status and overview of ipwgof ipwg–related precipitation

Status and Overview of IPWG relatedof IPWG–related

Precipitation Data SetsPrecipitation Data Sets

Chris Kiddand many many others…and many, many others…

NASA WetNet: Tallahassee c.1989NASA WetNet: Tallahassee c.1989

IPWG#5, Hamburg, 11-15 October 2010

NASA WetNet PIP-1 Bristol c.1991NASA WetNet PIP 1 Bristol c.1991


GPCP AIP-3 Shinfield Park c.1993


IPWG#4 CMA Beijing 2008IPWG#4 CMA Beijing 2008


History of precipitation 19601959 Vanguard 2

1960 TIROS-1

observation capabilities1970

1966 ATS-1

1970 1974 SMS-1

1978 SMMR1980 1983 NOAA-8

1987 SSM/I

1990

1997 TRMM

1988 WetNet1990 PIP-11989 AIP-1

20002003 SSM/IS

2002 MSG

C

1998 AMSU1993 PIP-21996 PIP-3

1991 AIP-21994 AIP-3

2001 IPWG

20102010 Megha-Tropiques

2006 Cloudsat2001 IPWG2004 PEHRPP

2020

2013 GPM

2010 Megha Tropiques

2018 PPM


Meteorological Earth Observing SystemGOES-13

GOES-E(USA)75° W.

GOES-W135° W.

100° W.

850 km

ОMETEOSAT-9(EUMETSAT)

0° E. 35800 km

МЕТЕОR(RUSSIA)

METOP(EUMETSAT)

DMSP

GOES-9144°E

DMSP

DMSP(USA)

MTSAT(JAPAN)

140° E.

(USA)

FY-2METEOSAT-8

3.4° E.

FY-1(CHINA)NOAA

(USA)

METEOSAT-7

FY-2(CHINA)

105° E.

(USA)

METEOSAT 774° E.

ELECTRO(RUSSIA)

76° E.METEOSAT-6

67.5° E.

Observation availabilityy

Region Availability Cycle (current) Res.*Region Availability Cycle (current) Res.

Visible Since start of satellite era

Geostationary, 15/30 minsPolar orbiters, 6-hourly

250 m+, y

Infrared Shortly after start of Geostationary, 15/30 mins 1 km+satellite era~ calibrated since 1979

Polar orbiters, 6-hourly

Passive Microwave

Experimental 1972/1975Uncalibrated since 1978Calibrated since 1987

Polar orbiters, 6-hourly+ Low Earth orbiter (TMI)

4 km+

Active Microwave(radar)

13.8 GHz since 199794 GHz since 2006

Low Earth Orbiter (PR)Polar orbiter (Cloudsat)

4 km1.5 km

* Resolutions vary greatly with scan angle, frequency, sensor, etc.y g y g q y


Satellite retrieval of precipitationp pVisible (including near IR)

R fl t l d t ti ( i• Reflectance, cloud top properties (size, phase)

I f dInfrared• Thermal emission – cloud top

temperatures → height

Passive Microwave• Natural emissions from surface and• Natural emissions from surface and

precipitation (emission and scattering)

A ti MiActive Microwave• Backscatter from precipitation particles

Note: Observations are not direct measurements


Observations to Products

ClimatologyData inputs Resolutionsti /

Agriculture/crops

Obs

Re P

Visibletime/space

M thl / l Agriculture/cropsser

etri

rod

Infrared

Monthly/seasonalClimate resolution

Meteorologyvat

iev

duct

Passive MW

Hydrology

ion

als

ts

Active MWInstantaneous

ss Instantaneous

Full resolution

Model outputs


Vis/IR and microwave retrievalsVis/IR and microwave retrievalsMicrowave methodologiesVisible/IR methodologies

Visible: Albedo, thickness

nIR: Particle size/type

Emission from hydrometeors over radiometrically ‘cold’ backgrounds

S tt i b h d tthIR: Cloud top temperatures/height Scattering by hydrometeors over radiometrically ‘warm’ backgrounds

Visible/IR techniques Microwave techniquesEmpirical techniques:

f fThresholding of cloud-top

( ) Use of surface observations to calibrate microwave observationsPhysical techniques:

temperatures (cold clouds=rain)

Cold cloud durationPhysical techniques:Radiative Transfer Modelling of MW energy through the atmosphere. Baysian techniques use of a priori

Empirical calibration of thIRMulti-spectral analysis

Baysian techniques – use of a prioridata bases of hydrometeor profiles derived from Cloud Radiation Models.

