GPM May 21, 2002 Eric A. Smith [email protected] 1 2nd International Planning Workshop on GPM Eric A. Smith;

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GPM

May 21, 2002Eric A. Smith [email protected] http://gpmscience.gsfc.nasa.gov

2nd International Planning Workshop on GPMEric A. Smith; NASA/Goddard Space Flight Center, Greenbelt, MD 20771

[tel: 301-286-5770; fax: 301-286-1626; [email protected]; http://gpmscience.gsfc.nasa.gov]

May 20-22, 2002; Shinagawa Prince Hotel, Tokyo, Japan

Global Precipitation Measurement (GPM) Mission

An International Partnership &Precipitation Satellite Constellation

for Researchon Global Water & Energy Cycle

Overview of NASA’sScience Agenda for GPM Mission

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GPM


Reservoir

• Water and climateWater and climate

• Water and foodWater and food

• Water quality and human healthWater quality and human health

• Water and environmentWater and environment

• Water and conflictWater and conflict

Reservoir

ENSO-Precipitation Links

Hydrologic Management

Water and Life

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GPM


GPM Reference ConceptGPM 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

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

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

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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.

GPM Mission is Being Formulated within Context of Global Water & Energy Cycle

with Foremost Science Goals Focusing On

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Status of Working Group Workshops & Preparation of Chapters for GPM Draft Science Implementation Plan

Name of Group Leads WS Chap1. Water Cycle E. Wood TBD yes2. Climate Diagnostics P. Robertson yes yes3. Modeling & Data Assimilation A. Hou yes yes4. Hydrometeorology H. Cooper yes (vir) yes5. Ocean Fluxes & Marine ABL V. Mehta yes (vir) yes6. Coupled Cloud-Radiation Modeling G. Tripoli / W. Tao Jul '02 yes7a. Core Satellite Reference Algorithm Z. Haddad yes yes7b. Rain Radiometer Parametric Algorithm C. Kummerow yes yes7c. Cross Calibration & Blended Algorithms E. Smith yes yes8. Ground Validation & Field Experiments S. Yuter / R. Houze yes yes9. Forecast Apps, TV, Education, & Outreach M. Shepherd yes yes

10. Boiler Plate A. Mehta / M. Shepherd / E. Smith N/A 90%

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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 Satellitefor Warm and Light Rain plus Snow Measurement

Scientific Assessment of Cross-Track STAR Wilheit & Everett in pressRadiometer Flown Bore-Sighted with Dual-FrequencyRadar on GPM Core Satellite

Potential Tropical Open Ocean Precipitation Adkins & Yuter printedValidation 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 printedPrecipitation Estimates

8 Description of GPM Project Adams et al in review9 GPM Core Satellite Trade Space Analysis Everett et al draft

formAdditional Publications1. The Global Precipitation Measurement (GPM) Mission Smith et al Plinius 32. Potential Applications of LRR-STAR Technology Smith et al ESTC-2

for GPM Mission3 Draft GPM Science Implementation Plan (SIP) Smith (editor) very rough

draft

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TBD

b

(GMI / DPR)

GPM Core

DMSP-F18/20

DMSP-F19

GCOM-B1

(SSMIS)

(SSMIS)

(AMSR-FO)

N-GPM

E-GPM

FY-3

(EPMR / NPR)

Reference

Co-O

p D

ron

e P

art

ners

NPOESS-1

NPOESS-2

NPOESS-3

(CMIS)

(CMIS)

(CMIS)

MEGHATROPIQUES

(MADRAS)

Pote

ntia

l New

Dro

nes/P

artn

ers

Currently Conceived Constellation Architecture

NPOESS-Lite

(CMIS)

(CPMR)

(NPMR)

TRMM

AQUA

ADEOS-IIDMSP-F17

DMSP-F16

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GPM: Constellation Mission of Opportunity& Good Citizenship

Satellite Main Purpose Value to GPM Mission1. GPM Core GPM rain reference calibration, rain physics,

[NASA/NASDA] system tropical-midlatitude sampling2 & 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-ops6. E-GPM EU: cold seasons/flash flood/data-assim res rain physics, frozen[ESA (ASI/CNES/EC)] & EU met-ops precip, global sampling7. N-GPM US: MW radiometer technology testbed global sampling

[NASA]8. Megha Tropiques India/France: IO monsoon res tropical sampling

[ISRO/CNES] & IMD met-ops9. FY-3 China: CMA met-ops & res global sampling

[CSM]

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Improving Precipitation RetrievalsCloud 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) = w (4/3r3) 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) / w

RFsur = RR(zsur) ∑ t

Implementation of Fully Modular OPEN ACCESS Facility AlgorithmsAccompanied by COMPREHENSIVE TESTING Capability within WPDC

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TRMM & GPM Rainrate Retrieval Simulations UnderVarying 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)

exact variability depends on

DSD variabilityin altitude

Standard Deviation of R (%) as Function of R in mm hr-1)

with R approximately

log-normal thenR

proportional to R

GPM Dual-Frequency Algorithm(near-zero bias & reduced scatter in mid-range)

Actual R (mm hr-1)

Retrieved

R(mm hr-1)

Per

cen

t

Actual R (mm hr-1)

GPM

TRMM

~12.5 mm hr-1~1.5 mm hr-1

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x-z cross-section of Snowat 89.0 & 157.0 GHz

157 GHz

89 GHz

Precipitating Snow

x-axis (km)

60 80 100 120 140 160 180

60 80 100 120 140 160 180

8

6

4

2

0

z-ax

is (

km

)

8

6

4

2

0

z-ax

is (

km

)

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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.

