THE TRANSPARENCY OF SELECTED U.S. COASTAL WATERS WITH APPLICATIONS TO LASER BATHYMETRY Maxim F, van Norden and Steven E« Litts h as I hi ^1? iiii-i NAVAL POSTGRADUATE Monterey, California OOL THESIS THE T WATERS RANSPARENCY OF SELECTED U.S. WITH APPLICATIONS TO LASER by Maxim F. van Norden and Steven E. Litts September 1979 COASTAL BATHYMETRY Thesis Advisor: S. P. Tucker Approved for public release; distribution unlimited. T191026 UNCLAgSIFIED SECURITY CLASSIFICATIOM Of THIS PAGt r*»i«»t Dmtm Sn(*r«<0 REPORT DOCUMENTATIOM PAGE I. RCPOMT NUMBCA 2. GOVT ACCCMION NO 4. TITLE r«nrf Su6(/Ma; The Transparency of Selected U.S. Coastal Waters with Applications to Laser Bathy- metry 7. AuTMO»»r«> Maxim F. van Norden and Steven E. Litts READ INSTRUCTIONS BEFORE COMPLETING FORM «eCl>»ttNT*$ CATALOG NUMSEM S. TYI»C OF REPORT ft PERIOD COVERED Master's Thesis; September 19 79 • ■ PCRFORMINC ORG. REPORT NUMSER a. CONTRACT OR GRANT NUMSERrtJ >. PERFORMING ORG-ANIZATION NAME AND AOORCIS Naval Postgraduate School Monterey, California 93940 to. PROGRAM ELEMENT. PROJECT. TASK ARIA * WORK UNIT NUMBERS n. CONTROLLING OFFICE NAME AND ADDRESS Naval Postgraduate School Monterey, California 93940 12. REPORT DATE September 1979 IS. NUMSER OF PAGES 162 pages 14. MONITORING AGENCY NAME • ADORESS<« dUtmrwnt from Contnlllnf Otileu) Naval Postgraduate School Monterey, California 9 3940 IS. SECURITY CLASS, (ol im» ripon) \%m. OCCLASSIFI CATION/ DOWNGRADING SCHEDULE l«. DISTRIBUTION STATEMFMT (oi thi* Hmpart) Approved for public release; distribution unlimited. 17. DlSTRiauTION STATEMENT (of tha aA«(r«et mifrad In Bieek 30, II (UU»r»nt tfom R»port) It. SUPPLEMENTARY NOTES It. KEY WORDS (Cantlnua on tmroram oldo ll nacomoorr and Idrnnllty by block ntamkor) Irradiance data, transparency, coastal waters, coastal zone, laser bathymetry, laser hydrography, Secchi data, light attenuation data, turbidity, beam transmittance data, irradiance attenuation lengths, marine optics, optical oceanography. Pacific Northwest & Gulf Coasts. 20. ASSTRACT (Contlmf an to¥9t»o aids II nmcmtomrr mtd Id^ntlfr kf kloek mtmbor) The operational effectiveness of airborne laser hydrography systems^ considering the optical environment of the coastal waters of Oregon, Washington, and the Gulf Coast states, is examined. The best times of the year are predicted for conducting laser bathymetry considering the temporal and spatial variability of optical proper- ties due to seasonal effects, and charts of seasonally averaged optical measurements are given. Original formulas to convert beam attenuation coefficients and Secchi depth measurements to i-rrad1 ;^nr-P DD ,:°r„ 1473 (Page 1) EDITION OF 1 NOV tt IS OBSOLETE S/N 0I03'014- 6601 I UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (Wtton Dat» Mntorod) UNCLASSIFIED ^eu*wTv CL^ttl^lC^TiOM py Tmi> m^at,fWSm> n>f Kn««»»^- attenuation coeffients are included. The number of irradiance attenuation lengths to the bottom depth (Kd) are used as the indi- cator to estimate areas where laser hydrography systems would be successful and are shown by season and region. The conclusions of this thesis are that airborne laser hydrography is not practical in the coastal waters of Oregon and Washington, would be practical in limited areas of the western Gulf Coast, and would be very practical in the eastern Gulf Coast area. Along the eastern Gulf Coast a 38,800 nmi^ area, delineated by a Kd = 4 contour, is judged survey- able bv laser. I DD Fo^'tljj 1*^"^ UNCLASSIFIED S/N 0102-0X4-6601 2 |,cu«itv cuAMincATiow o^ thi« ^*acrw•« o.»* »»/.'•-• pproved for public release; distribution unlimited. The Transparency of Selected U.S. Coastal Waters with Applications to Laser Bathymetry by Maxim F. van Norden Civil Engineer, U.S. Naval Oceanographic Office B.S., University of Maryland, 1972 and Steven E. Litts Cartographer, Defense Mapping Agency B.S., Pennsylvania State University, 1975 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN OCEANOGRAPHY (HYDROGRAPHY) from the NAVAL POSTGRADUATE SCHOOL September 1979 ABSTRACT The operational effectiveness of airborne laser hydrography systems^ considering the optical environment of the coastal waters of Oregon, Washington, and the Gulf Coast states, is examined. The best times of the year are predicted for conducting laser bathymetry^ considering the temporal and spatial variability of optical properties due to seasonal effects^ and charts of season- ally averaged optical measurements are given. Original formulas to convert beam attenuation coefficients and Secchi depth measure- ments to irradiance attenuation coefficients are included. The number of irradiance attenuation lengths to the bottom depth (Kd) are used as the indicator to estimate areas where laser hydrog- raphy systems would be successful and are shown by season and region. The conclusionsof this thesis are that airborne laser hydrography is not practical in the coastal waters of Oregon and Washington, would be practical in limited areas of the western Gulf Coast, and would be very practical in the eastern Gulf Coast 2 area. Along the eastern Gulf Coast a 33,800 nmi area, delineated by a Kd = 4 contour, is judged surveyable by laser. TABLE OF CONTENTS INTRODUCTION 11 A. HYDROGRAPHY AND THE DEVELOPMENT OF LASER BATHYMETRY 11 B. MAJOR BENEFITS OBTAINABLE FROM LASER BATHYMETRY 12 C. PURPOSE OF THE THESIS 14 ATTENUATION OF LASER BEAM POWER AS THE PARAMETER GOVERNING THE EFFECTIVENESS OF LASER BATHYMETRY 15 A. INTRODUCTION 15 B. OPTICAL CLASSIFICATION OF OCEAN WATERS 15 C. TRANSMISSION WINDOWS AND LASER TYPES 16 D. THE PRINCIPLE OF LASER BATHYMETRY 16 E. THE IMPORTANCE OF THE SYSTEM ATTENUATION COEFFICIENT IN THE LASER SIGNAL EQUATION 17 F. THE IRRADIANCE ATTENUATION COEFFICIENT AS AN APPROXIMATION 18 G. IRRADIANCE ATTENUATION LENGTHS AND PERFORMANCE OF LASER BATHYMETRY SYSTExMS 19 H. NATURE OF THE PROBLEM 20 DATA COLLECTION AND PROCESSING 22 A. LIMITATIONS OF MARINE OPTICAL DATA IN COASTAL WATERS 2 2 B. DATA REDUCTION AND CONVERSION 23 1. Irradiance Attenuation Coefficient (K) Data 23 2. Beam Attenuation Coefficient (C) Data 25 3. Secchi Depth (Z ) Data 27 C. REMOTELY SENSED DATA 33 D. DATA PROCESSING 35 TEMPORAL VARIATION OF OPTICAL PROPERTIES BY REGION 37 A. INTRODUCTION 37 5 B. PACIFIC NORTHWEST COAST 38 C. WESTERN GULF OF MEXICO 41 D. EASTERN GULF OF MEXICO 44 V. CONCLUSIONS AND RECOMMENDATIONS 47 A. CONCLUSIONS 4 7 B . RECOMMENDATIONS 48 APPENDIX A: DATA SOURCES OF IN SITU OPTICAL MEASUREMENTS IN COASTAL WATERS 50 APPENDIX B: COMPUTER PROGRAM 57 LIST OF REFERENCES 153 DISTRIBUTION LIST 159 LIST OF TABLES I. Smranary of linear regressions for spectral beam attenuation data at various depths taken in Monterey Bay, California 61 II. Data used to convert Secchi depth to irradiance attenuation (Z to K ) for eastern Pacific coastal waters 6 2 III. Data used to convert Secchi depth to irradiance atten- uation (Z to K ) for western Gulf coastal waters 6 3 s s IV. Summary of linear regressions to convert Secchi depth to irradiance attenuation (Z to K ) for selected U.S. coastal waters 64 V. Pacific Northwest Coast parameters used to determine optical seasons 6 5 VI. Western Gulf Coast parameters used to determine optical seasons 6 6 VII. Eastern Gulf Coast parameters used to determine optical seasons 6 7 LIST OF FIGURES 1. Laser/sonar cost comparison 68 2. Transmittance per meter of downward irradiance in the surface layer for optical water types 69 3. Spectral irradiance attenuation coefficients of down- ward irradiance in the surface layer for Jerlov's optical water types 70 4. Laser pulse and return signals 71 5. System attenuation coefficients as a function of receiver FOV and aircraft altitude 72 6 . Expected penetration of different laser systems as specified by Kd 73 7. Depth profiles of percentage of surface quanta (350- 700 nm) for different water types 74 8. The ratio of irradiance to quantum irradiance in the spectral range 350-700 nm as a function of depth in different optical water masses 75 9. Linear regressions of K and Z for Eastern Pacific coastal waters 76 10. Linear regressions of K and Z for Western Gulf J. T 1. s s 77 coastal waters- ' ' 11. Linear regressions of K and Z for Poole and Atkins data 78 12. Linear regressions used to convert Z^ to K for selected U.S. coastal waters 79 13. Upwelling index for the U.S. West Coast 80 14-16. Position plots of data 81 17-25. Seasonal Secchi data for the Pacific Northwest Coast — 84 26. C data for the Pacific Northwest Coast 93 27. K data for the Pacific Northwest Coast 94 28-36. Seasonally converted K data for the Pacific Northwest Coast 9 5 37-39. Seasonal Secchi data for the western Gulf Coast 10'^ 40-41. Seasonal C data for the western Gulf Coast ^^'^ 8 42. K data for the western Gulf Coast 109 43-45. Seasonally converted K data for the western Gulf Coast 110 46-53. Seasonal Secchi data for the eastern Gulf Coast 113 54-59. Seasonal C and K data for the eastern Gulf Coast 121 60-66. Seasonally converted K data for the western Gulf Coast 127 67-75. Seasonal Kd data for the Pacific Northwest Coast 134 76-78. Seasonal Kd data for the western Gulf Coast 143 79-85. Seasonal Kd data for the eastern Gulf Coast 146 ACKNOWLEDGEMENTS We would like to express our sincere gratitude to Assistant Professor Stevens P. Tucker, our thesis advisor, for his assistance and patience; Mr. David B. Enabnit for inspiring our thesis and providing funds for satellite imagery; and Lucia van Norden, an understanding wife, for her data key- punching and typing. Many people helped us in our search for data; and we are grateful to: Henry Odum of the National Ocean- ographic Data Center; Louis Hoelman of the Environmental Protection Agency; Gloria Richie of the Texas Natural Resources Information System; Dr. Murray Brown of the Bureau of Land Management; Dr. Hasong Pak and Dr. Lawrence Small of Oregon State University; John Grady of the National Marine Fisheries Service; V. Stewart of the Florida Department of Natural Resources; Gerald Shideler of the U.S. Geological Survey; and Larry Breaker of National Environmental Satellite Service. People who assisted us in the concepts of our thesis include: Andrew Bakun of the National Marine Fisheries Service and John Shannon and Howard Krumboltz of the Naval Air Development Center. 