Status and Overview
of IPWG–related
IPWG related
Precipitation Data Sets
Chris Kidd
…and
and many,
many many others
others…
NASA WetNet: Tallahassee c.1989
IPWG#5, Hamburg, 11-15 October 2010
NASA WetNet PIP-1
PIP 1 Bristol c.1991
IPWG#5, Hamburg, 11-15 October 2010
GPCP AIP-3 Shinfield Park c.1993
IPWG#5, Hamburg, 11-15 October 2010
IPWG#4 CMA Beijing 2008
IPWG#5, Hamburg, 11-15 October 2010
1960
1959 Vanguard 2
1960 TIROS-1
History of precipitation
observation capabilities
1966 ATS-1
1970
1974 SMS-1
1978 SMMR
1980
1983 NOAA-8
1987 SSM/I
1988 WetNet
1990
1989 AIP-1
1990 PIP-1
1991 AIP-2 1993 PIP-2
1994 AIP-3 1996 PIP-3
2001 IPWG
1997 TRMM
1998 AMSU
2000
2002 MSG
2003 SSM/IS
2006 C
Cloudsat
2004 PEHRPP
2010 Megha-Tropiques
Megha Tropiques
2010
2013 GPM
2018 PPM
IPWG#5, Hamburg, 11-15 October 2010
2020
Meteorological Earth Observing System
GOES-13
100° W.
GOES-E
(USA)
GOES-W
135° W.
75° W.
850 km
МЕТЕОR
О
(RUSSIA)
METEOSAT-9
(EUMETSAT)
METOP
(EUMETSAT)
0° E.
DMSP
(USA)
35800 km
GOES-9
144°E
DMSP
(USA)
MTSAT
(JAPAN)
140° E.
METEOSAT-8
FY-1
(CHINA)
NOAA
(USA)
3.4° E.
FY-2
(CHINA)
105° E.
METEOSAT-7
METEOSAT
7
74° E.
METEOSAT-6
ELECTRO
(RUSSIA)
67.5° E.
76° E.
Observation availability
y
Region
Availability
Cycle (current)
Res.*
Res.
Visible
Since start of satellite
era
Geostationary, 15/30 mins 250 m+
Polar orbiters,, 6-hourlyy
Infrared
Shortly after start of
satellite era
~ calibrated since 1979
Geostationary, 15/30 mins 1 km+
Polar orbiters, 6-hourly
Passive
Microwave
Experimental 1972/1975
Uncalibrated since 1978
Calibrated since 1987
Polar orbiters, 6-hourly
+ Low Earth orbiter (TMI)
4 km+
Low Earth Orbiter (PR)
Polar orbiter (Cloudsat)
4 km
1.5 km
Active Microwave 13.8 GHz since 1997
(radar)
94 GHz since 2006
* Resolutions vary
greatly
yg
y with scan angle,
g frequency,
q
y sensor, etc.
IPWG#5, Hamburg, 11-15 October 2010
Satellite retrieval of precipitation
p
p
Visible (including near IR)
• Reflectance,
R fl t
cloud
l d ttop properties
ti ((size,
i
phase)
IInfrared
f
d
• Thermal emission – cloud top
temperatures → height
Passive Microwave
• Natural emissions from surface and
precipitation (emission and scattering)
Active
A
ti Mi
Microwave
• Backscatter from precipitation particles
Note: Observations are not direct measurements
IPWG#5, Hamburg, 11-15 October 2010
Observations to Products
Resolutions
ti /
time/space
Data inputs
Visible
Infrared
Passive MW
Active MW
O
b
s
e
r
v
a
t
i
o
n
s
R
e
t
r
i
e
v
a
l
s
Monthly/seasonal
M
thl /
l
Climate resolution
Instantaneous
Full resolution
Model outputs
IPWG#5, Hamburg, 11-15 October 2010
Climatology
P
r
o
d
u
c
t
s
Agriculture/crops
Meteorology
Hydrology
Vis/IR and microwave retrievals
Visible/IR methodologies
Visible: Albedo, thickness
Microwave methodologies
Emission from hydrometeors over
radiometrically ‘cold’ backgrounds
nIR: Particle size/type
thIR: Cloud top temperatures/height
Scattering
S
tt i by
b h
hydrometeors
d
t
over
radiometrically ‘warm’ backgrounds
Visible/IR techniques
Microwave techniques
Thresholding of cloud-top
temperatures (cold
(
clouds=rain))
Empirical techniques:
Use off surface
f
observations to
calibrate microwave observations
Cold cloud duration
Empirical calibration of thIR
Multi-spectral analysis
Neural Networks
Physical techniques:
Radiative Transfer Modelling of MW
energy through the atmosphere.
