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2nd International Planning Workshop on GPM

Global Precipitation Measurement (GPM) Mission An International Partnership & Precipitation Satellite Constellation for Research on Global Water & Energy Cycle. Overview of NASA’s Science Agenda for GPM Mission. 2nd International Planning Workshop on GPM

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2nd International Planning Workshop on GPM

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  1. Global Precipitation Measurement (GPM) Mission An International Partnership & Precipitation Satellite Constellation for Research on Global Water & Energy Cycle Overview of NASA’s Science Agenda for GPM Mission • 2nd International Planning Workshop on GPM • Eric A. Smith; NASA/Goddard Space Flight Center, Greenbelt, MD 20771 [tel: 301-286-5770; fax: 301-286-1626;easmith@pop900.gsfc.nasa.gov;http://gpmscience.gsfc.nasa.gov] • May 20-22, 2002; Shinagawa Prince Hotel, Tokyo, Japan

  2. Water and Life Hydrologic Management • Water and climate • Water and food • Water quality and human health ENSO-Precipitation Links • Water and environment • Water and conflict

  3. OBJECTIVES  Understand Horizontal & Vertical Structure of Rainfall, its Microphysical Nature, & Associated Latent Heating  Train & Calibrate Algorithms for Constellation Radiometers OBJECTIVES  Provide Sufficient Global Sampling to Reduce Uncertainty in Short-Term Rainfall Accumulations  Extend Scientific and Societal Applications GPM Reference Concept • Core Satellite • TRMM-Like S/C, NASA • H2-A Launch, NASDA • Non-Sun Synchronous Orbit • ~ 65° Inclination • ~450 km Altitude • Dual Frequency Radar, NASDA • Ku & Ka Bands • ~ 4 km Horizontal Resolution • ~250 m Vertical Resolution • Multifrequency Radiometer, NASA • 10.7, 19, 22, 37, 85, 150 GHz V&H • Constellation Satellites • Dedicated Small or Pre-existing Experimental & Operational Satellites with PMW Radiometers • Revisit Time • 3-Hour goal • Sun- & Non-Sun- Synch Polar Orbits • ~600 km Altitude • Global Precipitation Processing Center • Produces Global Precipitation Data Product Streams Defined by GPM Partners • Precipitation Validation Sites • Selected & Globally Distributed Ground- Based Supersites (Multiparameter radar, up looking radiometer/radar/profiler, raingages, & disdrometers) • Dense Regional Raingage Networks

  4. GPM Mission is Being Formulated within Context of Global Water & Energy Cycle with Foremost Science Goals Focusing On • Improved Climate Predictions:through progress in quantifying trends & space-time variations of rainfall & associated error bars in conjunction with improvements in achieving water budget closure from low to high latitudes -- plus focused GCM research on advanced understanding of relationship between rain microphysics/latent heating/DSD properties & climate variations as mediated by accompanying accelerations of both atmospheric & surface branches of global water cycle. • Improved Weather Predictions:through accurate, precise, frequent & globally distributed measurements of instantaneous rainrate & latent heat release -- plus focused research on more advanced NWP techniques in satellite precipitation assimilation & error characterization of precipitation retrievals. • Improved Hydrological Predictions:through frequent sampling & complete continental coverage of high resolution precipitation measurements including snowfall -- plus focused research on more innovative designs in hydrometeorological modeling emphasizing hazardous flood forecasting, seasonal draught-flood outlooks, & fresh water resources prediction.

  5. Status of Working Group Workshops & Preparation of Chapters for GPM Draft Science Implementation Plan Name of Group Leads WS Chap 1. Water Cycle E. Wood TBDyes 2. Climate Diagnostics P. Robertson yesyes 3. Modeling & Data Assimilation A. Hou yesyes 4. Hydrometeorology H. Cooper yes (vir)yes 5. Ocean Fluxes & Marine ABL V. Mehta yes (vir)yes 6. Coupled Cloud-Radiation Modeling G. Tripoli / W. Tao Jul '02yes 7a. Core Satellite Reference Algorithm Z. Haddad yesyes 7b. Rain Radiometer Parametric Algorithm C. Kummerow yesyes 7c. Cross Calibration & Blended Algorithms E. Smith yesyes 8. Ground Validation & Field Experiments S. Yuter / R. Houze yesyes 9. Forecast Apps, TV, Education, & Outreach M. Shepherd yesyes 10. Boiler Plate A. Mehta / M. Shepherd / E. SmithN/A 90%