10 I. INTRODUCTION A. HYDROGRAPHY AND THE DEVELOPMENT OF LASER BATHYMETRY Hydrography has been defined as, "that science which deals with the measurement and description of the physical features of the oceans, seas, lakes, rivers, and other waters, and their adjoining coastal areas, with particular reference to their use for navigational purposes" (U.S. Naval Oceanographic Office, 1966) . Hydrographic surveys are used to produce nautical charts and related information which satisfy navigational, engineering and marine scientific needs and contribute to national goals such as ocean resource management and national defense. However, these products may become quickly outdated, and new surveys are required because of changes caused by such natural processes as winds, tides, earthquakes and because of man-made changes result- ing from construction of ports, channels, breakwaters, and pipelines. New surveys might also be needed because of changing requirements, for example those associated with deep draft tankers. Since the 19 30s most hydrographic surveys have been performed by ships equipped with sonic depth sounders to obtain bathymetric data. A new method for hydrographic surveying, airborne laser bathymetry, was shown to be a fast reliable technique to obtain bathymetric data by the U.S. Naval Oceanographic Office (NAVOCEANO) with their Pulsed Light Airborne Depth Sounder (PLADS) in 1969 (Bright, 19 73) . The PLADS system used a frequency-doubled Neodymium Yttrium Aluminum Garnet (Nd:YAG) laser (Rattman and 11 Cunningham/ 1969). NAVOCEANO's interest in such a system resulted from immediate requirements stemming from the Vietnam War for better charts of shallow coastal waters within range of enemy controlled territory (Bright, 1973) . Since that time further work has been done by NAVOCEANO, NASA, National Ocean Survey (NOS) , and the Australian Weapons Research Establishment. In 1974 NAVOCEANO tested a NASA-owned neon laser and in 19 75 obtained a frequency -doubled Nd:YAG laser for their Coastal Aerial Photo-Laser Survey (CAPS) system (Crandall, 1976). In 1977 NASA, with DOD and NOS sponsorship, began testing their Airborne Oceanographic Lidar (AOL) as a hydrographic data acquisition system (Guenther and Enabnit, 1978) . The success of these tests influenced the Naval Oceanographic Research and Development Agency (NORDA) to place their Hydrographic Airborne Laser Sounder (HALS) in the procure- ment stage in 1978 and influenced NOS to implement a development plan for a more sophisticated system in 1979. The Australian Weapons Research Establishment has built two systems, one for research and one for operational surveys (National Ocean Survey, 1979) . B. MAJOR BENEFITS OBTAINABLE FROM LASER BATHYMETRY The National Ocean Survey (1979) has evaluated airborne laser hydrography and has found four major benefits realizable over ship/sonar hydrography with this technique: cost savings, manpower savings, capability of increased production, and im- provement in the quality of marine charts. 12 The NOS (1979) study showed that projected cost savings would be achieved through the speed with which an area could be surveyed. Figure 1 shows the costs per unit area as a function of area surveyed annually. The three curves represent amortized nonrecurring capital cost, operating cost, and total cost. The constant line approximates the cost of launch/sonar hydrography at $2 730 per square nautical mile. The comparison 2 of the projected laser cost per unit area of $438/nmi to the 2 launch/sonar cost per unit area of $2 730/nmi for a fully 2 utilized system, 2000 nmi /yr, indicates that laser surveys would cost one-sixth of sonar surveys. The NOS (19 79) study also examined manpower and production. NOS concluded that manpower effectiveness of laser over launch/ sonar would be five-to-one. Projected production for each NOS 2 airborne laser system would be approximately 2000 nmi per annum. Finally, the NOS (1969) study suggested that the quality of marine charts would be improved by laser systems because of significantly increased spatial density and greater uniformity of distribution of soundings compared to sonar. The proposed NOS laser system was to collect 4 00-600 depth measurements per 2 second with an average distribution of one per 20 m , yielding measurements 4.5 m apart in all directions. This would be 300 times the number of soundings per unit area of typical ship/sonar surveys. The increased density and more uniform distribution would provide a more representative chart. 13 C. PURPOSE OF THE THESIS NAVOCEANO and NASA have shown that laser bathymetry systems may be practical and reliable. NOS has shown that major bene- fits for hydrography may be possible with a laser system. The purpose of this thesis was to determine the most effective use of airborne laser hydrography systems considering the marine environment. Specifically, the questions to be answered are ^ which areas of U.S. coastal waters may be most effectively surveyed using airborne laser bathymetry and at what times of the year? This study was confined to the Gulf and West Coasts because major studies have already been conducted by NOS for the East Coast (Enabnit, 1979) . 14 II. ATTENUATION OF LASER BEAM POWER AS THE PARAMETER GOVERNING THE EFFECTIVENESS OF LASER BATHYMETRY A. INTRODUCTION Laser penetration of ocean water is dependent on the optical properties of sea water. This thesis examines the optical prop- erties which can be used to delineate those ocean areas which might be surveyed advantageously by laser bathymetry. Definitions and terms used to describe optical properties of sea water are those recommended by the Committee on Radiant Energy in the Sea and given by Jerlov (19 76) . B. OPTICAL CLASSIFICATION OF OCEAN WATERS Jerlov (1976) has classified ocean waters in terms of the spectral transmittance of downward irradiance at high solar altitudes (Fig. 2) . The Jerlov coastal water types 1-9 are characterized by increasingly higher amounts of yellow substance. Water types of decreasing irradiance transmittance indicate a spectral shift in the transmittance maximum toward longer wave- lengths. Selective absorption by particles and yellow substance causes greater absorption at the shorter wavelengths and shifts the transmittance maximum from 4 70 nm, the blue region, for clear ocean type I water to 550 nm, the green region, for coastal type 7 water. Figure 3 is a similar graph of Jerlov' s water types but gives instead of transmittance the irradiance attenuation coefficient (K) for downwelling daylight as a function of wavelength. 15 C. TRANSMISSION WINDOWS AND LASER TYPES The preference for a particular type of laser to be used for laser bathymetry depends upon the wavelength of maximum transmission. The transmission window for Jerlov's coastal water types 1-7 is approximately 510-580 nm (Figs. 2 and 3) . Laser types that have operating wavelengths within that spectral band are: the frequency-doubled Nd:YAG laser (used in the proposed NORDA HALS and NOS systems) , which operates at 5 32 nm; the neon laser (used in NASA's AOL) , which operates at 540 nm; the argon laser, which operates at 514 nm; and the dye laser, which is tunable over the blue-green spectrum (Ferguson, 1975). The frequency-doubled Nd:YAG is preferred by NORDA and NOS for two primary reasons: (1) its high peak pulse power and high pulse rates, and (2) its small size and weight (NORDA, 1978) . D. THE PRINCIPLE OF LASER BATHYMETRY The technique of using a pulsed laser to measure water depths remotely can be explained with the aid of Figure 4. A short pulse of light is emitted from an airborne laser. The pulse of energy travels at the velocity of light and impinges upon the surface of the water. Approximately 3% of this energy is specularly reflected from the air/water interface and inter- cepted by the aircraft receiver. Half of the time difference between the initial laser pulse and this surface reflection yields the aircraft altitude. The remaining 97% of the laser 'energy is transmitted into the water, wherein its velocity is decreased by about 25%. (The transmission across the air/water interface is dependent on the angle of incidence, on polariza- tion, and on sea state conditions. The value of 97% is an 16 average value for angles of incidence between 0 and 4 5 in calm seas [Witt, 1979]./ In addition the signal is exponentially attenuated by absorption and scattering within the water column. If the signal is of sufficient intensity, it will be reflected from the water/sediment interface and be detected at the receiver. The time difference between the surface and bottom-sediment reflections is used to determine the water depth. E. THE IMPORTANCE OF THE SYSTEM ATTENUATION COEFFICIENT IN THE LASER SIGNAL EQUATION A signal equation for a laser pulse transmitted from an airborne platform to the ocean floor may be given as follows (Avco Everett Research Laboratory, Inc., 1975): ^^B Pt R(l-P)^ 1 ^ VsB Tr(h4)2 n^ P _ = Received peak power [W] rB P = Transmitted peak power [W] R = Bottom reflectivity p = Surface reflectivity a, = Atmospheric attenuation [km ] y = System attenuation coefficient of sea water [m ] A = Area of collector [m^] c T _, = System efficiency h = Aircraft altitude [km] d = Water depth [m] n = Index of refraction of sea water 17 This equation shows that the received signal is a function of environmental and system parameters. However, for a given appro- priately designed and operated laser system, the major operational limitation is due to the environmental parameters. A simplified signal equation that indicates this is: P^3 = SR (l-p)e-2^1^ e-2Td where S = (P^A^Xgg) / [tt (h+d/n) ^ n^] For an aircraft altitude of 609 m (2000 ft) , a water depth of 10 m, and representative values for the system and environ- mental parameters P = 30 kW, R = 15%, p = 2%, a, = 0.12/km, 2 Y = 0.2/m, A = 0.073 m , x „ = 1.27%, and n =1.33 (Avco Everett C SiD Research Laboratory, Inc., 1975) the following values are obtained: S = 1.32 X 10~^W, R = 0.15, 1-p = 0.98, e'^^^l^ = 0.86, e'^Y^ = 0.02, P^g = 3.33 x 10"^W. The system parameter, S, is fixed for a given system or survey operation. Therefore, the ultimate environmental parameter is the product of the system attenuation coefficient and water depth (yd) since it dominates all other terms. F. THE IRRADIANCE ATTENUTATION COEFFICIENT AS AN APPROXIMATION Witt (1979) showed that the system attenuation co- efficient (y) may best be approximated by the irradiance attenua- tion coefficient (K) , for downwelling light, an apparent optical oceanographic property readily measured in situ. This approxima- tion was further confirmed by Krumboltz (1979) in a series of 18 tests for NORDA's HALS system. The coefficient K best approxi- mates Y because after traversing several attenuation lengths, the photons of a laser beam undergo multiple scattering, i spreading the shape of the beam and ultimately giving it an asymptotic radiance distribution equivalent in shape to the irradiance distribution of downwelling daylight. Witt (1979) and Krumboltz (1979) have shown that receiver field of view (FOV) and altitude affect the accuracy I of this approximation. Figure 5 shows the variation of y ^s ! a function of FOV and receiver altitude at one test site. At a receiver altitude of 500 ft, y ~ K with a FOV of 80 mrad^ but at 150 0 ft, Y ~ K with a FOV of 4 0 mrad. The better approxi- mation at higher receiver altitudes is due to the greater laser divergence with distance. The NASA AOL system had a FOV of 5-20 mrad (Avco Everett Research Laboratory, Inc., 1975), the NORDA HALS system a FOV of 0-30 mrad (Naval Oceanographic Research and Development Agency, 19 78) , and the proposed NOS system a FOV of 0-50 mrad (Avco Everett Research Laboratory, Inc., 1978). Figure 5 indicates that for the NASA AOL, the NORDA HALS, and the projected NOS systems the approximation is good for airborne laser bathymetry systems operating at 500 ft or higher but should be used with discretion at lower altitudes . G. IRRADIANCE ATTENUATION LENGTHS AND PERFORMANCE OF LASER BATHYMETRY SYSTEMS The performance of laser bathymetry systems may be specified using irradiance attenuation lengths, L, which are the reciprocals of irradiance attenuation coefficients, i.e., L = 1/K, the 19 distance in which the irradiance decreases by a factor 1/e. The number of irradiance attenuation lengths to the bottom depth (d/L = Kd) that various laser bathymetry systems can attain or are projected to attain is shown in Fig. 6. The NASA AOL system has achieved two attenuation lengths in the daytime and three at night (Enabnit, 19 79) , the NORDA HALS system was contracted to achieve 3.2 (Houck, 1979) , and the proposed NOS system has a goal of four attenuation lengths (Enabnit/ 1979) . A higher value can be attained at night due to the lack of background noise caused by sunlight. It must be noted that in most studies of laser bathymetry, beam attenua- tion lengths have been used in describing the capability of laser systems, even though Krumboltz (1979) has shown that the system attenuation coefficient was better