such as SSH depressions and elevations, and the mooring instrumentation measured different water masses and biology inside and outside of mesoscale features. Edges of mesoscale features often are characterized by a number of different effects such as frontal upwelling and downwelling and internal/inertial wave trapping that further complicate interpretation of the data sets. We have observed coupling between the physics and the biology on time scales of days to bi-annual periods. The Arabian Sea is generally not a light limited region for primary producers. Also the region is quite nutrient rich compared with mid-latitude basins. Coastal upwelling and associated filaments lead to the transport of nutrient rich waters well into the central gyre of the Arabian Sea. In addition, mesoscale dynamics are prevalent and result in open ocean upwelling. Thus, the Arabian Sea is a near optimal open ocean environment for high biological productivity as observed. The bi-annual physical/biological coupling is likely basin wide. Future work with data sets collected during this study will help to answer other questions, and test other hypotheses. 112 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Appendix I Description of MVMS Data Conversions Parameters measured external to the VMCM are conductivity, photosynthetically available radiation (PAR), upwelled solar radiance at 683nm (Lu683), beam attenuation coefficient (beam c), stimulated fluorescence, and dissolved oxygen (DO). Conductivity is measured with a Sea-Bird sensor, and a frequency output is digitized and stored by the microcontroller. Frequency is converted to conductivity using the equation (provided in the Sea-Bird owners manual): Conductivity (af"+ bf+c + dt)/[10(l-9.57(10-8 )p)] (Al.l) where f is frequency, p is pressure, and t is temperature. Factory calibration constants are determined for a, b, c, d, and m. PAR is measured with a Biospherical scalar irradiance sensor (400 - 700nm). The sensor output varies between zero and five volts, but to increase the dynamic range at particular light levels a variable gain amplifier is used before the signal is digitized. The voltage is converted to |iEin m'2 sec'1 using the equation: 113 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. PAR = (Vpar*m + b)*Mconst (A1.2) where Vpar is the output voltage, m and b are the slope and y-intercept of the gain circuit respectively, and Mconst is a manufacturer supplied constant. Lu683 is collected with a Biospherical radiance sensor with similar output and circuitry to the PAR. Equation A1.2 would again be used with V683 substituted for Vpar and different constants to yield radiance at 683 nm with units jiW cm *2 s* 1 str'1 nm*1. Beam c is measured with a Sea Tech transmissometer (Bartz et al., 1978; SeaTech manual). A signal is transmitted at 660 nm across a path length of 25cm. The input minus the output measures total light attenuation due to absorption and scattering. The result from the transmissometer is converted to beam attenuation coefficient (1/m) using the equations: where V is the percent transmission, m is the maximum air voltage, a is the maximum average value just before deployment, t_volt is the V = 20 * (m/a)* (t_volt - z) (A1.3) beam c = [ In (V/100)] / 0.25 (A1.4) 114 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. transmissometer output signal, and z is the offset with the light path blocked. Chlorophyll a is estimated with a Sea Tech fluorometer which makes a measurement termed stimulated fluorescence. A pulsed blue light source is activated while an orthogonal red light receiver collects output signal produced from phytoplankton fluorescence. The output signal is digitized and run through equation A1.5 to yield chlorophyll units of (mg/1). chi a = m * chl_v + b (A1.5) Equation A1.5 is a linear relationship between chlorophyll concentration and output voltage. The constants m and b are determined from laboratory calibrations and in situ comparisons with CTD data. The determination of absolute chi a from stimulated fluorescence is still being investigated. The chi a data presented in this thesis were calibrated at LDEO at is described in Ho et al., (1996). The absolute values are reported here, but are believed to be lower by approximately 50% from SeaSoar data (pers. commun. Jones). 