  6. Document Status [http://gpmscience.gsfc.nasa.gov] NASA GPM Report Series (Smith & Adams, eds)  Summary of 1st GPM Partners Planning Workshop Shepherd, Mehta, Smith printed  Benefits to Partnering with GPM Mission Stocker printed  Scientific Assessment of High-Frequency Liu & Flaming in press Radiometer Channels on GPM Core Satellite for Warm and Light Rain plus Snow Measurement  Scientific Assessment of Cross-Track STAR Wilheit & Everett in press Radiometer Flown Bore-Sighted with Dual-Frequency Radar on GPM Core Satellite  Potential Tropical Open Ocean Precipitation Adkins & Yuter printed Validation Sites 6 Description of Global Precipitation Measurement Smith, Mehta, Shepherd in review (GPM) Mission 7 Bridging from TRMM to GPM to 3-Hourly Shepherd & Smith printed Precipitation Estimates 8 Description of GPM Project Adams et al in review 9 GPM Core Satellite Trade Space Analysis Everett et al draft form Additional Publications 1. The Global Precipitation Measurement (GPM) Mission Smith et al Plinius 3 2. Potential Applications of LRR-STAR Technology Smith et al ESTC-2 for GPM Mission 3 Draft GPM Science Implementation Plan (SIP) Smith (editor) very rough draft

  7. Currently Conceived Constellation Architecture Reference NPOESS-1 GPM Core (CMIS) N-GPM b DMSP-F18/20 (NPMR) (GMI / DPR) (SSMIS) E-GPM NPOESS-2 DMSP-F19 TRMM (EPMR / NPR) (CMIS) Co-Op Drone Partners Optimization and Compromise Potential New Drones/Partners (SSMIS) DMSP-F16 AQUA FY-3 NPOESS-Lite DMSP-F17 ADEOS-II (CMIS) NPOESS-3 (CPMR) (CMIS) MEGHA TROPIQUES GCOM-B1 (MADRAS) (AMSR-FO) TBD

  8. GPM: Constellation Mission of Opportunity & Good Citizenship SatelliteMain PurposeValue to GPM Mission 1. GPM Core GPM rain reference calibration, rain physics, [NASA/NASDA] system tropical-midlatitude sampling 2 & 3. DMSP US: NOAA/DOD met-ops & res global sampling [IPO] 4. NPOESS-Lite US: NOAA/DOD met-ops & res global sampling [IPO] 5. GCOM-B1 Japan: environ/hydro res global sampling [NASDA] & JMA met-ops 6. E-GPM EU: cold seasons/flash flood/data-assim res rain physics, frozen [ESA (ASI/CNES/EC)] & EU met-opsprecip, global sampling 7. N-GPM US: MW radiometer technology testbed global sampling [NASA] 8. Megha Tropiques India/France: IO monsoon res tropical sampling [ISRO/CNES] & IMD met-ops 9. FY-3 China: CMA met-ops & res global sampling [CSM]

  9. Improving Precipitation Retrievals Cloud Macrophysical & Microphysical Fundamentals Determination of: drop size distribution [DSD(r)], mass mixing ratio [q(z)hydro(r)], rain mass flux [Fr(z)], fall velocity [w(z)hydro(r) ], & latent heating [LH(z) ] q(z)hydro(r) = sw (4/3pr3) DSD(r) w(z)hydro(r) = GFO [q(z)hydro(r)] Fr(z) = ∫ q(z)hydro(r) w(z)hydro(r) dr LH(z) = C [∂ Fr(z)/∂z] RR (z) = Fr(z) / sw RFsur = RR(zsur) ∑Dt Implementation of Fully Modular OPEN ACCESS Facility Algorithms Accompanied by COMPREHENSIVE TESTING Capability within WPDC

  10. TRMM & GPM Rainrate Retrieval Simulations Under Varying Mean Adj Drop Diameter Profiles [ simulations based on Monte Carlo proliferation of Hurricane Bonnie observations ] TRMM Single-Frequency Algorithm (bias due to unretrievable DSD variability) GPM Dual-Frequency Algorithm (near-zero bias & reduced scatter in mid-range) R e t r i e v e d R (mm hr-1) Actual R (mm hr-1) Actual R (mm hr-1) Standard Deviation of R (%) as Function of R in mm hr-1) TRMM with R approximately log-normal then sR proportional to R exact variability depends on DSD variability in altitude GPM Percent ~1.5 mm hr-1 ~12.5 mm hr-1