approximated by the irradiance attenuation coefficient. (The problem resulting from the use of beam attenuation lengths is apparent from Figure 5.) Thus some investigators have reported attenuation lengths five times greater than those given here (Guenther and Enabnit, 1978) . H . NATURE OF THE PROBLEM The first thesis objective was to determine where in U.S. coastal waters laser bathymetry can be effective, using the irradiance attenuation length as the best indicator of the expected performance of airborne laser bathymetry systems. The second objective was to predict the best times of the year for using laser bathymetry. The optical properties of coastal waters may -have temporal and spatial variability due 20 to seasonal changes in currents, winds, runoff, upwelling and other physical processes, as well as to biological activity. Other effects of shorter duration and more limited extent are storms, plankton blooms, tides, and man-made pollutants. Only the temporal and spatial variability due to seasonal effects were investigated. These are summarized by figures of seasonally plotted optical data. 21 III. DATA COLLECTION AND PROCESSING A. LIMITATIONS OF MARINE OPTICAL DATA IN COASTAL WATERS One of the major tasks in this study was the collection of marine optical data. Optical data for coastal waters are scarce; this is especially true for irradiance attenuation data. The most common type of optical measurement, the Secchi depth (Z ) / is usually obtained by marine biologists studying the euphotic zone. The next most common type of optical measure- ment for the Gulf Coast area is beam attenuation. Irradiance attenuation measurements, the optical data actually sought, are almost nonexistent for U.S. coastal waters. This scarcity of irradiance attenuation data required the use of Secchi depths and beam attenuation data. Other marine optical measurements such as volume scattering and turbidity measurements such as those recorded in Jackson or Formazin turbidity units were not considered. The in situ data sources used are listed in Appendix A. A limiting condition on all optical data used was that the water depth at the ocean station where the optical measurements were made had to be less than 200 meters. Since laser bathymetry systems will probably be limited to approxi- mately four irradiance attenuation lengths (Enabnit, 19 79) , (80 m depth for a K of 0.05 m ) , 200 meters was considered more than sufficient. Satellite data may be indicative of the optical quality of coastal waters. Therefore, selected Landsat and NOAA-3 satellite imagery were qualitatively examined for turbidity patterns that correlated with in situ beam attenuation data. 22 Another necessary task was to find conversion formulas to convert Secchi depths (Z ) and beam attenuation coefficients (C) j to irradiance attenuation coefficients (K) , because irradiance I attenuation length was the chosen operational parameter. A related problem arose due to the spectral dependency of optical I ■ measurements. The optical data would be most useful if it were I obtained for a wavelength of approximately 5 32 nm (wave- length of the frequency doubled Nd:YAG laser) , but such data are scarce. This scarcity required the use of optical data measured with broad bandwidths or at wavelengths other than 532 nm and the formulation of the necessary conversion relations The third major task was the establishment of a data base with common optical and measurement parameters. Data from sites within a certain ocean region and collected during the same optical season were averaged. B. DATA REDUCTION AND CONVERSION 1. Irradiance Attenuation Coefficient (K) Data The irradiance attenuation coefficient, K(A), is an apparent, spectrally dependent optical property that measures the extent to which diffuse downwelling daylight diminishes exponentially with depth in water. Thus, H =He-K(^)Z z o where: K = solar irradiance at sea surfaces o H = downwelling irradiance at depth Z Z = depth of measurement K(X) = irradiance attenuation coefficient* * Normally (X) will not be written, as it will generally be assumed that K is for a specific wavelength. Depth averaged values of irradiance attenuation co- efficients (K) were required. Data were usually obtained in percent transmissions ( %T = 100 H /H ) for a series of depths. To obtain a depth- averaged value, K, for the entire water column the following equation was used in a linear regression using the method of least squares: In(T^) = ln(H^/H^)„ = -KZ„ n = index of data pairs K in units of m was the slope of the straight-line model with depths, z , in meters as the independent variable and the corre- sponding transmissions, T , as the dependent variable. Ideally, irradiance attenuation data used for this study should have been measured at X = 532 nm. However, few such data were found and irradiance data at other wavelengths had to be used. Most of these data were taken with irradiance meters having a photopic response with a peak transmission near 555 nm. The broad bandwidth of a photopic response coupled with the water's selective absorption by wavelength with increasing depth yields an effective response which is shifted towards the wavelength of maximum transmission for the given water. For this reason photopic K measurements were considered useful. Other K measurements used in this study were obtained with a quantum irradiance meter. A quantum meter is normally sensitive in the 350-700 nm bandwidth interval and has a spectral energy sensitivity directly proportional to wavelength (Jerlov, 1976) . To convert from quantum values, K q, to K the curves of Figs. 7 and 8 (Jerlov, 1976) were used. Given quantum transmission 24 measurements at a station. Fig. 7 was used to determine a water type. Figure 8 was then used to determine the K/K ratio. This ratio was then multiplied by the depth-averaged quantum irradiance attenuation coefficient (K-^) to obtain the irradiance attenuation coefficient (K) . Again the broad bandwidth of the quantum meter becomes narrowed to a green band with depth in 1 coastal waters. j 2 . Beam Attenuation Coefficient (C) Data The beam attenuation coefficient, C(X) , is an inherent, spectrally dependent, optical property that characterizes the attenuation due to absorption and scattering by a collimated beam of monochromatic light traversing a fixed path— length of homogeneous water. Thus, t o where: F = initial radiant power from projector F. = residual radiant power measured by receiver r = path length of measurement C{X) = beam attenuation coefficient* Depth averaged values of beam attenuation coefficients (C) were computed for this study. Data were usually expressed in percent transmission per meter, %T = 100 F /F , for a series of depths. To obtain a depth-averaged C for a water column, numerical integration of the transmittance profile with depth was performed. First, the water column at each observation station was divided into layers so that each beam attenuation measurement was at the center of that layer. Two exceptions to * Normally (X) will not be written as it will generally be assumed that C is for a specific wavelength. 25 this procedure were the surface and bottom layers, because layer boundaries between measurements were kept equidistant. Second, each layer was assumed to contain homogeneous water, and the beam attenuation coefficient was calculated for each layer using the equation: C^ =-ln(F^/F^) [m"^] Third, the transmittance of the entire water column was calcu- lated using an iterative procedure: T = T 1 exp {-C^ r^) n n-i n n where C = coefficient for the layer (m ) in question r = width of the layer (m) in question T _, = incoming transmission to the layer in question and outgoing transmission of the previous layer. T = outgoing transmission of the layer in question and incoming transmission to the next layer. T = 100% o n = number of layers Fourth, the depth averaged C was calculated by using the equation: C = -1/r^ In (T/lOO) where C = depth averaged beam attenuation coefficient (m ) r„ = water depth at the station (m) T = final T of previous equation Not all the beam attenuation data used for this study were measured at y - 5 32 nm. Beam attenuation data obtained for Oregon coastal waters (Pak, 1979) were measured at 660 nm and 26 had to be converted. A procedure to convert this data to 532 nm was formulated using data collected by Zaneveld, et al . (1978) in Monterey Bay, California. They used a spectral beam trans- missometer that simultaneously measured at six wavelengths at various depths. From these beam attenuation data those for 45 stations at three wavelengths (500, 550, and 650 nm) measured at six different depths (0-1, 5, 10, 20, 40, and 60 meters) were selected for this study. Linear regression models were computed (x, y: y = mx + b) for the following sets of variables: [C(650), C(500)], [C(500), C(650)], [C(650), C(550)], and [C(550), C(650)] at each depth. Table I summarizes the procedure followed in computing a mean slope (m) and a mean y- intercept (b) to obtain the two equations: C(500) = 1.12 C(650) - 0.42 C(550) = 1.09 C(650) - 0.35 The final equation, obtained by interpolating between the above two equations, was used to convert C(660) to C(532). C(532) = 1.10C(650) - 0.37 where C(650) : 0.425 <_ C(650) <_ 2.00 [m"""-] Beam attenuation coefficients were converted to irradiance attenuation coefficients using a relation computed by Shannon (1975) for C(532) . K = 0.2C + 0.04 [m"-""] where C: 0.11<_C<_1.6 [m~ ] 3. Secchi Depth (Z ) Data Most of the optical oceanographic measurements used were Secchi depths. This is the depth at which a white Secchi disc, usually 30 cm in diameter, lowered into the sea and viewed from 27 'directly above, disappears from view. Unfortunately, the proce- dure has never really been standardized (Tyler, 1968; Williams, 1968; Holmes, 1970) . Factors affecting the visibility of a Secchi disc include solar altitude, cloud cover, sea surface reflection and refraction, ship shadow, water color, observer's I visual acuity, and height above the water surface (Tyler, 1968) . Thus, Secchi disc measurements are somewhat subjective and imprecise. As are the beam and irradiance attenuation measurements, the Secchi disc measurement is spectrally dependent. For the purpose of this study, the observers should have worn eye glasses with, for example, Wratten 61 filters (Williams, 196 8). Again, such spectrally homogeneous data are not available. Williams (1968) investigated the relative response of the photopic eye (555 nm peak response) with and without a Wratten #61 filter (dominant wavelength 530 nm) . Because of the selective absorption with depth of ocean water, the errors generated in using the photopic Secchi measurements were not thought to be of significance for this study. Secchi depth measurements were converted to irradiance attenuation coefficients by methods based on geographic region. Formulas published by Poole and Atkins (19 29) , Graham (1966) , Otto (1966) , and Holmes (1970) were not considered ade- quate for this study because of poor statistical procedures or because the data were obtained in a different type of water. Instead, data from various sources were used to develop regional formulas to convert Z to K. s 28 The conversion formula used for Eastern Pacific coastal waters was based on photopic irradiance and Secchi depth data published by Callaway and McGary (1959) and Holmes (1970) . The data selected from Callaway and McGary were from 19 stations approximately 150 nautical miles off the U.S. coast and north of 35°N latitude (Table II) . Added to these were 13 stations in Goleta Bay near Santa Barbara, California, observed by Holmes. These 