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19830013439.Pdf General Disclaimer One or more of the Following Statements may affect this Document This document has been reproduced from the best copy furnished by the organizational source. It is being released in the interest of making available as much information as possible. This document may contain data, which exceeds the sheet parameters. It was furnished in this condition by the organizational source and is the best copy available. This document may contain tone-on-tone or color graphs, charts and/or pictures, which have been reproduced in black and white. This document is paginated as submitted by the original source. Portions of this document are not fully legible due to the historical nature of some of the material. However, it is the best reproduction available from the original submission. Produced by the NASA Center for Aerospace Information (CASI) JPL PU13LICATION, 83-5., ( NASA-CR-1701 lai j LINEAR RETRIEVAL^ AND N83-2 1710 GLOBAL MEASUREMENTS OF WIND SPEED -I ROM THE SEASAT SMMR (Jet Propulsion Lab.) 31 p A -- HC A03/MF A01 CSCL 04B Unclas G3/47 03186 r {I i a Linear Retrieval and =Global 111 Measurements, of 11l111ind Speed .-from - , the ' Seasat S ILL IVY R { , l w Prem Chand ,,Pandey < K ,e s ,Ma^chR 1, 1988i National Aeronautio$ and Space Administration fit+ .. , Jet 'Propulsion Laboratory, ,i California Institute of Technology i Pasadena,-California < 1 ^ t 1 '` x yy 5 Y ^ 1 t . ^ :.. i _,x . / ,{w-J ^ 1....,. 4' .t .. ^ ",. :^ ,' '^d: .. .•.:: .^fi^.r.-. i a t: +et a', 3^^`_* '^.a - JPL PUBLICATION 83-5 Linear Retrieval and Global Measurements of Wind Speed from the Seasat S M M R Prern Chand Pandey March 1, 1983 NASA National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California The research described in this publication was carried out by the Jet Propulsion Laboratory, California Institute of Technology, and was sponsored jointly by the National Academy of Sciences and the National Aeronautics and Space Administration. Contents 1. Introduction ----------------------------------------------------- 1 2. Seasat Sca aerometer and altimeter ---------------------- ,---------- 2 3. Radiative transfer equation ----------------- ,- ------------------- 3 4. Retrieval algorithm ----------------------------------------------- 4 5. Bias determination using Chester's algorithm and Seasat-A Scatterometer (SASS) data -------------------- -------- -- ------- 6 6. Wind speed comparison with JASIN surface measurements ------------ 9 6.1 Surface observations -------------------------------------- 9 6.2 Conversion of recorded wind speed to 19.5 m neutral stability wind speed ------------------------------ 11 6.3 SMMR wind speed versus surface wind speed ----------------- 13 7. Grid point interpolation of satellite-derived wind fields for map production ----------------------------------------------- 13 8. Discussion and intercomparison of SMMR-WS, SASS-WS and ALT-WS global maps ------------------------------------------------ 17 9. Conclusions and remarks ------------------------------------------ 23 References-------------------------------------------------------------- 25 Tables I. Results of the leaps and bounds technique in selecting the best subsets of two to five SMMR channels for wind speed determination ---------------- ----------------------- ------ 7 2. Regression coefficients of some of the subsets given in Table 1 -- 8 3. Determination of bias from comparison with Chester's algorithm and SASS measurements of WS from Rev. No. 1120 ------------------- 10 4. Results of comparison of wind speed derived from different subsets against in situ neutral density wind speed in JASIN area - 14 PRECEDING PAGE BLANK NOT (FILMED i i i Contents (Contd.) Figures I. The JASIN experiment platform distribution ----------------------- 12 2. SMMR wind speed comparisons with JASIN surface measurements ------ 15 3. Global distribution of Seasat SMMR wind speed for the period July 7 - August 6, 1978 ------------------------------------------ 18 4. Global distribution of Seasat SMMR wind speed for the period July 7 - Oct. 10, 1978 ----- ------------ - - --- _ - 19 5. Global distribution of Seasat-A Scatterometer (SASS) wind speed for the period July 11 Oct. 10, 1978 --------------------- 21 6. Global distribution of Seasat altimeter (ALT) wind speed for the period July 11 - Oct. 10, 1978 ------------------- ------------ 22 iv 4 Abstract Retrievals of wind speed (WS) from Seasat Scanning Multichannel Microwave Radiometer (SMMR) have been performed using a two-step statistical technique. Nine subsets of two to five SMMR channels were examined for wind speed retrieval. These subsets were derived by using a leaps and bounds pro- cedure based on the R 2 coefficient of determination selection