1. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 1 Use of GOES, SSM/I, TRMM Satellite Measurements for Estimating Water Budget Variations in Gulf of Mexico -- Caribbean Sea Basins E.A. Smith (NASA/GSFC -- Greenbelt, MD) & P. Santos (NOAA/NWS -- Miami, FL) Global Precipitation Measurement (GPM) Mission An International Partnership & Precipitation Satellite Constellation for Research on Global Water & Energy Cycle The 2nd TRMM International Science Conference Eric A. Smith; NASA/Goddard Space Flight Center, Greenbelt, MD 20771 [tel: 301-286-5770; eric.a.smith@nasa.gov; fax: 301-286-1626; http://gpmscience.gsfc.nasa.gov] 6-10 September 2004; Nara, JAPAN

2. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 2 Motivation & Background  Water cycle and climate research  Limited success due to lack of global data networks -- particularly over world oceans  Satellite global networks  Several research programs designed to develop comprehensive datasets of atmospheric processes in order to gain better understanding of climate and its variability  GCRP (TRMM)  GEWEX (GPM)  But rainfall is not only component of atmospheric water cycle today recognized as foremost control on Earth’s climate  Therefore, understanding of water budget processes, their interplay and natural variability would be a valuable contribution From this perspective, and examining problem first raised by Peixöto (1973) and put in climatic context by Peixöto and Oort (1992) -- main goal of research is: “to determine how water balance is achieved for oceanic basin at regional- seasonal scales, focusing on degree to which water vapor and cloud condensate storage terms contribute to water balance within convective ocean regime” Specifically, variability of atmospheric water budget of Gulf of Mexico – Caribbean Sea basin is investigated for six sample months over 16-month period, consisting of: Oct’97, Jan’98, Apr’98, Jul’98, Oct’98, and Jan’99.

3. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 3 Past Research 1958 - International Geophysical Year. Global Studies: Starr et al. (1958, 1969), Peixöto (1970, 1972), Starr and Peixöto (1971), Peixöto et al. (1976, 1978), Peixöto and Oort (1983), & Chen and Pfaendtner (1993). Studied elements of atmospheric water budget such as PW, qV,, and compared these to independent estimates of E - P. Zonal and meridional components of qV. In terms of yearly means, observed PW maintained by qV with E - P > 0 across subtropical belts and < 0 across the ITCZ and subpolar lows. Maximum water vapor transport in PBL. Standing eddies account for most of zonal transport except in mid-latitudes where transient eddies play greater role. Transient eddies principal mechanism responsible for meridional transport of water vapor in mid- latitudes while Hadley cell is main mechanism across tropics. Regional Studies: Benton and Estoque (1954), Hastenrath (1966), Rasmusson (1966a-b, 1967, 1968, 1971), Etter (1983), Etter et al. (1987), Yoo and Carton (1990), and Rabin et al. (1993). Monthly/Seasonal Scales: Convergence of qV related to P distribution. Basins transport easterly and southerly in summer -- during winter, easterly across southern Caribbean and westerly across northern Gulf. Southerly from SE Caribbean to northerly across northern Gulf. E - P > 0 across Gulf during winter and summer but strongest during Winter. Caribbean E - P > 0 throughout year but weaker than Gulf. Large diurnal variations of qV and based on twice a day radiosonde observations. Above normal P across eastern US eastern associated with >0 departures across Gulf and Caribbean. Daily Scale: Rasmusson: stated storage significant on daily scale but did not quantify;. Rabin et al. (1993) found storage term increases by factor of 3 or more following cold frontal passages across Gulf. In Summary: Local tendencies ignored -- therefore, complete analysis of hydrological cycle within context of atmospheric water balance equation has not yet been published.

4. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 4 Study Area & GOES/SSM-I/TRMM/ECMWF Coverage

5. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 5 Hypothesis/Scientific Objectives Hypothesis:  Local rate changes of storage of water vapor and cloud condensate within convectively active regions are significant and should be considered in space- time restricted water budget calculations. Thus, conventional time- averaged form of water balance equation used in previous studies, which consists of balance between E - P and may not retain its validity when budget calculations are obtained diurnally and/or regionally. Scientific Objectives:  Develop purely satellite-based retrieval methodology, based principally on multispectral measurements from GOES and SSM/I observations to calculate atmospheric water budget over Gulf of Mexico - Caribbean Sea basin, including retrieval of water vapor / cloud water contents and their time derivatives, as well as divergence of vertically integrated water vapor transport, surface rainfall, and surface evaporation.  Quantify uncertainty in convectively active ocean basin stemming from assumption that water vapor & cloud water storage terms are negligible insofar as atmospheric water balance at regional-seasonal scales.

6. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 6 Mathematical Framework Regional time-averaged form of atmospheric water balance equation given by: where:  PW is precipitable water ; LWP is cloud liquid water path  is water vapor plus cloud condensate storage term  are water vapor and liquid water mixing ratios  are horizontal water vapor transport & vertically-integrated horizontal water vapor transport  E, P are surface evaporation and precipitation  is divergence of vertically integrated horizontal water vapor transport

7. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 7 Climatic Regime During Study Period  Study period was influenced by strong El Niño that developed in spring of 1997 and lasted into late winter of 1997-98 -- followed by strong La Niña that developed in late spring/early summer 1998 and lasted through reminder of study period.  El Niño is characteristic of above normal cyclonic activity, and hence precipitation, across northern Gulf of Mexico during fall and winter seasons while Caribbean undergoes drier than normal summer conditions -- converse is true with La Niña.  Also, tropical storm activity is below normal during El Niño years and above normal during La Niña years across Atlantic.  1997 Atlantic season was below normal with no storms across Caribbean and only one across Gulf -- although not during study period.  1998 Atlantic season was above normal with 5 tropical storms affecting Gulf (during Aug and Sep) and intense category 5 hurricane (Mitch) moving across southwestern Caribbean during last 10 days of October.

8. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 8 Data Sets Budget methodology uses data from six sources:  GOES-8 Used to retrieve directly or indirectly P, PW, LWP, cloud cover, SST, Ta,,, and E  SSM/I Used to retrieve directly P, PW, LWP,, and  TRMM 2a12 V5 P retrievals for Determining P Uncertainty  ECMWF Gridded Global Analysis Data (2.5 deg resolution)  Upper Air Sounding Data  Buoy Data

9. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 9 Multi-Algorithm Water Budget Retrieval & Validation-Verification Methodology Algorithm Cross- Validation Algorithm Direct Validation Final Algorithm PW precipitable water LWP liquid water path P precipitation E evaporation 1. CldCov i. NESDIS-NRL 2. SST i. Legeckis & Zhu ii. NESDIS-LSST iii. NESDIS-NLSST iv. Schlüssel 3. U s i. Schlüssel ii. Bates iii. Clayson & Curry 4-5. T a & q s i. Clayson ii. Fairall 6. q a i. Schlüssel ii. Schulz MODEL Clayson & Curry (1996) Clayson et al. (1996) with GOES-SSM/I Inputs 1. Santos & Smith Sondes Combined GOES-SSM/I 1. Chesters 2. Crosson & Smith 3. Santos & Smith Methodology Verification GOES CldCov Combined GOES-SSM/I 1. Santos & Smith 1. Spencer 2. Adler 3. Ferraro 4. Olson 5. Smith TRMM Line Integral  Q from Sounding Data ECMWF  Q from Global Analyses  Q vapor divergence Residue Term 1. Alishouse 2. Greenwald 3. Lojou 4. Weng & Grody 1. Wentz 2. Greenwald 3. Lojou 4. Petty Sondes & Buoys GOES SSM/I Combined GOES-SSM/I 1. Grose & Smith 2. Turk 3. Santos & Smith

10. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 10 Definition of Contribution to Total Water Budget (TWB)

11. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 11 Calculation of Time-Dependent Water Budget at Various Scales Retrievals are made on GOES-8 2 x 4 km grid and averaged to 0.25 x 0.25 degree grid for water budget analysis. Spatial-temporal characteristics of regional water budget are mainly analyzed on two scales: 1. regional fully-averaged monthly scale 2. regional diurnally-averaged monthly scale Noise reduction:   E = 1.9 10 -4 kg m -2 s -1   P = 3.7 “      /  t = 4.1 “     L  P/  t = 0.2 “ where: 1  10 -4 kg m -2 s -1 = 0.36 mm hr -1

12. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 12 SSMI GOES / SSMI match TRMM GOES / TRMM match SSMI GOES / SSMI match TRMM GOES / TRMM match TRMM vs SSMI and GOES Rainrate (mm hr -1 )

13. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 13 E Model Sensitivity Analysis

14. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 14 Monthly Mean Budget Distribution Maps Oct’97Apr’98 Jan’98Jul’98

15. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 15 Monthly Mean Budget Distribution Maps Jan’99Oct’98

16. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 16 Methodology Verification (Line Integral)

17. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 17 Methodology Verification (ECMWF)

18. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 18 Methodology Verification (ECMWF)

19. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 19 Monthly Mean Budget Time Series

20. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 20 Monthly Mean Budget Time Series

21. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 21 “Termwise” Contribution to TWB

22. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 22 Comparisons to Previous Studies This Study

23. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 23 Fully-Averaged Monthly Framework    Q = (E - P) Ocean Atmosphere Vapor Transport to Surroundings Vapor-Condensate Storage P = 36% E = 50% ∂(PW + LWP)/∂t = 0%    Q = 14%

24. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 24 Diurnally-Averaged Monthly Budget Cycle (mass fluxes) & TWB Contributions Oct’97

25. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 25 Illustration of Diurnal Fluctuations

26. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 26 Diurnally-Averaged Monthly Framework P = 14%E = 22% ∂(PW + LWP)/∂t = 32%    Q = 32% Ocean Atmosphere Vapor Transport to Surroundings Vapor-Condensate Storage P

27. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 27 Summary and Detailed Conclusions Emphasis placed on regional-seasonal water balance storage processes. Satellite algorithm retrieval methodology. Regional Fully-Averaged Monthly Scale: Rain maximum in Winter-Spring across Gulf, Summer-Fall in Caribbean -- with divergence term compensating. Results reflect expected weather patterns associated with El Niño / La Niña conditions. E exhibits weak seasonal variability but overall larger winter versus summer. In fully-averaged monthly framework: Gulf: E main contributing term to TWB 80% of time. Caribbean: E and P main contributing terms 50% of time. Combined basins: P dominant process only during Oct’98 -- highlighting Mitch’s impact on regional budget. Study period means: E = 50%, P = 36 %, = 14%. Regional Diurnally-Averaged Monthly Scale: Balance between four terms: E, P, with divergence & storage revealing large amplitude diurnal oscillations, as noted earlier (qualitatively) by Rasmusson. Diurnal modulations largely driven by strong synoptic scale forcing mechanism. Diurnal TWB contributions:,,, &. Assumptions: LWP derived from daily mean SSM/I modulated by GOES-8 cloud cover and SSM/I daily mean wind speed used in water budget retrievals. Verification: Comparisons to line integral calculations (direct) & ECMWF global analyses (indirect) give guarded confidence in satellite retrievals when considering weather patterns. Hypothesis: True at diurnally-averaged monthly scale, confirming suspicions of Peixöto and Rasmusson. Objectives: Ignoring storages can lead to 30% error in estimating diurnally- averaged monthly water budget. Satellite approach is viable.

28. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 28 General Conclusions Fully-Averaged Monthly Scale Balance between and E - P, confirming findings of previous studies (e.g., E. Rasmusson) -- but through complete rendition of water budget -- not through simple balance assumption. Results agree with number of previous studies over Caribbean basin -- do NOT agree with single study over Gulf basin possibly due to climatic differences. Diurnally-Averaged Monthly Scale Balance between, E - P, and Storage. Budget mechanisms within both basins on this scale select synoptically-driven diurnal storage mode to achieve climatic adjustments. Results bear out Peixöto and Oort’s suspicions concerning role of storage.

29. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 29 Future Research Improvements to multi-algorithm retrieval methodology are possible as satellite technology improves, e.g., multifrequency rain radars and better sampling frequency by microwave radiometers, i.e., main promise of GPM. Better retrievals of various surface meteorological variables needed in ocean evaporation models. For example, T a would be better retrieved using advanced infrared interferometer technology -- to be deployed around mid- decade by NASA/NAVY GIFTS mission. Other improved retrieval products are becoming available on routine basis when considering scatterometer-retrieved surface winds, space radar- retrieved precipitation, and ever evolving constellation of microwave radiometer-bearing satellites. Satellite approach becomes even more compelling when lidar-measured wind profiles become available from space, so that in combination with satellite-retrieved water vapor mixing ratio profiles, divergence term can be retrieved independently. This circumvents need for residue calculations, as well as enabling comprehensive testing of how well actual water budget closure can be achieved. Essential point is to bring water budget analysis, budget closure, and scale resolution to degree of accuracy and precision, such that weather, climate, and hydrometeorological modelers are compelled to upgrade their model’s physics so as to reproduce important details in observed water cycle.

30. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 30 Satellite-based Water Budget of Gulf of Mexico & Caribbean Basins Design of Algorithm System Combined TRMM-SSM/I & GOES ECMWF Validation Gulf-Caribbean Basins & Upper Air/Buoy Validation Data Sites Study Area, GOES-SSM/I-TRMM Sectors, & ECMWF Grid Line Integral Validation  Q Uncertainty (%) vs Sample Count (N) Gulf Basin Jul’98 - 12Z Caribbean Basin GOES SSM/I

31. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 31 Satellite-based Water Budget of Gulf of Mexico & Caribbean Basins Design of Algorithm System Combined TRMM-SSM/I & GOES ECMWF Validation Gulf-Caribbean Basins & Upper Air/Buoy Validation Data Sites Study Area, GOES-SSM/I-TRMM Sectors, & ECMWF Grid Line Integral Validation  Q Uncertainty (%) vs Sample Count (N) Gulf Basin Jul’98 - 12Z Caribbean Basin GOES SSM/I

32. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 32 Backup Slides

33. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 33 Study Region

34. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 34 Surface Map valid Oct 24, 1998 at 00Z

35. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 35 SST, Ta, Us, & qa Algorithm Validation

36. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 36 E Response to Variations in U s

37. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 37 Methodology Verification (Line Integral)

38. http://gpmscience.gsfc.nasa.gov eric.a.smith@nasa.gov 38 Methodology Verification (Line Integral)