32 stations were used and processed in the following manner. First, the Callaway and McGary irradiance attenuation data were transformed to a depth- aver aged value for the same water layer as the Secchi depth measurement. This value (K ) was computed by using only those irradiance transmission values which were measured or interpolated at depths equal to or shallower than the Secchi depth. The procedure used to calcu- late K from these transmission values was the same linear s regression technique mentioned in Section III.B.l. The Holmes irradiance data were already in the correct form. Second, two linear regression models were used to compute conversion formulas. The first linear regression model used the Secchi depth reciprocal (Z ) as the independent variable and K as the dependent variable. The equation obtained was: K = 1.21 Z "-^ + 0.06 [m~-^] s s ■• ■" 95% confidence interval m = 1.21 + 0.10 b = 0.06 + 0.02 r = .98 29 In the second linear regression model Z was interchanged with K . The equation obtained was: Z """■ = 0.78 K -0.04 [ra"-"-] s s "• -■ 95% confidence interval m = 0.78 + 0.07 b = -0.04 + 0.02 r = .98 The final conversion formula used is the mean of the above two equations : K = 1.25Z "■•■ + 0.05 [m"-"-] s s ■■ -■ where Z : 1.9 < Z < 32 [ml 5 — s — ■■ -■ Figure 9 is a graph of the data points and the regression lines. The conversion formula used for the western Gulf Coast waters (Longitude >_ 89.5 W) was based on data published by Kamykowski, et al . (1978), quantum irradiance and Secchi depth data for one station off Texas observed on four different cruises. Eleven of the twelve published measurements were used. First, the data were transformed from quantum irradiance transmission to depth-averaged quantum irradiance attentuation coefficients for the same layer of water as the Secchi depth measurements. Second, these coefficients were converted from the Kq to K by using Figs. 7 and 8 from Jerlov (19 76) . Table III summarizes the results. Third, linear regression models were computed resulting in the following equations: K^ = 1.14Z^~''" + 0.04 [m"-"-] 9 5% confidence interval m = 1.14 + 0.39 30 b = 0.04 + 0.05 r = .91 Z''^ = 0.73K - 0.01 [m"-'-] s s "■ -• 95% confidence interval m = 0.73 + 0.25 b = -0.01 + 0.05 r = .91 The final conversion formula used is the mean of the above two equations : K = 1.26 Z "■'■ + 0.03 [m"-'-] s s "■ -■ where Z : 3.5 < Z < 26 [m] Figure 10 is a graph of the data points and the regression lines. The conversion formula used for the Eastern Gulf coastal waters (Longitude < 89.5^W) was computed by Shannon (Witt, et al . , 1976) from optical measurements taken in the West Pacific and Eastern U.S. coastal waters. K = 1.15 Z "■'■ + 0.03 [m"-"-] s s *• ■" r = .95 where Z : 4 < Z < 43 [m] The K data used were measured with two types of irradiance meters--photopic response or a peak response at 533.5 nm (Witt/ 1S79>-. This formula was determined by a linear re- gression model with Z the independent variable and K the dependent variable (Shannon, 1979) . The weakness of this equation was that Z as the independent variable was assumed to be error free. 31 The Poole and Atkins (1929) data were examined due to the wide use of their formula, K = 1.7 Zg"^ [m"^] Poole and Atkins used an irradiance meter with a photopic response and made fourteen series of observations mostly at one station in the English Channel over the course of one year. An average K was calculated for the surface water layer (0-20 m) for each series, and this was multiplied by Z , giving the product Kq_2q Z . Poole and Atkins then found the mean value of the fourteen K^ ^^ Z 0-20 s products to be 1.7. The same Poole and Atkins data were used to recalculate a formula using linear regression and to verify the conversions of this thesis. The two computed linear regression equations are: Kq_2o = 1.11 Zg""^ "^ ^'^^ f"^""^^ 95% confidence interval m = 1.11 + 0.35 b = 0.04 + 0.03 r = .90 2s"^ = 0-^2 Kq_2o -0.01 [m-^] 95% confidence interval m = 0.75 + 0.22 b = -0.01 + 0.03 r = .90 The mean equation from the above two is: Kq_2o = 1-25 Zg"^ + 0.03 [m"-^] where Z : 6.5 < Z < 22 [ml s — s — ■■ -" Figure 11 is a graph of the data points and the regression lines. 32 The close agreement between these equations verified the conversion formulas used to estimate the irradiance attenuation coefficient from the Secchi depth. Table IV summarizes the regression equations, and Fig. 12 shows the final conversion formulas. C. REMOTELY SENSED DATA Three types of satellites are able to provide data that indicate the optical quality of ocean waters: Landsat series, NOAA series and Nimbus 7. Selected imagery from Landaat and NOAA series were examined. Landsat data have been used with some success by numerous investigators studying currents tagged by suspended sediments, plumes, and dispersal patterns of suspended sediments (Jarman, 1973; Pirie and Steller, 1973; Hunter, 1973; Erb, 1974; Carlson, et al . , 1975; Maul and Gordon, 1975; Rouse and Coleman, 1976). The most successful studies have used image enhancement processes with in situ data simultaneously collected for calibration purposes. However, such enhancement was not available for this study, and only B&W imagery as received from the EROS data center of the U.S. Geological Survey were used. For the coastal region off Oregon MSS4 and MSS5 Landsat imagery taken during the March 11, March 28, May 12, and May 13, 1975, overpasses were compared to beam attenuation data (X = 660 nm) collected on April 23-May 1, 1975 by Pak and Zaneveld (1977). No noticeable correlations were observed. For the region off Texas MSS5 Landsat imagery taken during the November 12-13, 1975, and May 28-29, 1976, overpasses were 33 compared to beam attenuation data (X = 528 nm) published by Berryhill/ et al . (1976) and collected on November 15-21, 1975 and May 21-25, 19 76, respectively. Turbidity patterns were I much more noticeable for the Texas imagery and some trends between the satellite imagery and the beam attenuation data ,were observed. These turbidity patterns observed in the andsat imagery were used as an aid in contouring the Texas beam attenuation coefficient data. Shideler (1979) extensively examined the data of all six cruises published in Berryhill , et al. (1976) and Berryhill, et al.(1978) with the related B&W Landsat imagery and indicated that turbid water masses through- out the inner shelf depths (less than 45 m) were apparent in the imagery. The NOAA-3 imagery for selected days throughout 19 75 were used to observe upwelling off the U.S. West Coast. The relation- ship of upwelling to seasonal variation of optical properties off the Northwest Coast is discussed in the next chapter. Coastal ^one Color Scanner (CZCS) data from the Nimbus 7 satellite were not available at the time of the writing of this thesis. However, it is mentioned here because of its enormous potential as an optical data source for the marine environment. Data can be obtained on magnetic tape, CRCST (Calibrated Radiance, Pigment, Diffuse Attenuation Coefficient, and Tempera- ture Tape) , or film format. The irradiance (diffuse) attenuation coefficient is a computer parameter obtained on tape or film image. Since this scanner views a swath 1566 km wide, K data for enormous ocean areas could be obtained (Goddard Space Flight Center, 1978) . 34 D. DATA PROCESSING Each measurement datum was keypunched onto a standard 80- character computer card along with its latitude, longitude, date, bottom depth (when available), measurement unit (meters, feet, etc.)/ converted K value, and the source for the data. The latitude and longitude were given to a tenth of a minute. The data on magnetic tape from NODC, EPA and Texas Natural Resources, required special processing due to limitations on processing resources and the wealth of data measurements recorded over relatively small areas. The NODC tape data was punched one card per measurement. The EPA "Storet" tape gave monthly data covering a span of three years. These data were averaged according to monthly means per station. The Texas Natural Resources tape was averaged by predetermined optical seasons (detailed in Chapter IV. C) per station. These data cards were then used as input for the plotting program. A copy of this program is included in Appendix B. The data points were plotted on a Mercator projection at the same scale as available charts of the area. The plots were then overlayed onto the charts to trace the coastlines and bathymetric contours. Because of the irregular spacing of the data, a spatial averaging routine was used for areas where a dense spacing of points would have caused values to overprint one another. This was accomplished by a straight averaging of all points which were spaced within one plotted number width of one another. Contours were developed for plots by using the smallest plottable number, which was .04 inches for the NPS Versatec Plotter. These contours were 35 then transferred using a light table to a same scale plot which used a number size of .10 inches, the minimum reproducible size for thesis presentation. Therefore, the data contours represent an averaging of values plotted within 1.9 miles of one another on the West Coast, and within 3.4 miles on the Gulf Coast. However, data values on the final plots represent an averaging I ' of values plotted within 4.7 miles of one another on the West Coast and within 8.5 miles on the Gulf Coast plots. No averaging was performed for individual data points positioned beyond j these limits. Figures 14 through 16 show the locations of all the data points used in the plots. For some months data were so sparse that meaningful plots could be obtained only by dividing the year into seasons. The determination of these seasons is the topic of the next chapter. 36 IV. TEMPORAL VARIATION OF OPTICAL PROPERTIES BY REGION A. INTRODUCTION The months of lead time required for laser bathymetric mission planning make it important to determine which times of the year provide optimum water clarity. The sparcity of data for certain months leads to a grouping of months into seasons. Seasonal trends were estimated by comparing the month-to- month variations of oceanographic factors known to affect turbidity with the optical measurements of those few stations which provided monthly optical data. Oceanographic parameters which correlated best with the optical measurements were used to delimit the seasonal boundaries during those months with in- sufficient data. Secular variations were not studied due to the lack of repetitive optical measurements at the same location over a number of years. Coastal water turbidity can be influenced by physical, chemical, and biological processes occurring both in the water column and in adjacent land areas. A major contributor to turbidity is particulate matter produced by land runoff and plankton, especially in areas of upwelling. Phytoplankton blooms can produce sudden increases in turbidity, which may be closely related to upwelling which in turn may be seasonal. Sea surface temperature measurements can be useful in identify- ing areas of upwelling, and salinity measurements have been used to trace the outflow from large rivers such as the Columbia 37 River (Pruter and Alverson 1972) . York in (1974) demonstrated an inverse relationship between Secchi depths and Bakun's (1975) upwelling index. This upwelling index was helpful in determining optical seasons for the west coast of the U.S. Other factors such as large storms may increase turbidity over shorter time frames . Data for the northwest coastal waters of the U.S. were assembled for the region from 42 N to 49 N out to a depth of 200 m. The California coast was not covered due to the narrowness of the Continental Shelf there.