criteria to a statistical data base of brightness temperatures and geophysical parameters. Analysis of Monsoon Experiment (MONEX'79) and ocean station PAPA (504, 145°W) data showed a strong correlation (correlation coefficient N .77) between sea surface temperature and water vapor. This .relation was used in generating the statistical data base. A comparison of SMMR-WS with Joint Air-Sea Interaction Experiment (JASIN) surface wind speed shows an rms accuracy of —1.5 m/sec for a wind speed range of 3-16 m/sec. The retrieval accuracy of WS from different subsets agreed to within about 10 percent. Global maps of WS have been produced for one and three month periods. These maps show the global distribution of winds in well organized belts. The tropical easterlies are found to be of comparable strength in both hemispheres whereas westerlies of the southern hemisphere are stronger than those of the northern hemisphere. These maps reveal the previously known features and con- form to the prevailing ideas. A comparison of global maps of wind speed from SMMR, Seasat-A Scatterometer (SASS) and Altimeter (ALT) shows some similarities and discrepancies which need further investigation. v all s. 1. Introduction The Scanning Multichannel Microwave Radiometer (SMMR) aboard Seasat and Nimbus-7 satellites was intended to monitor global sea surface temperature, wind speed, water vapor, liquid water content and rain fall rate over oceanic regions. The SMMR measured microwave radiation at 6.6, 10,69, 18.0, 21.0 and 37.0 GHz and in both horizontal and vertical polarizations from which surface G and atmospheric parameters are inferred. A recent review article by Njoku rF [1982] describes the passive microwave remote sensing of the ocean and atmos- pheric parameters from space-borne radiometers. Recently we (Pandey and Kakar, 1983) have developed a linear two-step statistical technique to retrieve geophysical parameters from microwave radio metric data. The technique has already been used to retrieve sea surface temperature [Pandey and Kniffen, 1982] and precipitable water [Pandey, 19821 from Seasat SMMR data. The purpose of this document is to retrieve ocean surface wind speed from SMMR measurements using the previously developed statistical technique of the authors and compare the SMMR retrieved wind speed with in situ observation during Joint Air-Sea Interaction (JASIN) experiment. Comparison with Chester's [Lipes and Born, 1981] geophysical algorithm which has been used at Jet Propulsion Laboratory for processing Seasat SMMR data will also be made. Seasat also carried a scatterometer called Seasat-A Satellite Scatterometer (SASS) and an altimeter (ALT) for meas-il ing wind speed. SASS also measured wind direction. An intercomparison of wind speed derived from both active and passive sensors aboard Seasat will prcvide confidence to users of the data about the quality of the retrieved parameter. At present there are only a few thousand (2000) widely scattered ship reports per day and even fewer data buoy measurements of wind speed over the vast oceanic regions. Seasat provided -1- ORIGINAL PAGE 13 OF POOR QUALITY several thousands wind vectors per day which have been used in a numerical experiment at Goddard Laboratory for Atmospheric Sciences [Gower, 19811 to test the utility of Seasat wind vector in improving weather forecasting. These experiments have shown a strong impact of Seasat data in improving short range forecasts (2-3 day). The Indian monsoon is one of the most important wind patterns in the world. The ability to measure winds over the Indian ocean (including the Arabian sea extending up to Somali coast, and the 'Bay of Bengal) and to calculate the ocean circulation will greatly enhance our under- standing of V`!e monsoon. Calculations of the momentum, heat and water vapor fluxes across the ocean-atmosphere system also require an accurate knowledge of surface wind speed. More confidence in synoptic weather analysis is gained when wind field is available as an additional input. All these studies demon- strate the usefulness of wind measurements for meteorolo g ical and oceanographic purposes. National Oceanic Satellite System (NOSS) or any other similar system if implemented will provide these data in real time and perhaps with better capability. 2. Seasat Scatterometer and altimeter The Seasat SMMR instruments have been described in detail by Njoku et al. (1980). A brief description and characteristics of scatterometer and altimeter r relevant to the intercomparison and interpretation of data will be given here. For more detail, the reader is referred to several articles published in Journal of Geophysical Research, Seasat special issue,[Bernstein, 1982]. The Seasat-A Satellite Scatterometer (SASS) operated
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