Validation Expectations fromResearch &Operations End Users

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GPM Validation StrategyTropical Continental

Confidencesanity checks

GPMSatellite

DataStreams

ContinuousSynthesis

error variances precip trends

Calibration

Mid-Lat Continental

Tropical Oceanic

Extratropical Baroclinic

High Latitude Snow

ResearchQuality

Data

Algorith

mIm

provem

ents

Research cloud macrophysics cloud microphysics cloud-radiation modeling

FC Data

Supersite Products

II. GPM Supersites Basic Rainfall Validationhi-lo res gauge/disdrometer networkspolarametric Radar system

Accurate Physical Validationscientists & technicians staffdata acquisition & computer facilitymeteorological sensor systemupfacing multifreq radiometer systemDo/DSD variability/vertical structureconvective/stratiform partitioning

III. GPM Field Campaigns GPM Supersitescloud/ precip/radiation/dynamics processes GPM Alg Problem/Bias Regionstargeted to specific problems

I. Basic Rainfall Validation Raingauges/Radars new/existing gauge networks new/existing radar networks

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GPM

January 28 , 2002Eric A. Smith

Long term precipitation trendsobserved during 1900-1988

Is Water Cycle Accelerating?Is Water Cycle Accelerating?

Changes in globaltemperatures may imply

change in rate of water cycle.

Global Average Precip Index

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GPM

January 28 , 2002Eric A. Smith

Weather-resolvingDynamic Core

PhysicalParameterizationTRANSIENT FLUX FTRANSIENTWEATHERVARIABLES u

OBSERVED DATAASSIMILATION

COMPARE TOFIELD DATA

Dynamic Core

PhysicalParameterizationCLIMATE VARIABLES < u >MEAN FLUX < F >

State of Art Climate Model (CCM-3)

Next Generation Climate Model

Precipitation Prediction: Key Objective of Water Cycle Resear ch

NOW

GOAL

Is Water Cycle Accelerating?Is Water Cycle Accelerating?

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Horizontal & Vertical Winds in Tropical Cyclone Bonnie

Impact of TMI Rain Assimilationon Tropical Cyclone Dynamics

J.-F. MahfoufECMWF

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Example for Weather PredictionCloud Resolving Model Simulations from UW-NMS for

Establishing Cloud-Radiation Relationships

Middle-Latitude Cyclone

Supercell Thunderstorm

Alps Orographic-Convective Storm

Explicit Convection in Hurricane Bonnie

Lake-Effects Roll Convection

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GPM


QuickTime™ and aMicrosoft Video 1 decompressorare needed to see this picture.

Piemonte - 2000

Simulation ofLow-Level Flows

within Tyrrhenian, Ligurian, Ionian, &

Adriatic Seaswhite (surface) -- orange (1.5 km)

Friuli - 1998

Amplifying Mesoscale StormsArising 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


Inflow Cross-Section Surface e (shaded)Stable Brunt-Vaisalla Frequency (dark shading)

Genova - 1992



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 e surface)

SurgingEML ==>

Elevated Mixed Layer3 km MSL Brunt Vaisala Frequency

Better Flood Predictions:

CRM Simulation & Microphysical

Analysis of Three (3)Late Season

Mediterranean Floods

brown trajectories: > 2.0 km precipitation feed

green trajectories: < 1.5 km precipitation feed

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.427 mm

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[ , QD, QD ]

Anomaly[ Satellite ] [ NCEP ]

Comparison of Satellite [QD] Anomalies to SST AnomaliesMean SST and Anomalies

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Towards a GPM Community Towards a GPM Community Ground Validation ProjectGround Validation Project

1. Black dot on globe represents 1. Black dot on globe represents "Anywhere" -- U.S. or World."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.

22. . CRGN validation procedureCRGN validation procedure

Members of CRGNs can access World Precipitation Data System (WPDS) via password protected internet portal and enter independent rain gauge measurements.

3. Then question is, does:3. Then question is, does: GPM rainfall (time, lat, lon) = GPM rainfall (time, lat, lon) =

CRGN rainfall (time, lat, lon) ?CRGN rainfall (time, lat, lon) ?

Project Enables:Project Enables:

• broader science validation • public involvement in meaningful

science research• formal & informal education

activities & resources

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GPM


SSM/I Era

TRMM Era

EOS or GPM Precursor Era

GPM Era

Documents

GPM May 21, 2002 Eric A. Smith [email protected] 1 2nd International Planning Workshop on GPM Eric A. Smith;