* Data from the Gulf of Mexico were divided into two groups, one for the area west of 89 30 'W and the other to the east of that line. The Western Gulf region comprised that area along the coasts of Texas and Louisiana out to a depth of 200 m. The pastern Gulf region started at 24 N, 80°W and included the southern and western coasts of Florida and the coasts of Alabama and Mississippi out to a depth of 200 m. B. NORTHWEST COAST Discharge from the Columbia and other rivers and seasonal upwelling along the coast dominate the turbidity observed along the northwest coast of the U.S. Upwelling affects most of the coast during the summer and the river discharges produce turbidity plumes which affect the coastal areas near river mouths. Brown (1973) correlated Secchi depths for the northwest coast with other simultaneously measured oceanographic parameters and found *For the California coast there are a number of optical obser- vations to which the reader can refer. References to California data which have either beam attenuation or diffuse attenuation measurements may be found in reports by the Allan Hancock Foundation (1963); Drake (1972); Frederick (1970); Karl (1976); and Winzler and Kelly (1977) . 38 coefficients of .610 correlation with water depth, -.598 with observed Forel-Ule color codes, -.591 with Si04 and .504 with salinity. Other parameters such as surface temperature, density, and oxygen levels did not show as good correlations . Bakun (1975) has attempted to quantify upwelling through the use of an upwelling index which is an estimate of the com- ponent of computed Ekman transport directed of:fehore. This transport is calculated from daily mean surface atmospheric pressure data. Figure 13 (Bakun, 1975) shows the upwelling indices computed by month versus latitude for the western coast of the U.S. Shaded areas represent upwelling in units of cubic meters per second per 100 m of coastline. Negative values indicate downwelling. The figure was compiled from an average of 20 years of wind observations. Upwelling occurs as a result of change in wind patterns from southwesterly in winter to northerly in summer. Although the upwelling is not constant but varies with wind variations, this same annual cycle of summer upwelling has been observed over the course of many years . The Columbia River is the only major river source of turbidity along the Northwest coast. It ranks second among U.S. rivers in volume of discharge at its mouth with an average 3 of 640,000 cubic feet per second (or approximately 7,300 m /sec) (Boone 1978) . Peak discharges occur from May to July with lowest flows from August to October. Surface currents along this coast flow southerly from May through September, and northerly from mid-November through February (U.S. Navy Hydrographic Office 196 7) . This movement pushes the plume of the Columbia 39 'River to the south during the months of peak discharge. Most of the remaining streams of the Northwest coastline originate in the Coast Range and produce highest stream flows in February through March and lowest flows from August to September (Geraghty 1973) . The preceding oceanographic factors along with K data from the area (Small, 1979) are summarized in Table V. The table shows upwelling from May to September, also the period of peak discharge of the Columbia River. Upwelling and river discharge act together to assure higher K values at this time. A season of relatively lower K was established from October to January when oceanic and coastal waters meet near shore and little or no upwelling occurs. February through April shows variability with upwelling occasionally establishing itself for short periods. Seasonal plots, figures 17 through 36, were generated using this division scheme. Figures 17 through 25 show Secchi values obtained for this area. Of particular interest is the delineation of the Columbia River plume. Figure 21 shows the 5 m contour being extended south across the 46 parallel towards deeper waters. Figure 22 shows the same contour bulge as much smaller and directed northerly with the current at that time of year. Figure 20 shows the 5 m contour bulging straight out from the river mouth during the time of year when the surface currents are weak and variable in direction. Figure 26 shows all the beam attenuation measurements obtained for the Northwest coast for all seasons. Figure 27 shows all the irradiance measurements obtained for all seasons. 40 Figures 28 through 36 show all measurements after their conversion to irradiance K according to the methods detailed in Chapter 3. Due to the abundance of Secchi measurements as opposed to any other type, these plots mainly reflect the trends indicated in the raw Secchi plots. C. WESTERN GULF OF MEXICO Winter storms and their associated winds and resulting high seas appear to be the most efficient mechanism in generating turbidity in the Western Gulf. Besides being able to resuspend bottom sediment, these storms apparently cause efficient tidal flushing of local estuaries and lagoons as suggested by Shideler (1979) . These lagoons are laden with sediments from local rivers. However, peak discharges of turbid water from these lagoons is not related to high stream flows. Instead, the majority of sediment is trapped by the lagoons until storm conditions can aid high tides in dis- charging it. The discharges of the Mississippi and Atchaflaya Rivers dominate the turbidity regime along the Louisiana Coast. Peak discharges for both rivers are from March to May, with lowest stream flows from September to November (Perret, et al 1971) . These flows dominate the nearshore coast of Louisiana with diminishing effect towards the outer continental shelf. Other stream flows show peak discharges from January to May and lowest stream flows from August to October. Coastal currents are generally weak (less than 1 m/sec over 95% of the time) but do play a role in directing turbidity 41 flows. From October to June the longshore currents are from the east and flow west, then south, along the Texas Coast (U.S. Naval Oceanographic Office, 1972) . This causes the Atchaflaya and most of the Mississippi water to follow the Louisiana coast and keep turbidities high in this area. These currents also direct discharges from Texas lagoons to follow nearshore shallow waters. From July to September a longshore current from the south invades the southern Texas coast until it meets the previously described current at about 29 latitude. In- cursions of the Loop Current of the Gulf of Mexico onto the Continental shelf have been observed (Shideler, 1979) . This shoreward incursion of deep water confines turbid coastal waters to the shallow inner shelf and results in lower turbidities elsewhere . Upwelling, which plays an important role in turbidity levels for the Northwest coast, is not thought to be important for the Western Gulf. Winds from the south to southwest (for Texas coast) and from the west (for the Louisiana coast) which would be needed to produce an offshore Ekman transport are infrequent and generally weak. Berryhill, et al . (1976) report finding a prevalent two-layer turbidity structure in their study of the South Texas outer continental shelf. This structure consisted of a nepheloid layer below a less turbid layer. This nepheloid layer varied in both thickness and distribution but in general became thickest toward the outer shelf. This type of structure casts doubt on the validity of the use of Secchi measurements to obtain K for the entire water column because they only indicate transparency near the surface. 42 Table VI illustrates the variables used in determining optical seasons. Wind data were obtained from a Summary of Synoptic Meteorological Observations (U.S. Naval Weather Service Command, 1970) . Sea heights were obtained from a U.S. Naval Oceanographic Atlas (1972). Zooplankton counts were obtained from a study done by the Louisiana Wild Life and Fisheries Commission (Perret, 1971) . Secchi transects were from a study of the South Texas outer continental shelf (Kamykowski, 1979) . A season from November to February was chosen to represent that time of year when storms are most prevalent and an efficient tidal flushing of lagoons is thought to occur. There is a varia- ble season from March to May when winds are occasionally strong and outflows from the larger streams are high. June to October is the third season, when winds and streamflow are lowest. This third season is thought to consistently provide the best overall water visibility. Hurricanes which occur during this season could raise turbidities substantially, but are infrequent and usually short term in their effects. Figures 37 through 39 show Secchi measurements made in the VJestern Gulf. Within the lagoons of Texas and the nearshore area of Louisiana, visibility is most related to streamflow and therefore March to May is generally the period of shallowest Secchi depths and when streamflows are highest. June to October is generally that period when the deepest Secchi depths were found, but a sparcity of data during these months makes compari- sons difficult. November through February generally are the months when highest turbidities are encountered in the offshore deeper waters. 43 Figures 4 0 and 41 show the only beam attenuation data col- lected for this area. The more turbid waters of November to February of the two figures provide a further indication of tidal flushing of lagoons during this stormy season. Figures 4 3 through 4 5 show the conversion of all the data to the common parameter K. Secchi depths less than 2m wete not dealt with by the Z to K conversion formula which was derived from measurements deeper than 2 m. Therefore, the Texas lagoon measurements do not appear on these figures. These plots display the same seasonal variations mentioned before. Shideler (19 75) notes that secular variations were thought to be related mainly to annual stream flow variations and storm occurrences for those years. D. EASTERN GULF OF MEXICO The eastern Gulf data indicate similar mechanisms of turbidity generation as were present in the Western Gulf. The main differences are due to the appearance of some upwelling during winter months and a change of the months of highest stream flow along the Florida coast. Alexander, et al . (1977) attribute mixing of the water column over the eastern Gulf 's continental shelf to wind stress which can be linked to the frequency of low pressure disturbances (storms) crossing this area. In winter when storms are most frequent the water column was observed to be unstable and well mixed. By contrast, in summer and fall the water column is stable with established thermoclines and haloclines. Alexander, et al . (1977) also noted that the passage of Hurricane 44 Eloise did not raise turbidity levels to the degree that per- sistent winter storms had. Also^ the rise in turbidity caused by the hurricane disappeared after one week. Monthly Ekman transports for 2 degree squares in the Eastern Gulf have been computed by Ichiye, et al . (1973). Their results show transports to be lowest from June to August with averages less than 3,000 gm/cm-sec. Transport is generally alongshore except from December to February when offshore transports result from scattered areas of upwelling along the Florida coast, especially near De Soto Canyon. In other months there may be occasional periods of offshore transport but of smaller magnitudes. Surface currents generally flow in a northwesterly direction along the coast in the nearshore areas. This directs Mississippi River flow away from the Eastern Gulf except from April to September when a reversal in flow direction occurs from the Mississippi River mouth to the Florida panhandle. Incursions of pockets of Mississippi outflow were observed by Alexander, et al . (1977) along with Loop Current eddies which had intruded onto the continental shelf during these summer months. No Loop Current intrusions were found during other seasons. Table VII summarizes the main parameters used to delineate optical seasons. Wind mixing occurring during winter storms and a simultaneous increase in upwelling makes January to March a season of highest K. Lowest K values can be expected from June to September when the water column is most stable and clear water from the Loop Current intrudes upon the outer shelf. Exceptions to this occur along the Mississippi, Alabama, 45 and western Florida coasts where turbid Mississippi River out- flows make K higher. The two remaining seasons are transition periods where K is variable and less predictable. Stream flows other than the Mississippi do not appear to influence turbidity levels greatly. Figures 46 through 53 show the Secchi measurements obtained for the Eastern Gulf. Figures 54 through 59 show beam and irradiance attenuation measurements and figures 6 0 through 66 show all measurements converted to irradiance K. Overall, these plots show the lowest K values encountered in this study. 