Baysian techniques – use of a priori
data bases of hydrometeor profiles
derived from Cloud Radiation Models.
IPWG#5, Hamburg, 11-15 October 2010
Vis/IR & microwave combined techniques
Vis/IR
Rationale: Observation of
cloud top properties
(temperature/size) but indirect
(temperature/size),
Microwave (active/passive)
Rationale: Observations more
directly related to hydrometeors
Observations: Frequent
observations (30mins); Good
spatial resolution (1-4 km)
Observations: Infrequent
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
properties with microwave
observations
Advect microwave estimates
with information
f
from
f
IR
observations
IPWG#5, Hamburg, 11-15 October 2010
PM-calibrated IR products
TIME
2045
2145
2215
2245
0945
1015
LEO
2015
H
H
H
M
H
M
H
H
Ra
ainfall
esttimate
GEO
O
M
Joe Turk NRL/JPL
M = match between LEO+GEO observations
H = GEO-only observations
Result: Improved rainfall estimates every 30 minutes
IPWG#5, Hamburg, 11-15 October 2010
Advection/Morphing
p g products
p
12 May 2003
MSG – SSMI
study
Wind vectors derived from
MSG 15 minutes data
(simple correlation match)
PMW estimates advected using
MSG wind
0745-0930
i d vectors:
t
0745
0930
Basis of ‘CMORPH’ and GSMaP techniques
uses forwards and backward propagation of PM rainfall
IPWG#5, Hamburg, 11-15 October 2010
“Global” Estimates
All products have advantages and disadvantages
IPWG#5, Hamburg, 11-15 October 2010
Satellite – g
gauge
g data sets
Publicly available, quasi-operational, quasi-global, multi-sensor satellite-gauge precipitation estimates
Algorithm
Input data
GPCP Version 2.1
Satellite-Gauge
(SG)
GPCP-OPI, gauge 1/796/87, 12/87
SSM/I-AGPI (IR), gauge,
TOVS 7/87-4/05
7/87 4/05 except
12/87, AIRS 5/05-present
TCI-TMI, TCI-SSM/I, TCIAMSR-E, TCI-AMSU,
MW-VAR (IR), gauge
OPI SSM/I,
OPI,
SSM/I GPI,
GPI MSU,
MSU
gauge, model
OPI, SSM/I, GPI, MSU,
gauge, GPCP monthly
SSM/I-TMPI (IR), GPCP
monthly
thl
TRMM Plus Other
Data (3B43
Version 6)
CMAP
GPCP pentad
(Version 1.1)
GPCP OneD
Degree
D
Daily
il
(Version 1.1)
TRMM Plus Other
Satellites (3B42
Version 6)
African
f
Space/time
scales
2.5˚/monthly
Areal coverage/
start date
Global/1979
Update
frequency
Monthly
Latency
Producer
3 months
NASA/GSFC 613.1
(Adler & Huffman)
0.25°/monthly
Global – 50°N-S/Jan
1998
Monthly
1 week
NASA/GSFC PPS
(Adler & Huffman)
2 5˚/monthly
2.5
/monthly
Global/1979
Seasonal
3 months
2.5˚/5-day
Global/1979
Seasonal
3 months
1˚/daily
Global – 50˚N50˚S/O t b 1997
50˚S/October
Monthly
3 months
NOAA/NWS CPC
(Xie)
NOAA/NWS CPC
(Xie)
NASA/GSFC 613.1
(H ff
(Huffman)
)
TCI-TMI, TCI-SSM/I, TCIAMSR-E, TCI-AMSU,
MW-VAR (IR), V.6 3B43
G
GPI,
NOAA
O
SSM/I,
SS / gauge
0.25°/3-hourly
Global – 50°N-S/Jan
1998
Monthly
1 week
NASA/GSFC PPS
(Adler & Huffman)
10 km/daily
/
Africa/April
f
/
2000(?)