Neural Networks


Vis/IR & microwave combined techniquesVis/IR & microwave combined techniquesVis/IR Microwave (active/passive)

☺ Rationale: Observations more directly related to hydrometeors

Rationale: Observation of cloud top properties (temperature/size) but indirect ☺

☺(temperature/size), but indirect

Observations: Frequent observations (30mins); Good

Observations: Infrequent observations (2/sat/day); Poor

☺☺

observations (30mins); Good spatial resolution (1-4 km)

observations (2/sat/day); Poor spatial resolution (5-25 km) ☺

Combine directness of MW observations with the resolution/frequency of IR observations

Calibration of Vis/IR-derived Advect microwave estimates f fproperties with microwave

observationswith information from IR

observations


PM-calibrated IR products

2015 2045 2215 2245 0945 10152145TIME

LEO

H HH H H H

O

M M M

GEO

ainf

all

timat

eR

aes

t

M = match between LEO+GEO observations H = GEO-only observationsJoe Turk NRL/JPL

Result: Improved rainfall estimates every 30 minutes


Advection/Morphing productsp g p12 May 2003MSG – SSMI

study

Wind vectors derived from MSG 15 minutes data(simple correlation match)

PMW estimates advected using MSG i d t 0745 0930(simple correlation match) MSG wind vectors: 0745-0930

Basis of ‘CMORPH’ and GSMaP techniquesuses forwards and backward propagation of PM rainfalluses forwards and backward propagation of PM rainfall


“Global” Estimates

All products have advantages and disadvantagesAll products have advantages and disadvantages


Satellite – gauge data sets

Algorithm Input data Space/time Areal coverage/ Update Latency Producer

Publicly available, quasi-operational, quasi-global, multi-sensor satellite-gauge precipitation estimates

g g

Algorithm Input data Space/time scales

Areal coverage/ start date

Update frequency

Latency Producer

GPCP Version 2.1 Satellite-Gauge (SG)

GPCP-OPI, gauge 1/79-6/87, 12/87 SSM/I-AGPI (IR), gauge, TOVS 7/87 4/05 except

2.5˚/monthly Global/1979 Monthly 3 months NASA/GSFC 613.1 (Adler & Huffman)

TOVS 7/87-4/05 except 12/87, AIRS 5/05-present

TRMM Plus Other Data (3B43 Version 6)

TCI-TMI, TCI-SSM/I, TCI-AMSR-E, TCI-AMSU, MW-VAR (IR), gauge

0.25°/monthly Global – 50°N-S/Jan 1998

Monthly 1 week NASA/GSFC PPS (Adler & Huffman)

CMAP OPI SSM/I GPI MSU 2 5˚/monthly Global/1979 Seasonal 3 months NOAA/NWS CPCCMAP OPI, SSM/I, GPI, MSU, gauge, model

2.5 /monthly Global/1979 Seasonal 3 months NOAA/NWS CPC (Xie)

GPCP pentad (Version 1.1)

OPI, SSM/I, GPI, MSU, gauge, GPCP monthly

2.5˚/5-day Global/1979 Seasonal 3 months NOAA/NWS CPC (Xie)

GPCP One-D D il

SSM/I-TMPI (IR), GPCP thl

1˚/daily Global – 50˚N-50˚S/O t b 1997

Monthly 3 months NASA/GSFC 613.1 (H ff )Degree Daily

(Version 1.1) monthly 50˚S/October 1997 (Huffman)

TRMM Plus Other Satellites (3B42 Version 6)

TCI-TMI, TCI-SSM/I, TCI-AMSR-E, TCI-AMSU, MW-VAR (IR), V.6 3B43

0.25°/3-hourly Global – 50°N-S/Jan 1998

Monthly 1 week NASA/GSFC PPS (Adler & Huffman)

f G O SS / / f / (?) O / S C CAfrican GPI, NOAA SSM/I, gauge 10 km/daily Africa/April 2000(?) Daily 6 hours NOAA/NWS CPC (Xie)

South Asian GPI, NOAA SSM/I, gauge 10 km/daily South Asia/April 2001

Daily 6 hours NOAA/NWS CPC (Xie)

CAMS/OPI CMAP-OPI, gauge 2.5˚/daily Global/1979 Monthly 6 hours NOAA/NWS CPC (Xie)

Mostly daily-monthly, 10km-250km

Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010

Multi-Satellite data setsPublicly available, quasi-operational, quasi-global, multi-satellite precipitation estimates



Update frequency

Latency Producer

TRMM Real-Time HQ (3B40RT)

TMI, TMI-SSM/I, TMI-AMSR-E, TMI-AMSU

0.25˚/3-hourly Global – 70˚N-S/ Feb. 2005

3 hours 9 hours NASA/GSFC PPS (Adler & Huffman)

TRMM Real-Time MW-VAR 0.25˚/hourly Global – 50˚N-S/ 1 hour 9 hours NASA/GSFC PPSTRMM Real Time VAR (3B41RT)