46 V. CONCLUSIONS AND RECOMMENDATIONS A. CONCLUSIONS The present and near-future water penetration capability of laser systems is limited to about four attenuation lengths (Enabnit, 1979) as was discussed in Chapter II (see also Fig. 6) , Seasonal Kd values were plotted in nineteen figures for Pacific Northwest and Gulf coastal areas. These figures indicate where and when laser bathymetry systems would be successful, given the Kd<_4 criterion. These seasonal Kd values were derived from optical data collected over different years. However, inter- annual variations may change the utility of laser bathymetry systems in a particular area. In the coastal areas of Oregon and Washington laser bathy- metry would probably not be successful at any time over signifi- cant areas as is shown in Figures 67 to 75. A Kd value of ten was contoured (the lowest contourable value) as an indicator of possible areas surveyable by laser. The area within the Kd=10 contour is small for all seasons; the even smaller area with a Kd<_4 is too small for practical laser hydrographic opera- tions. In the Western Gulf, limited areas are candidates for laser bathymetry as shown by Figures 76 to 78. The southern half of Laguna Madre , Texas, is surveyable by laser bathymetry from November through February. The area from Matagorda Bay to Sabine Pass off Texas is surveyable all year up to depths of 10 to 20 fathoms as indicated by the Kd=4 contours. West of the 47 Mississippi Delta, possibly to Sabine Pass, a strip from outside local estuaries and bays to the 10-fm depth contour is available to laser bathymetry from March to October. i The Eastern Gulf coastalarea is the area best suited to laser bathymetry as indicated in Figures 79 to 85 by the Kd=4 contour. Off Florida from Panama City to the Florida Keys, an ' 2 area of 30,000 nmi bordered by the 30-fm depth contour may be surveyed by laser bathymetry during June through September, and a reduced area bordered bv the 20-fm depth contour all year. t 2 This 30,000 nmi area alone represents 15 years of work for one laser system and represents a costs savings of $69 million (1977 dollars) over launch/sonar surveys. From Panama City to the eastern Mississippi Delta an area of 8,800 nmi bordered by the 20-fm depth contour is surveyable from October through December. B. RECOMMENDATIONS 1. More optical measurements, especially irradiance and beam attenuation data, should be collected throughout the year in U.S. coastal waters. 2. More simultaneous measurements of Z , K, and C at the same wavelength should be taken and more investigations of the relationships between them should be made. Universal relationships should not be expected due to regional variation in suspended particles and yellow siibstance (Gordon and Wouters , 19 78) and, therefore, such studies should be regional. 48 3. Investigators should send optical measurements to the National Qceanographic Data Center, especially measure- ments made in the Gulf Coast area. NODC should establish irradiance and beam attenuation data categories as part of the Ocean Stations Data Base. 4. This thesis studied seasonal variation of marine optical properties in U.S. coastal waters; others should investi- gate long term trends and their cause. 5. Investigators should always state the wavelength at which their optical data were taken. 6. Prior to the commencement of laser hydrographic survey operations. Nimbus 7-CZCS data for the areas of interest should be examined and used to update the figures pre- sented here. 7. This thesis did not examine the bottom reflectivities of coastal waters because of their generally relatively minor effect compared to attenuation lengths as a limiting parameter for laser bathymetry operations. However, in areas of marginal utility for laser bathymetry, bottom reflectivity may become significant. This suggests further study of this effect is needed. B\ The National Ocean Survey should consider the west coast of Florida for airborne laser hydrographic operations due to the favorable marine optical environment there. 49 APPENDIX A DATA SOURCE OF IN-SITU OPTICAL MEASUREMENTS IN COASTAL WATERS 1. Data Source: CDS Data Base Institution: Texas Natural Resources Information System Geographic Area: Texas Date of Tape Generation: May 19 79 Data Range: 1968-77 Optical Data Type: Z Number of Data Observations: 14,232 Data Reduction Procedures: Data was on magnetic tape. Converted to K by methods of Section III.B.3. 2. Data Source: SD-2 Oceanographic Stations (Master Records) Data Base Institution: National Oceanographic Data Center Geographic Area: Primarily Oregon and VJashington Date of Tape Generation: March 19 79 Data Range: 1952-74 Optical Data Type: Z Number of Data Observations: 1329 Data Reduction_Procedures : Data was on magnetic tape. Converted to K by methods of Section III.B.3. 3. Data Source: STORET Data Base Institution: Environmental Protection Agency Geographic Area: Florida Date of Tape Generation: June 19 79 Data Range: 1966-79 Optical Data Type: Z Number of Data Observations: 3,000 Data Reduction Procedures: Data was on magnetic tape for selected stations off Florida. Converted to K by methods of Section III.B.3. 4. Investigator: Barret, Barney B. Data Source: Barret (1971) Institution: Louisiana Department of Wildlife and Fisheries Geographic Area: Louisiana 50 Date of Data Collection: 1968-1969 Optical Data Type: Z Data Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. Investigators: Barret, Barney B. et al Data Source: Barret et al (1978) Institution: Louisiana Department of Wildlife and Fisheries Geographic Area: Louisiana Date of Data Collection: 1974-76 Optical Data Type: Z Data Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. Investigators: Berryhill, Henry L. , Jr., et al Data Sources: Berryhill et al (1976) and Berryhill et al (1978) Institution: U.S. Geological Survey Geographic Area: Texas Date of Data Collection: 1975-1977 Optical Data Type: C Instrument: Martek Transmissometer (52 8nm) Data Reduction Procedure: Integrated C computed by method outlined in Section III.B.2 for 28 stations sampled six different times. Most stations had the beam transmission measurements (surface, middle, and bottom) per profile but some lacked bottom measurements. For these stations the middle value was used to the bottom depth. K was then computed from c . Investigators: Carder, K. L. , and Haddad, K. D. Data Source: Carder and Haddad (1979) Institution: University of South Florida Geographic Area: Mississippi, Alabama, and Florida Date of Data Collection: 1976-1978 51 Optical Data Type: C Instrument: Hydro Products Transmissometer (5 50nm) Data Reduction Procedure: The original data were given as suspended particles beam attenuation coefficient (C ) contours on profile figures. The use of this data ^ required special processing. First, values of C had to be picked off the figures for the C vs depth profi?e at each ocean station. Second, C was converted to C for each layer by using the relation C ^ .06935 = C (Carder and Haddad, 1979). _Third, the methods of Section III. B. 2. were used to obtain K. Investigator: El-Sayed, Sayed Z, Data Source: Unpublished Data (El-Sayed 1974) Institution: Texas A&M University Geographic Area: Gulf of Mexico Date of Data Collection: 1971-73 Optical Data Type: Z Data Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. Investigators: Godcharles, Mark F. and Jaap, Walter C. Data Source: Godcharles and Jaap (1973) Institution: Florida Department of Natural Resources Marine Research Laboratory Geographic Area: Florida Date of Data Collection: 1970-71 Optical Data Type: Z Data Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. 0. Investigators: Gordon, Howard R. and Dera Jerzy Data Source: Gordon and Dera (1969) Institution: Institute of Marine Sciences, University of Miami 52 Geographic Area: Florida Date of Data Collection: December 1967 Optical Data Type: K Instrument: Irradiance meter with a selenium photocell covered by a 525nm filter and a diffuse screen. Data Reduction Procedure: None 1. Investigator: Grady, John R. Data Source: Grady (1979) . Five Cruises of GUS III Institution: National Marine Fisheries Service Geographic Area: Louisiana and Texas Date of Data Collection: Jan-May 1966 Optical Data Type: Z Data Reduction Procedures: Z converted to K by methods of Section III.B.3. ^ 2. Investigators: James, W. P., et al . Data Source: James (1977) Institution: Texas A&M University Geographic Area: Florida Date of Data Collection: 2/76, 3/76, 7/76 Optical Data Type: K, Z Instrument: Kahl Scientific Co. Universal Radiometric Submarine Photometer (Green filter) Data Reduction Procedures: K data reduced to a depth_ averaged by method of Section III.B.l. Z data converted to K by method of Section III.B-3. 3. Investigators: Joyce, Edwin A. and Williams, Jean Data Source: Joyce and Williams (1969) Institution: Florida Department of 'Natural Resources Geographic Area: Florida 53 Date of Data Collection: 1966-69 Optical Data Type: Z Data Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. ^ 4. Investigators: Kamykowski, Daniel et al . Data Source: Kamykowski et al (19 78) Institutions: University of Texas Marine Science Institute Port Aransas Marine Laboratory Geographic Area: South Texas Date of Data Collection: 6/78-11/78 Optical Data Type: Quantum K, C, and Z Instrument: Lambda Photometer (quantum) Martek Transmissometer (52 8nm) Data Reduction Procedure: Quantum K reduced to K by procedure outlined in Section III.B.l. Integrated C computed by method outlined in Section III.B.2. Quantum K and Z were used to compute the conversion formula, Z to K , for the Western Gulf Coast and the procedure is described in Section III.B.3. All data for one oceanographic station. 5. Investigators: Manheim, Frank T.; Steward, Robert G. , and Carder, Kendall L. Data Source: Manheim, Steward and Carder (1977) . Institution: University of South Florida Geographic Area: Mississippi, Alabama, and Florida Date of Data Collection: 1975-1976 Optical Data Type: C Instrument: Hydro Products Transmissometer (550nm) Data Reduction Procedures: C and K computed by methods of Section III.B.2. 