  11. x-z cross-section of Snowat 89.0 & 157.0 GHz Precipitating Snow 8 6 4 2 0 89 GHz z-axis (km) 60 80 100 120 140 160 180 8 6 4 2 0 157 GHz z-axis (km) 60 80 100 120 140 160 180 x-axis (km)

  12. Validation Expectations from Research &Operations End Users Validation should be treated as important as retrieval because improved prediction depends on it. Error characterization of satellite precipitation retrievals is needed to support: (a) Algorithm Improvement -- for reducing bias & precision errors in retrieved precipitation estimates; (b) Climate Diagnostic Analysis -- for assessing physical significance of trends/variations in observed precipitation time series; (c) Data Assimilation -- for improving climate reanalyses, numerical weather prediction, & hydrometeorological forecasting. (d) Validation Research -- for advancing validation techniques, validation measuring systems, & space instrumentation.

  13. Mid-Lat Continental Tropical Continental Tropical Oceanic Extratropical Baroclinic GPM Validation Strategy I. Basic Rainfall Validation  Raingauges/Radars new/existing gauge networks new/existing radar networks Research Quality Data Confidence sanity checks II. GPM Supersites  Basic Rainfall Validation hi-lo res gauge/disdrometer networks polarametric Radar system  Accurate Physical Validation scientists & technicians staff data acquisition & computer facility meteorological sensor system upfacing multifreq radiometer system Do/DSD variability/vertical structure convective/stratiform partitioning GPM Satellite Data Streams Continuous Synthesis  error variances  precip trends Calibration Algorithm Improvements Supersite Products III. GPM Field Campaigns  GPM Supersites cloud/ precip/radiation/dynamics processes  GPM Alg Problem/Bias Regions targeted to specific problems FC Data Research  cloud macrophysics  cloud microphysics  cloud-radiation modeling High Latitude Snow

  14. Is Water Cycle Accelerating?

  15. Impact of TMI Rain Assimilationon Tropical Cyclone Dynamics Horizontal & Vertical Winds in Tropical Cyclone Bonnie ECMWF J.-F. Mahfouf

  16. Example for Weather Prediction Cloud Resolving Model Simulations from UW-NMS for Establishing Cloud-Radiation Relationships Lake-Effects Roll Convection Explicit Convection in Hurricane Bonnie Middle-Latitude Cyclone Supercell Thunderstorm Alps Orographic-Convective Storm

  17. brown trajectories: > 2.0 km precipitation feed green trajectories: < 1.5 km precipitation feed Barrier Convergence Zone ∑ surface flow convergence set up off-shore ∑ due to flow normal to high alps terrain ∑ flow surge lifted over convergence zone off-shore (335 qe surface) Better Flood Predictions: CRM Simulation & Microphysical Analysis of Three (3) Late Season Mediterranean Floods Elevated Mixed Layer 3 km MSL Brunt Vaisala Frequency Simulation of Low-Level Flows within Tyrrhenian, Ligurian, Ionian, & Adriatic Seas white (surface) -- orange (1.5 km) Amplifying Mesoscale Storms Arising within Mobile Westerly Disturbances under Control of Fixed Geography & Orography 35/50 m s-1 jet cores; 5 km MSL isobars (2 mb); surface temperature Surging EML ==> Inflow Cross-Section Surface qe (shaded) Stable Brunt-Vaisalla Frequency (dark shading) 427 mm Piemonte - 2000 Friuli - 1998 Genova - 1992

  18. Mean SST and Anomalies [ , QD, QD ] Anomaly [ Satellite ] [ NCEP ] Comparison of Satellite [QD] Anomalies to SST Anomalies

  19. Towards a GPM Community Ground Validation Project 1. Black dot on globe represents "Anywhere" -- U.S. or World. GPM constellation members provide: ** Rainfall amount (time, lat, lon) ** Community rain gauge networks, i.e., CRGNs (e.g., GLOBE, Farming, TV, School networks) or backyard recreational gauges) provide: ** Rainfall amount (time, lat, lon) ** CRGNs-potential independent validator of GPM-retrieved pixel values. • 3. Then question is, does: • GPM rainfall (time, lat, lon) = CRGN rainfall (time, lat, lon) ? • Project Enables: • broader science validation • public involvement in meaningful science research • formal & informal education activities & resources 2. CRGN validation procedure Members of CRGNs can access World Precipitation Data System (WPDS) via password protected internet portal and enter independent rain gauge measurements.

  20. SSM/I Era TRMM Era EOS or GPM Precursor Era GPM Era

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