115 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Appendix II Data Processing Description Data from the MVMS are stored every 3.75 minutes. A sample is stored from each sensor every 3.75 minutes except for the orthogonal rotors which record the number of turn counts for the entire sample period. This is stored in a 4 bit hex format as shown in the example below. F0011COOOFOOOFOOOFOOOF808A7D300000001102EE014D000001540F9C000008081153 The format of the hexadecimal line is shown in table A2.1: Sensor: Number of characters: Record Number 5 North Vector 4 East Vector 4 Rotor 2 4 Rotor 1 4 Compass 2 Temperature 4 Check Sum 2 PAR 4 Dissolved Oxygen 4 Temperature from D. Oxygen 4 Beam attenuation coefficient 4 Conductivity 4 Stimulated Fluorescence 4 Battery Voltage 4 Natural Fluorescence 4 116 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Day 2 Hour 2 Minute 2 Second 2 Table A2.1 Description of raw hexadecimal data line. The data line is stored in a temporary buffer (volatile memory) tin til 0.5 megabytes worth of lines are stored, at which point the data are transferred to the hard drive and assigned a file number. Each file begins with a header like the one show below: MVMS ARAB 35M 10/94 FILE= 1 @ 941008081152 LOCAL Each of these files is then run through a rigorous scheme of checks to identify faulty data and conversions to transform valid data to physical units. A block diagram description of this process is shown in figure A2.1. 117 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Input: Raw Hex Data Output is a 11 by 79060 tab delineated Matrix. Plots can m e m ade with any G raphing program like Matlab o r IDL. Fortran File: 35fix4.f 80fix4.f Program d o e s a linear interpolation betw een g ap s found a t th e beginning of m ost 80m files. O U TPU T FILES: 35mc.volt & 80mc.volt Fortran File: gd35.f gd80.f Program u se d to rem ove d ata at the beginning an d ending of the D eploym ent w hen MVMS w as not in th e w ater. OUTPUT FILES: thirph & eighph OUTPUT FILES : 35m .volt & 80m.volt C onverts Julian Day, tem perature, and C urrents from Hex to Volts to Physical Units. Fortran File : hd35m 7.f hd 80m 7.f Program C onverts bio-optical d ata from Hex to Volts Fortran File: 35m 1.f 80m1 .f PAR, Beam C, Stim ulated Fluorescence, Natural Fluorescence and Salinity are converted to Physical units in this program . DO and DO tem p eratu re will eventually be converted from volts to physical untils here. OUTPUT FILES: 35m .phys & 80m .phys Figure A2.1 Block diagram description of data processing procedure 118 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. The third section of figure A2.1 above is a crudal step where all the calibration constants for the bio-optical parameters are applied to convert the recorded voltages to physical parameters. These calibration equations are shown in Appendix I. 119 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. References Bartz, R. R. W. Spinrad, and J. C. Kitchen, A low power, high resolution, in situ fluorometer for profiling and moored applications in water, O c e a n O ptics V , M. Bilizard (ed.), pp. 157-170, Proc. SPIE, 925,1988. Bartz, R. R., J. R. V. Zaneveld, and H. Pak, A transmissometer for profiling and moored observations in water, O cean O ptics V , M. B. White, and R. E. Stevenson (eds.), pp.102-108, Proc. SPIE, 106 ,1978. Bauer S., G. L. Hitchcock, and D. B. Olson, Influence of monsoonally- forced Ekman dynamics upon surface-layer depth and plankton biomass distribution in the Arabian Sea, D eep-Sea R es., 38, 531-553, 1991 Booth, C. R., The design and evaluation of a measurement system for phytosynthetically active scalar irradiance, L im nol. O cea n o g r., 19, 326-335, 1976. Brock, J., S. Sathyendranath, and T. Platt, Modeling the seasonally of subsurface light and primary production in the Arabian Sea, M a r i n e Ecology P rogress, 1992 Desai, S. D., and J. M. Wahr, Emperical ocean tide models estimated from TOPEX/POSEIDON altimetry, J. G eophys. R es., 100, 25,205-25,228,1995. Dickey, T.D., The emergence of concurrent high-resolution physical and bio-optical measurements in the upper ocean and their applications, R e v . G eophys., 29, 383-413, 1991. Dickey, T., Bermuda Testbed Mooring program, Bull. Amer. Meteor. Soc., 76,584,1995 Dickey, T. D., and D. Manov, Moored systems for time series observations of bio-optical and physical variability in the coastal ocean, Coastal Zone '91, In: Proceedings o f the 7 th S y m p o siu m o n C oastal and O cean M a n a g e m e n t , pp. 86-100, ASCE, Long Beach, CA, 1991. Dickey, T. D., and J. J. Simpson, The influence of optical water type