6. Investigators: McGrail, David W.; Huff, David; Jenkins, Stacy Data Source: McGrail, Huff and Jenkins (19 78) Institution: Texas A&M University 54 Geographic Area: Texas and Louisiana Date of Data Collection: 1977 Optical Data Type: C Instruments: Martek Transmissometer Data Reduction Procedures: The data published were trans- mi ttance profiles graphed for each ocean station. Thus, inflection points were picked off and the methods of Section III.B.2 were used to computer C and K. 17. Investigator: Oregon State University Cruises Data Source: Unpublished data (Pak 19 74) Institution: Oregon State University Geographic Area: Oregon Date of Data Collection: 1968-1971. Optical Data Type: Z Date Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. J. Investigators: Pak, Hasong and Zaneveld, Ronald V. Date Source: Unpublished data (Pak 1979) Conclusions of this data were published by Pak and Zaneveld (19 77) . Institution: Oregon State University Geographic Area: Oregon Date of Data Collection: 8/74-5/75 Optical Data Type: C Instrument: OSU Transmissometer (66 0nm) D^ta Reduction Procedure: Computed C at 66 0nm converted to C (532nm) , and converted to K by methods outlined in Section III.B.2. K Investigator: Saloman, Carl H. Data Source: Saloman (1974) Institution: National Marine Fisheries Service Geographic Area: Florida 55 Date of Data Collection: 11/70-9/71 Optical Data Type: Z Data Reduction Procedure : Computed K from Z by method out- lined in Section III.B.3. ^ 20. Investigators: Saloman, Carl H. and Collins, L. Alan Data Source: Saloman and Collins (1974) I Institution: National Marine Fisheries Service Geographic Area: Tampa Bay, Florida I Date of Data Collection: 1/71-12/72 Optical Data Type: Z Date Reduction Procedure: Computed K from Z by method outlined in Section III.B.3. 21. Investigators: Small, Lawrence F. and Curl, Herbert, Jr. Data Source: Unpublished Data (Small 1979). Conclusions of this data were published by Small and Curl (1968) . Institution: Oregon State University Geographic Area: Oregon Date of Data Collection: 4/62-4/65 Optical Data Type: K Instrument: Kahl Scientific Irradiance Meter (photopic) Data Reduction Procedure: R)ne 22. Investigators: Stevenson, W. H., and Pastula, E. J. Data Source: Stevenson and Pastula (1973) Institution: National Marine Fisheries Service Geographic Area: Mississippi Sound Date of Data Collection: August 1972 Optical Data Type: Z Data Reduction Procedure: Computed K from Z by method out- lined in Section III.B.3. 56 UtJUUUUtJUU u o OS U o u ^ <2e-t6H u * aatn q U v^ cy«c2 u \ <-» • staww u Ln .^ >*- co:>i= u in ,«, z-< << -3:h U in .^ O » JH U tn -^ cjx O-^ H U in (N iiST- eHU2:<: U in N» «• * Mtax U in f- p-io Zf-iWH u tn M M . 00403 U N \ «< 2S^ O Wl U \ - iJ CJfa » coca u :>i: h • < « » qq-j:2: u CO - OT "— ' ^x Ehz cnu Sit, H:» Q* uso-« U .^ *^a »- M Oi cii<<: zctrw-i t) o 'S.fNVe-i ij ^-^ >« * OMp^p-i u o 03 \- ph 9 e- u a- I X- - OS e-4 • cu » QQQ3 U '— VJZW < "^ WiT Z&3W • a tn QMUE-t as o qm CUCQOW U OI > X >• *«»; 1-7 EX W OUIQ u • * <:Wo» Q -< Hoo o Qx -aa U Oi ,«. s:»-«. % w '*^ z •. o DCQWCtiM CJ W in «NU\ M I — org r- Srt ZtOM U a *-* \ .U- fc -^— . SM i-i«o30 p_( f > » p^ cncernos HP-I iJ-S us «aJ (T>»-- 03 ID — »— . a2X JQ-S!tj f> X >t \XU- 04 W >• » O EMU U * » Q>JU\ • o zQoes e -*<< ^i * -> P-iWOCO to * O M » *W C>-.-^ i-J>-4 tOl o o -< OS «< U Q ^-o sWOi ca «s:o&t*i cj >^ Oct ^CNO * U*QQ *- — X •> »-o .ooo»-o -fitasEQs u •■ O"*-- \rfT-\ XX *.+.-. *m oof-ioco o CJP-I *-i f— . .vo >*'ZX :?=tO SM (N ^ i-3 »- »— t- O *- ,*!zt/)z f) P-t if ,,» rno\o t-i«< U4i-iirt P-i fc « e-1 JD3&3 M O Sij *-^ V ^n . QSE QjCUK sdX oOEOOO r-» ■C-aSSrW U * ZO QV^ZOcr 2^— — Q^— —r-i . ••- 6h e-t >• £H E-f =-i o e-i uaiCBx>i CJ sn=oos>xxw i m «< e-t e-t x z z s id s * . cj? MM F-iCQ t) xF-tr/)ozx JfsavOi <«j:z«a; CDcOCT>r-)rMW . c-t cn=30 CJ 3"if3"Z cainr* McaoOrf:^:*-' os ii ofN • .cv o 'WQco CJ ♦ » * o ao»- z < es H-i ^-'^-'V ** M'-M o»5-i ow w e- = M >JZO CJ 03CBQSM r*0 M 03 CC &-. N,* >-• %^-' W h-5 W C3 CJ) h4 E-* • ciiO-jJzw U wcacqcocT z • • E it ii ii xKi-? <: o o^s-H.— zcu MQSOQ3 O CJOOZ* OOO r-r^lr- J II W 6-t II O ^-<: XQ QQ QQ QOM 3CE-(eoM<< CJ et^wcacaHJ^-u-s'^fl'T: II it Mf-if-isiysQ -c cj ^osinxxxs-ixxsra <:u>eH CJ e-te-tens-cc-is-ie^e-iSirQ e-i<: ««: o a m u qom -scafN^-'- — — ^ "-^"-^ cBW<:«j;tn cj zzzmw<<<*s:'4 h q owo «.:t.ctHiii(ttii,ct4Ci^fc4 C5'-5 e-lQ U MMMQQ3QQCiQCjaiQ3 CU ■< rt! -a: aS X -a! Q2H Q CB Cl4 O MM M M M M M M ooQcnoa CJ s •>< »- QSCeiZ •< CJ o u a<04«s:«ccj CJ U oa u CJ o UUCJUUUUUCJU UU CJU CJCJ ,- APPENDIX B PLOT PROGRAM 57 o en a 04 o o S • • • (O _3 • • • •< <:04au04a40 ene-tp-tfr-e-' 03- E-l > OS » tn ca o w z n =3 C-i o in -^ o -< c/> C » MOO s: » ;^ H oz M Q MM w o «; I o O t ^ II II o e-.z«'J jo?-i u: «»: i< Q »3! Q o U--3MHU to CQ o H S &4 M cn u Cl] . sz UQin com -<« »&ao z =3hJO O-CO ItiCJ cn WW X cn E-IOZ OO • OOMZ H *€hO o«QSx: z O M -< El)C1i-t>4Z z emi II — ' uww W -<<-i Mbi'-n a 1 1-3 CLi tii ^-' ►-5^^-' Mo xafci P-tZOQQM OE-t e-toz cn&-H UUUvO «5 S-t30Q3 >wzcoow caao ocn W OZ»-CQ cnnUCi3 4.o CQP-t &3Ph O osico^Ga z oe-t zocn&3 + -c ME-t <-KJZ>WZCJ z QtyoM ►J QSQs: cy o <- o o xz woo e^ cn OjEHtt. X M Qcn •< -cat UUU UOUUU u 'UUCNUUO H • » X s X Eh o H a Pu H z O << << > 03 OS X M u Z en cn CE3 9 >4 O O < u H ca EH s «< cn ' O z w 3 a M X <<. Eh s cn X ti z o o cn M H C3 Eh w O M X s cn n Fh • 33 Oa x: a P^ o M M CS as OS 3 M b4 • «n X z cnw s Eh o Cc30 o M zx W o EH MPH H Eh U >JH H cq Eh cn O OS rn*< o z M Zi-3 04 o M Q O J33 >J (N OS M O I-) o > QSm -»: n u M z H _ u Eh -ccj b O < M z O o o cn EhH C3 o Q o <:U u o W Oi iJ-a: o ,^ ^- P-i Oi «e o ■» e_> «ss (^.^ Etitn s: o Q o CJO O o z Q ^ zz - hJ cntnoo*-" z Oi MMO-^ »<«: MEht-o t \ EH IK-N <:> ^- CU •O— . ...^ M 63S-iO'^ JCB m WZEhOM M « cao'— caw » C3 •h-31 ■— "~^ ^-» -a XtJ cn WP-t r^ <6r- . \cn cn cncucncn >z (N a 11 j-^ ..^}-^ M cn .-« e-ii: OMZ II Wmmm>» s»ca EHZWCi30&H H ^ > >i^ -'II r- • II X ZOSMi-JW QWS -seocncn— .+ j-ijr*i MH HOtCn MZX O *■ .(HMMQMM OEhShJ OSM II o J(N>>>--Z^ — P^ &.U -s:.-3j CJSEh rn «< ■^-^ II cn II cnz WQHhJ»-J 05 .Z>U EHO-^HUU «S&HQmQ h oica z QDiXW OSW -«: • • • • • • o 9 • • • • • r— • • • • • t o (NUOCJuO UUU APPENDIX B (cont'd) 59 a H H Cm i< T~ CO 1 •< « £ o hJ • « o e-i » < ^^ m4 n >• ^i* « en in OM o o> o ^ » • r- o> >> » oo ^ CN H • u CO » H • o— ,0^ ,«>« •< f-k- can 0 en OS » ^^ 0 en __^^ «« o —X er^o^ CT> ^ A. r- m » 1 + .< u » n — o • « » en • • n ^ • t oe-< O cnw^ o O »o< z » E-tZ>4 o * « OJ om . CU t^- u • o • «o OT •o z*-» o zo oil «<»-'*- •rtoa ,_^<«* M"*- >-x U II r--*-Ta m &4 H-»J u^coa It zoa .f-i S-lg-t O II w r)M nOSIM oow oo l^^o< 3 X 03 tn3 = W J=3 -JJ SM-< 2 UOC5 0-CZ25 .CUZ 04 Ol ^-'11 *■ -H -s:* — OW M 23 M ' hje-«E-t>c-i Wir-3 ^fOvje-t rjnJJH JhJO* b<:Hj. Eh < < < Q 2 O H D W E-* < < CQ g Eh M U 2 W « (X O cn fa M « ^ o < fa u CO •k z >H o < H ffl en en >H w fa « Di o w w H 05 2 O « s < w 2 2 M M a 2 w fa t«: O < Eh >H « cn ^ K s Eh § CU D fa cn Q w CQ < Eh S- «+- CO r»- CO CO cn s- cu cr> cn CT> CJ\ CT» cn o o « • • • • • o o «3 + o r^ CO U3 LO cn LO UJ CTv o n3 CO LO CM LO CM r-^ CO s- r^ LO n n ro CO CO CO CO CO IT) • • • • • • • •^ Q • ■ — ' Tf 2: 1 c II r— ■^ LO r^ CO CO CO oo • CO o C o LO r— <^ r^ o CO 2: _i CO LO LO CO cn 00 CO CT> CO < 1— CO KO • • ♦ • • q: o ' • • ' t— 1— r— o <_) 1 o j3 LO + O CTi r— CM LO "^ CM CM LO *— ^ ro IJ3 ^— r>» •^ •=J- ^— r^ ^_--' o J3 C\i CO CO CM CO CO CO CO C_) u-> • • • • • • • • cn CO CO o un LO 1— ^ r^ cn CO «^ '^r LO LD CTi 1— o o o o o "lo • • • • • • • • N*— ' c_> ■ '" '— '— •— '~~ ■— O s_ <+- P^ CO LO O CO en s- CT> cn CT> (T> cn o o • • • • • • o o 03 + --*s LiJ C ra CM O cn LD ^:r • LO LO CO CO CO ^:r CO CO CO O C/1 ^^ • • • • • • • LO • C_) >^ — Q 1 c II LO LO CO CO ^ CO ^ ^ CO CO «3 • • • • • • C_> 1 1 1 I 1 1 1 1 CM E •"; II 1 — **— ^ II o E r^ r^ r— LO CM r^ CO CO o cr> vX) o r^ cn ^:f 00 00 o LO C7^ O cr> r— r— o o o • • • • • • • • LO C_) ''" ^~ '"' ^~ ' '~~ o ^—^ s: — ' -C z: ■^ _j 1— +J r— lO o o o o < < cC — o cn ^ I O r— 00 « r>. O CM CM • r>» o o 4- o cn "^ cu O r- Qi r— I— I— OO LO o o o o cn «:a- O r— »« «\ • O " •* 1 — I — LO LO fO LO o o O CO CO -M O I— •> d) O CO ^ " " — to f" »^ ** « O CO LO LO •I- o o o -(-> CO r— LO +J *" *" "" (/^ #% A A LO "^ "Cf rD O O O CO .— f— LO O I— I— .— •K 61 TABLE II. DATA USED TO CONVERT SECCHI DEPTH TO IRRADIANCE ATTENUATION (Z TO K^) FOR EASTERN PACIFIC COASTAL WATERS ^ ^ 1957 North North _ , Station Date Latitude Longitude Z (m) K (m~ ) 49A 7/9 39° 59' 126° 38' 32 .0718 51 7/10 40° 02' 127° 07' 32 .0363 61 7/15 44° 50' 126° IT 22 .1114 64 7/23 44° 18' 126° 38' 20 .1117 65 7/23 43° 51' 127° 22' 32 .0708 66 7/24 43° 43' 127° 5T 32 ■ .0747 67 7/24 43° 13' 127° 12' 26 .0903 83 7/30 39° or 126° 26' 28 .0674 88 8/4 38° 56' 125° 42' 26 .0651 89 8/4 38° 57' 126° 10' 24 .0900 91 8/5 38° 14' 125° 40' 20 .1096 92 8/5 38° 05' 125° 25' 16 .1327 93 8/5 38° 14' 125° 44' 22 .0938 95 8/6 37° 06' 125° 07' 24 .0999 96 8/6 36° 58' 124° 56' 18 .1291 98 8/6 36° 45' 124° 34' 20 .1340 101 8/7 36° 45' 124° 34' 22 .1123 102 8/8 36° 08' 123° 24' 20 .1151 103 8/8 35° 19' 123° 23' 10 .2577 Original station data from Callaway and McGary (1959); K computed by van Norden. 62 TABLE III. DATA USED TO CONVERT SECCHI DEPTH TO IRRADIANCE ATTENUATION (Z TO K ) FOR WESTERN GULF COASTAL WATERS ^ Date Local Time Z3 (m) Quanta K„ K3 (m-b 5/29/78 1300 23.75 .0609 1.085 .0661 6/29/78 1700 20 .0909 1.06 .0964 7/24/78 1200 26 .0683 1.095 .0748 7/25/78 0800 19 .0587 1.08 .0634 7/25/78 1200 20 .0442 1.12 .0495 9/25/78 1345 4 .387 .975 .377 9/26/78 0000 3.5 .295 .975 .299 n/08/78 1200 9 .233 .990. .231 11/08/78 1600 9 .183 .980 .180 11/09/78 0800 14 .187 .950 .177 11/09/78 1200 14 .158 .950 .143 All observations at N 27° 34' Latitude and W 96 50' Longitude. Original station data from Kamykowski, et al . (1978) ; Quanta Kq and K computed by van Norden and K/K^ obtained from Jerlov (1976) . 63 u < o E-» W 05 K U ^ Eh 04 < w s Q )J H < a: E" u W u < w O w U E-t • Di en a • > D Z o Q u W E-t o u Eh U J tn pa z en o H « 03 O m fa s o '"w ui;^ a; o e: Eh < w W z Nl H ««-«' J 2 fa o o H £h >• < 05 D rf 2 s W § Eh D E-t cn < • > M u 1^ m <: E^ c o C -H (T3 -P 0) (d cr fa •H > +j G C en Q) 0) C in o • o + m o • o + CO CO N (SI LD y£> CN CN w (0 IK>e: IJ4 o o • • o 1 o 1 1 en 00 1 en m en tS3 N 0) V£) ■«r m tH O o o i2 • • • 03 o o o •H >-l + + + fO > 1 rH 1 1 4J 1 en 1 en 1 ( en c rsj N tS] (TJ Q) iH ^ ID t3 < o o + en CS] in o CN I o l« H O • o I o CN I CSl o en N o I o It4 C 0 •H 4J -P rH en iw (d - Q) c r* •H rH fd • • C -H rH 0 -P en en 0 (d • • jS — C Oh Q D D en fa 64 Q ^ c Z i»^l 1 7 _j 2 z 2l 1 o V ^ 5 , (/) 0 -J 9 < I 1 1 »- X D < i<: ") o S^ 2 X I I < -0 o o 2 X »- 2 " I < I O _^ I I u. I 1 — z V 1 -D on O z 2 A f— < z LLING EX RIVER OW STREAM -OWS z UJ q: q: 3 Z J— < Q O t/) < l>i < t u g 1— 3 Q -1 s ^ Ld CL 3 S R z o 3 cr u. ACE U < LlI — 5 ^ m ^ s U a. Q 1 X I 5 FT. ATCHAF EAM FLO ER STRE FLOWS ANKTON r OF MIS BLE (S. :)ATA VAL UTED SE> division: m ^ 0(3 ^ X -J (/> < 7 Q. ^ Ul CO 1 O ZOOP (we: ^ LU CO r 2 o u en 2 O cn cn < u M &^ Oh O W 2 M w W a o Q cn cn oi Eh s D 2 E-t cn s M > CQ < 66 < 1 Q Z o 8 0 _j en z _t \' o X k < CO O u X en z hJ < 5 Z i«: S J ^ z E-t ) 9 2 O z -^ M i' s / k Ei) 2 O _i Q X o < CD X V Q / ^ :^ X ^^ cn D X X cn Ul < < X X ^ ^ o < X 2 —> ^ ' < 04 b ^ FROM ISSIPPI z O m -J q: Li z < 2 ^ ^ UJ < s 1- X •": IPPI FLO' to > UJ u >i li- Z i O LJ CO ^ UJ u_ UJ o n en to E- LO z E-i cn < Id -J CD < FREOUENCY PRESSURE ( X ID t/1 OFFSHORE TRANSI MISSISS RIVER RIVER FLO ALABAMA & FLORIDA FLO COMPUTED DIVISIO • M M > J CQ g 67 z < LLI < Z D £C LU CL h- O O 2500 2000 1 500 1 000 500 $2730/NM AVERAGE LAUNCH HYDROGRAPHY. COST -TOTAL COST OPERATING COST CAPITAL COST $438/NM LASER COST 500 1000 1 500 2000 AREA SURVEYED ANNUALLY (NM ) FIGURE* 1. LASER/SONAR COST COMPARISON, COSTS IN 1977 DOLLARS (NOS, 1979) . 