(?)
Daily
6 hours
South Asian
GPI, NOAA SSM/I, gauge
10 km/daily
Daily
6 hours
CAMS/OPI
CMAP-OPI, gauge
2.5˚/daily
South Asia/April
2001
Global/1979
Monthly
6 hours
NOAA/NWS
O /
S CPC
C C
(Xie)
NOAA/NWS CPC
(Xie)
NOAA/NWS CPC
(Xie)
Mostly daily-monthly, 10km-250km
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
Multi-Satellite data sets
Publicly available, quasi-operational, quasi-global, multi-satellite precipitation estimates
Algorithm
Input data
TRMM Real-Time
HQ (3B40RT)
TRMM Real
Real-Time
Time
VAR (3B41RT)
TRMM Real-Time
HQVAR (3B42RT)
NRL Real TIme
TMI, TMI-SSM/I, TMIAMSR-E, TMI-AMSU
MW-VAR
MW
VAR
HQ, MW-VAR
0.25˚/3-hourly
SSM/I-cal PMM (IR)
0.25˚/hourly
TCI (3G68)
PR, TMI
0.5˚/hourly
TOVS
HIRS, MSU
1°/daily
AIRS
AIRS sounding
di rettrievals
tt i
l
CMORPH
TMI, AMSR-E, SSM/I,
AMSU, IR vectors
TMI, AMSR-E, AMSR,
SSM/I
TMI, AMSR-E, AMSR,
SSM/I, IR vectors
TMI, AMSR-E, SSM/I, IR
vectors
swath/orbit
th/ bit
segments
0.08°/30-min
GSMaP-MWR
GSMaP-MVK+
GSMaP-NRT
Space/time
scales
0.25˚/3-hourly
0.25˚/hourly
0.25
/hourly
Areal coverage/
start date
Global – 70˚N-S/
Feb. 2005
Global – 50
50˚N-S/
N S/
Feb. 2005
Global – 50˚N-S/
Feb. 2005
Global – 40˚N-S/
July 2000
Global – 35°N-S/
Dec. 1997
Update
frequency
3 hours
Latency
Producer
9 hours
1 hour
9 hours
3 hours
9 hours
Hourly
3 hours
Daily
4 days
NASA/GSFC PPS
(Adler & Huffman)
NASA/GSFC PPS
(Adler & Huffman)
NASA/GSFC PPS
(Adler & Huffman)
NRL Monterey
(Turk)
NASA/GSFC PPS
(Haddad)
Global/1979-April
2005
Gl b l/M 2002
Global/May
Daily
1 month
D il
Daily
1d
day
50°N-S/2000
Daily
18 hours
0.25°/hourly,
daily,montjhly
0.1°/hourly
60°N-S/1998-2006
–
–
60°N-S/2003-2006
–
–
0.1°/hourly
60°N-S/Oct. 2007
1 hour
4 hours
NASA/GSFC 610
(Susskind)
NASA/GSFC 610
(Susskind)
NOAA/CPC (Xie)
JAXA (Aonashi &
Kubota)
JAXA (Ushio)
JAXA (Kachi &
Kubota)
Mostly hourly-daily, 10km-100km
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
Single sensor products
Publicly available, quasi-operational, quasi-global, single-sensor precipitation estimates
Algorithm
Input data
Space/time
scales
Areal coverage/
start date
Update
frequency
Latency
Producer
Goddard Profiling
Algorithm (3G68)
TRMM PR Precip
(3G68)
GPROF
TMI
0.5˚/hourly
Daily
4 days
PR
0.5˚/hourly
Daily
4 days
SSM/I
M thl
Monthly
1 month
th
RSS
TMI,AMSR-E,SSM/I,
QSCAT
pending
pending
HOAPS
SSM/I
TMI
1-,3-,7day;
monthly
Monthly
1 day, then
15 days
1 week
NASA/GSFC PPS
(Kummerow)
NASA/GSFC PPS
(Iguchi)
C l St
Colo.