MW VAR 0.25 /hourly Global 50 N S/ Feb. 2005

1 hour 9 hours NASA/GSFC PPS (Adler & Huffman)

TRMM Real-Time HQVAR (3B42RT)

HQ, MW-VAR 0.25˚/3-hourly Global – 50˚N-S/ Feb. 2005

3 hours 9 hours NASA/GSFC PPS (Adler & Huffman)

NRL Real TIme SSM/I-cal PMM (IR) 0.25˚/hourly Global – 40˚N-S/ July 2000

Hourly 3 hours NRL Monterey (Turk)July 2000 (Turk)

TCI (3G68) PR, TMI 0.5˚/hourly

Global – 35°N-S/ Dec. 1997

Daily 4 days NASA/GSFC PPS (Haddad)

TOVS HIRS, MSU 1°/daily Global/1979-April 2005

Daily 1 month NASA/GSFC 610 (Susskind)

AIRS AIRS di tt i l th/ bit Gl b l/M 2002 D il 1 d NASA/GSFC 610AIRS AIRS sounding rettrievals swath/orbit segments

Global/May 2002 Daily 1 day NASA/GSFC 610 (Susskind)

CMORPH TMI, AMSR-E, SSM/I, AMSU, IR vectors

0.08°/30-min 50°N-S/2000 Daily 18 hours NOAA/CPC (Xie)

GSMaP-MWR TMI, AMSR-E, AMSR, 0.25°/hourly, 60°N-S/1998-2006 – – JAXA (Aonashi & SSM/I daily,montjhly Kubota)

GSMaP-MVK+ TMI, AMSR-E, AMSR, SSM/I, IR vectors

0.1°/hourly 60°N-S/2003-2006 – – JAXA (Ushio)

GSMaP-NRT TMI, AMSR-E, SSM/I, IR vectors

0.1°/hourly 60°N-S/Oct. 2007 1 hour 4 hours JAXA (Kachi & Kubota)

Mostly hourly-daily, 10km-100km


Single sensor products



Update frequency

Latency Producer

Publicly available, quasi-operational, quasi-global, single-sensor precipitation estimates

scales start date frequencyGoddard Profiling Algorithm (3G68)

TMI 0.5˚/hourly Global – 37°N-S/Dec. 1997

Daily 4 days NASA/GSFC PPS (Kummerow)

TRMM PR Precip (3G68)

PR 0.5˚/hourly Global – 37°N-S/Dec. 1997

Daily 4 days NASA/GSFC PPS (Iguchi)

GPROF SSM/I 0 5˚/ bit Gl b l 70°N S/ M thl 1 th C l St t U iGPROF SSM/I 0.5˚/orbit segments

Global – 70°N-S/ Jan. 1998

Monthly 1 month Colo. State Univ. (Kummerow)

RSS TMI,AMSR-E,SSM/I, QSCAT

pixel/orbit;1°/ 12-hr;0.5°/ pentad,monthly

Global Ocean – 82°N-S/1988-2007

pending pending HOAPS/Univ. of Hamburg, MPI (Klepp,Andersson)

HOAPS SSM/I 0.25°/1-,3-, 7-day;monthly

Global Ocean – 70°N-S/July 1987

1-,3-,7day; monthly

1 day, then 15 days

RSS (Wentz)

Chang-Chiu-WIlheit Statistical

TMI 5°/monthly Global ocean – 40°N-S/Jan. 1998

Monthly 1 week NASA/GSFC TSDIS (Chiu)

Chang-Chiu- SSM/I 2.5°/monthly Global ocean – Monthly 1 month Chinese U. of Hong gWilheit Statistical

y60°N-S/July 1987

y gKong (Chiu)

NESDIS/ FNMOC Scattering index

SSM/I 0.25˚/daily 1.0˚/pentad, mon 2.5˚/pentad, mon

Global/July 1987 Daily 6 hours NESDIS ORA (Ferraro)

NESDIS AMSU 0 25˚/daily Global/2000 Daily 4 hours NESDIS ORANESDIS High Frequency

AMSU 0.25 /daily1.0˚/pentad, mon 2.5˚/pentad, mon

Global/2000 Daily 4 hours NESDIS ORA (Weng and Ferraro)

GPI GEO-IR, LEO-IR in GEO gaps

2.5°/pentad Global – 40˚N-S 1986–March 1997

N/A N/A NOAA/NWS CPC (Xie)

GEO LEO IR 1°/3 hourly Global 40˚N S Monthly 1 Week NOAA/NWS CPC GEO-, LEO-IR 1°/3-hourly Global – 40 N-S Oct. 1996

Monthly 1 Week NOAA/NWS CPC (Xie)

OPI AVHRR 2.5˚/daily Global/1979 Daily 1 day NOAA/NWS CPC (Xie)