3 0NVlllHSNVdl 30NViaVddl U Q < Z M EC » Eh m U cn 2 W a u H en Eh 2 S un m CU U rH H W Eh W U CU W 2 O O. Eh Eh < Eh O CO Di; 2 W CO < >* < « < o Eh J U CN W Pi D H fa 69 COASTAL TYPES .0 0.1 2 I- z UJ u Ll u. O (J z O < D Z U f- < u u z < < cr q: 0.01 •OCEAN WATER (JERL0V.19761 1 300 400 500 600 WAVELENGTH (NM) 700 FIGURE 3 SPECTRAL IRRADIANCE ATTENUATION COEFFICIENTS OF DOWNWARD IRRADIANCE IN THE SURFACE LAYER FOR JERLOV OPTICAL WATER TYPES (AVCO EVERETT RESEARCH LABORATORY, INC., 1978). 70 2 cr CC UJ 10 _J Q_ CC LjJ 10 < _1 CO _J < o t/) 2: q: 3 h- hl u rr LLl «0 ^ Z LlI z 1 q: < LU O LlI 3 CL LlI lO < _J CO T 71 2 .7 2 V- I- z y Li. Ll LJ o u .5 o §•4 z UJ I- 3-- DATE : 5 MAY 1979 PLACE: KEY WEST FL SEA STATE : 1 LASER POWER:50KW. BOTTOM DEPTH :34.4F •500 FT. 20 30 40 50 60 70 RECEIVER FOV (MRAD) FIGURE 5. SYSTEM ATTENUATION COEFFICIENTS AS A FUNCTION OF RECEIVER FOV AND AIRCRAFT ALTITUDE. DATA FROM KRUMBOLTZ (19 79). 72 80 70 60 50 ^40 QL Q O 30 §20 10 NOS GOAL NASA DAY O .1 .2 .3 .4 .5 IRRADIANCE ATTENUATION COEFFICIENT K FIGURE 6 . EXPECTED PENETRATION OF" DIFFERENT LASER SYSTEMS AS SPECIFIED BY IRRADIANCE ATTENUATION LENGTHS TO THE BOTTOM. 73 PERCENTAGE OF SURFACE QUANTA (350-700nm) I 10 20 50 1 III II IB lA I FIGURE 7 100 — -J w W' ^^ ^ ^ ^ X y V y / ^y / / m 20 ^0 60 80 100 120 DEPTH PROFILES OF PERCENTAGE OF SURFACE QUANTA(3fO-700nm) FOR DIFFERENT WATER TYPES (JERLOVJ976) 74 K/K 0.95 - 100 - 120 -- 1^0 FIGURE 8. THE RATIO OF IRRADIANCE TO QUANTUM IRRADIANCE IN THE SPECTRAL RANGE 350-700 nm AS A FUNCTION OF DEPTH IN DIFFERENT OPTICAL WATER MASSES (JERLOV, 1976) . 75 1 1 1 1 .8 - .7 — Rs«1.25Zs''»0.05 — ^^ ^ 1 2 ^- Zg -O./0K3-O.O4 Y^ ^ /// 6 __ ///\ — . 1- •'^ /f \ • Z // \ u // \ u • >^ \ b. // \ u. .5 — // \ I u /• • \ o ^ \ u /^K3=1.21Z3^0.06- \ 2 , . \ O .4 — //* ^— h- ^ < /x * z> /^ z • ^'^ Id yV a' __ • J7* < J/ LU • V U jff 2 jy < .2 — — j^ — Q * A' < jy q: . ^ a / .1 « 1 1 1 1 1 0 ,1 .2 .3 A .5 SECCHI DEPTH RECIPROCAL Z^''(M-'') FIGURE 9. LINEAR REGRESSIONS OF K AND Z FOR EASTERN PACIFIC COASTAL WATERS. ^ 76 1 1 1 i 1 ^ •7-1_/-\~7iP -nni / '^ / 4Lc -vj./orv ^.u 1 ' / / ^■^ — / / / - T / / y 2 Rs=1.262^^^0.03 ^///^ FFICIENT JK • ^— u O U ■ /^ \ §.2 .^ /^ K3=1.14Z3''*0.04 — ^ ^_ 5 z • / 5 -I. • / IRRADIANCE ] 9 • 1 1 1 1 1 .1 .2 .3 SECCHI DEPTH RECIPROCAL ZgCM"^) FIGURE 10. LINEAR REGRESSIONS OF K AND Z FOR WESTERN GULF COASTAL WATERS. ^ ^ 77 3 z y y u. Ll O u z o D Z QJ h- < u z < < q: q: .2 .1 H- Zi'=0.72K^:2^Q01 ■fl.=U25Z3'1*0,03 0-20 '^o:2(3-^^^^0-0^ 0 .1 .2 -1 SECCHI DEPTH RECIPROCAL ZsCM"') FIGURE 11. LINEAR REGRESSIONS OF K AND Z FOR POOLE AND ATKINS DATA. ^ ^ 78 .7 Z .6 LJ y u. Ll o z Q .4 !< Z LlJ UJ U < .2 O < £ .1 .1 NORTHWEST COAST R=1.25Z;^>0.05 ^" WEST GULF COAST R| 1.262-^0.03 EAST GULF COAST __ K^=1.15Zs^-0.03 WITT,ET AL(1976) .2 .4 .5 SECCHI DEPTH RECIPROCAL Z^ FIGURE 12. LINEAR REGRESSIONS USED TO CONVERT Z TO s K FOR SELECTED U.S. COASTAL WATERS. s 79 SON JFMAMJJ ASONDJ 45 N 40N 35 N 30 N FIGURE 13 UPWELLING INDEX FOR THE U.S. WEST COAST (m^/ sec / 100nn ) BAKUN C1975) 80 LjJ Q:: o Ll O _j CL O o CL 00 < o u u I- O 81 o _J a. z O h- 00 O CL Ll _l LlI I— OO LlI ID LU 3 CD Li- sa ^ \ * > \<-^ i i « ( 1 • • • .V J 1 1 / f • • • • •• i . .. • • • •• * • • • • : • • • • % • • • • » • / / / • 9 ( • V- • • •— . • • ' ^* / • 1 ] "4 / / ^ 1:; -J o D _J CD < ^ .^ 1 • 1 EASTERN G POSITION P FIGURE 1 ^ ^ 1 \ 1 \ N - ■ i ^ \ 7^ s * \ • \ 1 ./ / « 1 83 84 86 47* NORTHWEST COAST SECCHI FEB-APR 46' FIGURE 20 45' 126* 88 89 qn 92 .X ^T NORTHWEST COAST C JAN-DEC 46° /' v.. FIGURE 26 45° 126° 125° 93 94 o J o a ,\o' ,?f^' (M ■ O / CM a O CSI 95 CO C\J o o }? OREGON FIGURE 35 M2l \ \0.3 \ 1 0. 1 ^ y 0.3 V 0.2\ I 0. -O nn ' a l-cl. 102 104 105 106 WESTERN GULF C - DATA NOV-FEB FIGURE 40 107 WESTERN GULF C-DATA MAR -MAY FIGURE 41 108 94° 30° L 92° OUISIANA 90° 5 . ^*^>>k^ L»-i "^ '^.^•nrU"' ^^^ 28° 0.3 y - -. -^ \ v.^ ■ 1 \ s ■\ / 0-2 0.2 ^^ • ' 's./ —" WESTERN GULF K - DATA JAN -DEC FIGURE 42 109 110 Ill &. \ \ \ \ \ i ! 1 -^ S, \ J \ jn**! 1 1 at 1 1 -^ \ "L^ (• / tzr J a' b- /\J ' 0) f V ^v2 1 1 ,K- ^v ^/' ^: <.' \ ; \ : 1 ^^"^ A ^U9 » w i ^ / d d w li \i ic: I 1 i < ^1 :\ Q Z ^ --sK7 1 1/ LU < 7 ^ V 1- o U} / : q: CVJ ^ s ; 1 : 1 > a 0 (X - \ 2 LO -' X ] a s a 1 -J, J ■ t \ 1 o u u o 1 z 3 ' / 1 1 -> 3 "5 O Ll / o 3- ' °\ d 1 o ,^^ --^ I r\j i LlI 1 '^ ^^ c\\ '^ d / I h- Q) \y) / KO : y 1 1 LU ^ /. / ( i 1 : I 1 / § i \i N \ V \ . 1 , \ : i. i V 1 \b 1 1 \ 1 o 1 1 \ i s j o 1 1 f^ 1 \ i 1 CO j i \\ i \ ^ 1 O) ; 1 1 r t o ' 1 \\ *. =>\ 1 i 1 to ^\ ^ o 1 \ >> i ^, i < -^ /" t^ 3* --^ 1 1 X ^ r I m O ! hi \ r iL \. 1 < 1 1— i V '«'"' ^^ - d < 00 1 i 1 1 ^^ ^ §" °CD ^ CO ! C\J OJ 112 / / / / / / i£L. CO OD CO 1 LL. ;y ~n —J =D CD — > —D ^-H CD LL. ^ cc: o oo 115 116 85^ 84^ te^ EASTERN GULF CDAST SECCHI 82^ 81^ FIGURE 50 117 FIGURE 52 119 FIGURE 53 120 121 / / y tJD CXI UJ 4— - \ \ \ / / / Ln 1 Q_ un t-^ UJ oo LjJ 1 cc: LL. •zi "~^ _J ^D CD \ \ o CZ) o oo CN 123 FIGURE 57 124 FIGURE 58 125 FIGURE 59 126 127 <*>• 128 129 FIGURE 63 130 FIGURE 64 131 ^ 8^° 83° 82^ EASTERN GULF (tOAST CONVERTED 81^ FIGURE 65 132 0.07 \ 0.04 0.1 0.2 0 O.I 0.03 0 ;^",JClnfAMPA \ 2 J. 5 FIGURE 66 133 134 135 136 137 \ \ \ \ ' \ \WASHlNGTON r ^ 13\ \ 1 V I / V \ \ 17 V I \ > 9 \ 47 » ' ^ \r\ *''-» '"^ 1.3 \ 11 ^ r^ ^'J ^^2 \° (^r 1 ( \ V \ i ^ 1 -Kd=10 I NORTHWEST COAST \ \ \ % u N \ 19 ^ vT"^ Kd FEB-APR ^ \ 19 • 10 y'19 l ^ /27 24\ 10 5\ 1^ / \ 10 ^ / ^\ \ h pLUMBIAR ^^,.''*-^ \ \ ^ \ r^'^'^ ^.59 39 V V-v ^. 0 ^^ /> ^^ 22 53 2U\ 1 26 19 17 >1 "M"^ 46° J 29 \ / 5" \ f **• \ \ S » S 3S 29 1 1 ; .1 ( v_ _ , \i> - 33 ; T t 1 ki \ u. ks '. 32 0 ( \ ' \\ \ 1 ^OREGON FIGURE 71 t » 1 y * 116 1 / 1 16 ,1 1 1 M-'Kd=10 45° lie yl ^ -" ''(i 1 / » 1 / 126° 125° 2? / '9 / 1 124° 138 42: / 12 WASHINGTON NORTHWEST COAST Kd OCT- JAN 46 FIGURE 72 45! ^ \ > » \24 125° 139 126° 125° 36^30 25 20 / 14,^24'' 4,1 15 M2NN 1 it ^~ ^ / 5 1 I 207/ ^^ '/L / '° 16/^T / 25 37 iio/ Kd = 10 ^' /! 1 (la \ 56 20 15\ I 22 ! 1 44" ' ' >. iB__ "^ lap- • " - - " * ^ 1 / I / ) • 13/ 1 1 NORTHWEST COAST Kd MAY-SEP ; 26 '/ 136 // 1 ' / ! 3S/^ f // OREGC 5N 43" /-' t] '-> "J 90', 2&' ( ^ ^ \ FIGURE 73 • ' ^ 1 s / / I'e / y^ f ^ 1 r \ r 16 I 1 ^ \ \ I 1 ^\ i25 17) » ^ V 42° 1 * \ tja t i_a_JI _^ 140 126° 125'' 35; 12 ,''i5V ' / r\ ' r 1 f 1 / * \ 1 f 124' 1 \ / ' 1 / ^ 1 / / 1 f ^ r 1 / 26 24 18 j 1 * A4' • 1 15 . ' . NORTHWEST COAST i 7. Kd FEB -APR 1 :^ .^ 7 U. / / o / hp P / //T - / /J .' X / OREGC •N 43' r-' 1/ 1 ^ / 1 ' ^' / » / ( \ f \ FIGURE 74 - \ \ ^ ^^ M 1 ^ \ \ \ 1 \\ 1 ^ 1 1 ' \ 42^ 1 ' \ no / ^ - 141 126 a4 NORTHWEST COAST Kd OCT -JAN 43' 125' 31 / 15 14 IS 14 IS'./g K-d=10 FIGURE 75 ^AZ 142 143 144 145 146 85° 84° 183° 82° 81° \ easJtern gulf coast Kd APR-N1AY FIGURE 80 3d f 1 1 >. - »— X. I v. ^ 2d N ^* \ N \ \ % t * . V- X \ \ s 1 > •-» \ \ \ \ J r- TAMPA FLORIDA 2^ \ o 3 1 1 t 5X3 3 2 1 : 3\ 0 J^ IMIvir'M rf^SlrjBAY 2 / « « \ % V • % \ ^x \ 2I ■'.', Kd = 4-^ \l » 2\\\l / 6 \ 3\ 3 1. 2^ \ V « 1 \ \ . • 1 \ 1 1 ^ 2 r^ Jii ^^-'25 ""'*'v. 1 / * 9 1 * 1 - 1 F-LORrDA K^"^ * 1 1 1 1 1 ! 1 24 147 85° 84° 83° j82° EASTERN GULF COAST Kd JUN-SEP FIGURE 81 81° 30° • 2^' X \ '^' \ • - • 1 ) 1 / 2 y 3 r FLORIDA 28° \3 \ K 3 I ■ \ 5 * \ \ \ i ■^ 0 t'N TAMPA 4 Sin BAY ■ 27° \ 1 1 1 %^ 1 1 1 < 1 \ t 1 1 1 1 8 \ 1 t I - 1 f 2^ / / 1 t < . f 1 1 1 \ \ \ 1 \ \ Kd=4-^ \ « •T • X t t 1 '-'J 1 / , • \ 1 / 2 2 3 r' 2 3 V I * " \ FL'ORrpA'KF • s 24° • 148 85° 84° j83° 82° EASTERN GULF COAST iKd OCT -DEC 8f 1 • FIGURE Sf \ 3d ^ ■ ;:-■■■-• \ 1 \ -\ • 2d ^\' > - \ -LORIDA \\ \ 3 \ 1 J 28" , \ 5 1 ■' i 8 "A 8 S 1 SVjBAY ■'■■4 • 1 • Kd=4- 5\ '\ 3 \ O 27 1 • • I \ H r ■ 1 \ \13 \ 10 7 2 U 2^ ^ 1 1 1 ^\ 1 / 1 I 2^ 1 1 1 1 1 1 9 8 5 ' "^"^ f ' •' 1 I \ \ 1 % % N \ e i^ JS .-'-" ,.., /I I FL'ORipA.KE^ / 24 149 150 151 O _j Ll ^0 ro o ^y 103 .^ fVJ. ^ "* "*•" I)' .^ in CT m ^ •S LO sx p T^ g o 3 LlJ "9 r^ I— ^ Ll < 00 m (O OJ CM cn _-— -.; "v^ \ "^^ ^-^ oj' CO < col _I CVJ 152 LIST OF REFERENCES Alexander, J.E., et al . , BLM Contract No. 08550-CT5-30 , Baseline Monitoring Studies > Mississippi, Alabama, Florida, Outer Continental Shelf, 1975-1976, Vol. IV, 28 June 1977. 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Zaneveld, J.R., et al . , Oregon State University, School of Oceanography Ref. 78-13, Optical Hydrographic and Chemical Observations in the Monterey Bay Area During May and September 1977, August 1978. 158 INITIAL DISTRIBUTION LIST No. Copies Defense Documentation Center 2 Cameron Station Alexandria, VA 22314 Library, Code 0142 2 Naval Postgraduate School Monterey, CA 9 3940 Chairman, Code 68 3 Department of Oceanography Naval Postgraduate School Monterey, CA 9 3940 Dr. Stevens P. Tucker, Code 6 8Tx 5 Department of Oceanography Naval Postgraduate School Monterey, CA 93940 Director 1 Naval Oceanography Division (OP952) Navy Department Washington, DC 20 350 Office of Naval Research 1 Code 4 80 Naval Ocean Research and Development Activity NSTL Station Bay St. Louis, MS 39522 Dr. Robert E. Stevenson 1 Scientific Liaison Office, ONR Scripps Institution of Oceanography La Jolla, CA 92037 Commanding Officer 1 Fleet Numerical Weather Central Monterey, CA 93940 Dr. Murray Brown 1 Bureau of Land Management, OSC Hale Boggs Fed. Bldg., Suite 841 500 Camp Street New Orleans, LA 70130 Mr. Gerald L. Shideler 1 U.S. Geological Survey P.O. Box 6732 Corpus Christi, TX 78411 159 Coirananding Officer Naval Environmental Prediction Research Facility Monterey, CA 9 3940 Commander Oceanographic Systems Pacific Box 1390 Pearl Harbor, Hawaii 96 86 0 Commanding Officer Naval Ocean Research and Development Activity NSTL Station Bay St. Louis, MS 39522 Commander Naval Oceanography Command NSTL Station Bay St. Louis, MS 39522 Commanding Officer Naval Oceanographic Office NSTL Station Bay St. Louis, MS 39522 Mr. Maxim F. van Norden Code 8412 U.S. Naval Oceanographic Office NSTL Station Bay St. Louis, MS 39522 Mr. John Shannon, Code 3012 Naval Air Development Center Warminster, PA 189 74 Mr. H. Krumboltz, Code 3010 Naval Air Development Center Warminster, PA 18974 Mr. Steven E. Litts, Code HYAI DMAHTC 6500 Brookes Lane Washington, DC 20315 Mr. David B. Enabnit National Oceanic and Atmospheric Administration National Ocean Survey Rockville, MD 20 852 Mr. Mike Cooper, Code 772 Naval Coastal Systems Lab Panama City, FL 32407 Mr. Richard M. Wargelin, Code 2000 U.S. Naval Oceanographic Office NSTL Station Bay St. Louis, MS 39522 160 Mr. Jim Hammock DMAHTC 6500 Brookes Lane Washington, DC 20315 Mr. Albert Pressman, Code 335 Naval Ocean Research and Development Activity NSTL Station Bay St. Louis, MS 39522 Library DMA H/TC 6500 Brookes Lane Washington, DC 20315 U.S. Naval Oceanographic Office Library, Code 410 3 NSTL Station Bay St. Louis, MS 39522 Mr. Jimmy C. Stribling, Code 8412 U.S. Naval Oceanographic Office NSTL Station Bay St. Louis, MS 39522 CDR Donald Nortrup, Code 6 8Nr Department of Oceanography Naval Postgraduate School Monterey, CA 9 3940 Mr. K. 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Henry Odum, III Environmental Data Service National Oceanographic Data Center Washington, DC 20235 Mr. Louis Hoelman, WH553 Environmental Protection Agency Washington, DC 20460 Mr. Andrew Bakun National Marine Fisheries Service c/o Fleet Numerical Weather Central Monterey, CA 9 3940 John Murdock, Code 8412 U.S. Naval Oceanographic Office NSTL Station Bay St. Louis, MS 39522 Dr. Hasong Pak School of Oceanography Oregon State University Corvallis, Oregon 97331 162 -1 C.1 186201 Thesis ^23 van Norden 26 StP as ^ ® ^ 00 32075 Thesis V23 c.l 186201 van Norden The transparency of selected U.^. coastal waters with applications to laser bathymetry. thesV23 The transparency of selected US. coasta 3 2768 002 05382 9 DUDLEY KNOX LIBRARY