on the diurnal response of the upper ocean, T ellu s Ser. B, 35, 142-154, 1983 120 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Dickey, T.D., R.H. Douglass, D. Manov, D. Bogucki, P.C. Walker, and P. PetreUs, An experiment in two-way communication with a multivariable moored system in coastal waters, J. A tm o s O ceanic T e c h n o L , 10, 637-644, 1993b Dickey, T., D. Frye, M. Stramska, H. Jannasch, E. Boyle, D. Manov, D. Sigurdson, A. Michaels, N. Nelson, J. McNeil, and D. Siegel, Preliminary results from the Bermuda Testbed Mooring program, to be submitted to Deep-Sea R es., 1996 Dickey, T. D., T. Granata, J. Marra, C. Langdon, J. Wiggert, Z. Chai-Jochner, M. Hamiltion, J. Vazquez, M. Stramska, R. Bidigare, and D. Siegel, Seasonal variability of bio-optical and physical time series observations in the Sargasso Sea, J. G eophys. Res., 98, 865-898, 1993a. Dickey, T. D., J. Marra, T. Granata, C. Langdon, M. Hamilton, J. Wiggert, D. Siegel, and A. Bratkovich, Concurrent high resolution bio-optical and physical time series observations in the Sargasso Sea during the spring of 1987, f. G eophys. R es., 96, 8643-8663, 1991. Dickey, T., J. Marra, M. Stramska, C. Langdon, T. Granata, R. Weller, A. Plueddemann, and J. Yoder, Bio-optical and physical variability in the sub- Arctic North Atlantic Ocean during the spring of 1989, /. G eophys. R e s., 99, 22,541-22,556,1994. Eriksen, C.C., J. M. Dahlen, and J.T. Shillingford, An upper ocean moored current and density profiler applied to winter conditions near Bermuda, /. Geophys. R es., 87, 7879-7902, 1982. Flagg, C. N. H. S. Kim, and Y . Shi, A c o u s tic D oppler C u r r e n t P r o filin g fr o m the JG O FS A ra b ia n Sea C ruises A b o a rd the R V T. G. T h o m p s o n , Brookhaven National Laboratory, New York, 1995. Hastenrath, S., C lim a te D yn a m ics o f the T ro p ics, Kluwer Academic Publishers, London, 1991. Hastenrath S., The monsoonal regimes of upper-hydrospheric structure in the tropical Indian Ocean, A tm o sp h e re-O c e a n , 27(3), 478-507, 1989 Hastenrath, S., and L. Greischar, The monsoonal current regimes of the tropical Indian Ocean: observed surface flow fields and their geostrophic wind-driven components, }. Geophys. R es., 96, 12,619-12,633, 1991 121 Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. Hastenrath, S., and P. Lamb, C lim a tic A tla s o f the In d ia n O c e a n , vol. 1, Surface C lim a te a n d A tm o s p h e r ic C ir c u la tio n , 116pp., University of Wisconsin Press, Madison, 1979a Hastenrath, S., and P. J. 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Peterson, W.L. Prell, N. Surgi, J.C. Swallow, and K. Wishner. U.S. JGOFS: Arabian Sea Process Study, U.S. JG O FS P la n n in g R eport N o. 13, Woods Hole Oceanographic Institution, Woods Hole, 1991. Stramska, M. and T. Dickey, Variability of bio-optical properties of the upper ocean associated with diel cycles in phytoplankton population, f. G eophys. R es., 97, 17,873-17,887, 1992. Stramska, M., T. D. Dickey, A. Plueddemann, R. Weller, C. Langdon, and J. Marra, Bio-optical variability associated with phytoplankton dynamics in the North Atlantic Ocean during the spring and summer of 1991, f. G eophys. R es., 100, 6621-6632, 1995. Swallow J., Eddies in M a rin e Science, A. R. Robinson, ed., Springer-Verlag, New York, 1983. Swallow, J. G, Some aspects of the physical oceanography of the Indian Ocean, Deep-Sea R es., 31, 639-650, 1984. Tchemia, P., D escrip tive R e g io n a l O c e a n o g r a p h y , Pergamon Press, New York, 1980. Tomczak, M. and J. S. 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Sigurdson, David Eric
(author)
Core Title
Analysis of physical and bio-optical variability in the Arabian Sea during the northeast monsoon of 1994
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Graduate School
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Master of Science
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Ocean Sciences
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University of Southern California
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biogeochemistry,biology, oceanography,OAI-PMH Harvest,physical oceanography
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English
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Sammis, Charles G. (
committee chair
), Dickey, Tommy (
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biogeochemistry
biology, oceanography
physical oceanography