Gauge-based precipitation analyses

Publicly available, quasi-operational, quasi-global, gauge precipitation analyses

Gauge based precipitation analyses

y , q p , q g , g g p p yAlgorithm Input data Space/time

scales Areal coverage/ start date

Update frequency

Latency Producer

GPCC Gauge – Version 2 “Full

~60,000 gauges (climatology anomaly)

0.5°,1˚,2.5°/ monthly

Global/1901-2007 Occasional – DWD GPCC (Rudolf)Version 2 Full

Analysis” (climatology-anomaly) monthly (Rudolf)

GPCC Gauge – “Monitoring”

~8,000 gauges (climatology-anomaly)

1˚,2.5°/monthly Global/2007 Monthly 3 months DWD GPCC (Rudolf)

GHCN+CAMS Gauge

~3,800 gauges (SPHEREMAP)

2.5°/monthly Global/1979 Monthly 1 week NOAA/NWS CPC (Xie)Gauge (SPHEREMAP) (Xie)

CRU Gauge ~20,000 gauges (anomaly analysis)

0.5°/monthly Global/1901 Occasional – U. East Anglia (New and Viner)


EXAMPLES: GPCP V.2.1 SG climatology for 1979-2008

Note ITCZ, dry subtropical highs, mid-latitude storm tracksPrecipitation is concentrated around maritime continentp


Local linear trend in GPCP V.2.1 SG, 1979-2007 (29 years)

Regionally coherent trends do exist0 7 /d/d d li t d 29 l ll• >0.7 mm/d/decade linear trend over 29 years, locally

• the pattern appears to be driven by increases in ENSO frequency • data set inhomogeneities require careful examination


Model vs satelliteF

ECM

WF

2RT

3B4

3-hourly precipitation accumulations for 1 June 2007

Clear differences between identification (or definition) of precipitation


High resolution climatologiesHigh resolution climatologiesTRMM PR data: 11 years (1997→) at ~5 km resolution.

fall

all

e of

rain

f

Rainfall shows significant local al

rain

fa

curr

ence

gvariability linked with relief.

nnua

l tot

OccAn


IPWG Inter-comparison regionsp gNear real-time intercomparison of model & satellite estimates vs radar/gauge


Space-time dependency3-hour

Space-time dependencyAt full resolution the ‘accuracy’ of

day

At full resolution the accuracy of estimated rain is low; averaging over time and space improves the picture

5-day

Month

VAR vs. HQ (mm/hr) Feb. 2002 30°N-S

Fine-scale data allows users to decide the averaging strategy


Satellite error propagation in flood prediction700 700)

400

500

600

700

e (m

3 /s)

radar 1kmSREM2D KIDD 4km

400

500

600

700

e (m

3 /s)

radar 1kmSREM2D 3B42

1200

km

2

Anagnostou& Hossain:

100

200

300

Dis

char

ge

0

100

200

300

Dis

char

ge

higl

ione

(

0 20 40 60 80 100 120 140 1600

Time (hrs)

0 20 40 60 80 100 120 140 1600

Time (hrs)

Bac

ch

200

250 radar 1kmSREM2D KIDD 4km

200

250 radar 1kmSREM2D 3B42

2 )

50

100

150

Dis

char

ge (m

3 /s)

50

100

150

Dis

char

ge (m

3 /s)

a (1

16 k

m2

0 20 40 60 80 100 120 140 1600

Time (hrs)

0 20 40 60 80 100 120 140 160

0

Time (hrs)

Posi

naPMIR: 4km/30min 3B42RT: 1deg/3hr

High:57.9

0.5 km 1 km 2 km 4 km 8 km 16 kmLow:1.6A li ti l ti iti lApplications are resolution critical


High latitude precipitationHigh latitude precipitation

Validation instrumentation at high latitudes to observe and

measure precipitationmeasure precipitation


Sounding MW techniques

07:35183-WSLC

snowfall

183-WSL

snowfall

10:55 09:15 07:3509:15

183-WSLC

Use of AMSU 183GHz: capable of retrieving

NIMROD22 November 2008183-WSLC

10:55

p gprecipitation (rain and snow) over cold backgrounds 22 November 2008backgrounds

Vincenzo Levizanni, ISAC


Summaryy• Wide range of techniques and algorithms exist• Estimates available from monthly/2.5° to 15min/4km• Validation results show good correlations, although

seasonally dependent (poor cold-season performance)

F t h llFuture challenges• Future missions will advance satellite precipitation retrievals

through improved sensors and sampling

• Extensions of retrievals of precipitation at higher latitudes is p p gchallenging:- Light intensity, low-level, frozen precipitation- Surface background contamination- Monitoring changes critical for climate studies


status and overview of ipwgof ipwg–related precipitation

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