State
t U
Univ.
i
(Kummerow)
HOAPS/Univ. of
Hamburg, MPI
(Klepp,Andersson)
RSS (Wentz)
Chang-ChiuWIlheit Statistical
Chang-Chiug
Wilheit Statistical
NESDIS/
FNMOC
Scattering index
NESDIS
High Frequency
0.5˚/orbit
0
5˚/ bit
segments
pixel/orbit;1°/
12-hr;0.5°/
pentad,monthly
0.25°/1-,3-,
7-day;monthly
5°/monthly
Global – 37°NS/Dec. 1997
Global – 37°NS/Dec. 1997
Gl b l – 70°N-S/
Global
70°N S/
Jan. 1998
Global Ocean –
82°N-S/1988-2007
SSM/I
2.5°/monthly
y
SSM/I
0.25˚/daily
1.0˚/pentad, mon
2.5˚/pentad, mon
0 25˚/daily
0.25
/daily
1.0˚/pentad, mon
2.5˚/pentad, mon
2.5°/pentad
GPI
OPI
AMSU
GEO-IR, LEO-IR in GEO
gaps
GEO LEO-IR
GEO-,
LEO IR
AVHRR
1°/3 hourly
1°/3-hourly
2.5˚/daily
Global Ocean –
70°N-S/July 1987
Global ocean –
40°N-S/Jan. 1998
Global ocean –
60°N-S/July 1987
Global/July 1987
Monthly
y
1 month
Daily
6 hours
Global/2000
Daily
4 hours
NESDIS ORA
(Weng and Ferraro)
Global – 40˚N-S
1986–March 1997
Global – 40
40˚N
N-S
S
Oct. 1996
Global/1979
N/A
N/A
Monthly
1 Week
Daily
1 day
NOAA/NWS CPC
(Xie)
NOAA/NWS CPC
(Xie)
NOAA/NWS CPC
(Xie)
IPWG#5, Hamburg, 11-15 October 2010
NASA/GSFC
TSDIS (Chiu)
Chinese U. of Hong
g
Kong (Chiu)
NESDIS ORA
(Ferraro)
Huffman 2/10
Gauge-based
Gauge
based precipitation analyses
Publiclyy available,, quasi-operational,
q
p
, quasi-global,
q
g
, gauge
g g p
precipitation
p
analyses
y
Algorithm
Input data
Space/time
scales
Areal coverage/
start date
Update
frequency
Latency
Producer
GPCC Gauge –
Version 2 “Full
Full
Analysis”
GPCC Gauge –
“Monitoring”
GHCN+CAMS
Gauge
CRU Gauge
~60,000 gauges
(climatology anomaly)
(climatology-anomaly)
0.5°,1˚,2.5°/
monthly
Global/1901-2007
Occasional
–
DWD GPCC
(Rudolf)
~8,000 gauges
(climatology-anomaly)
~3,800 gauges
(SPHEREMAP)
~20,000 gauges (anomaly
analysis)
1˚,2.5°/monthly
Global/2007
Monthly
3 months
2.5°/monthly
Global/1979
Monthly
1 week
0.5°/monthly
Global/1901
Occasional
–
DWD GPCC
(Rudolf)
NOAA/NWS CPC
(Xie)
U. East Anglia
(New and Viner)
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
EXAMPLES: GPCP V.2.1 SG climatology for 1979-2008
Note ITCZ, dry subtropical highs, mid-latitude storm tracks
is concentrated around maritime continent
Precipitation
p
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
Local linear trend in GPCP V.2.1 SG, 1979-2007 (29 years)
Regionally coherent trends do exist
• >0.7
0 7 mm/d/decade
/d/d
d linear
li
trend
t d over 29 years, locally
l
ll
• the pattern appears to be driven by increases in ENSO frequency
• data set inhomogeneities require careful examination
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
3B42RT
ECMWF
F
Model vs satellite
3-hourly precipitation accumulations for 1 June 2007
Clear differences between identification (or definition) of precipitation
IPWG#5, Hamburg, 11-15 October 2010
High resolution climatologies
IPWG#5, Hamburg, 11-15 October 2010
Occ
currence
e of rainffall
An
nnual total rainfa
all
TRMM PR data: 11 years (1997→) at ~5 km resolution.
Rainfall shows
g
local
significant
variability linked
with relief.
IPWG Inter-comparison
p
regions
g
Near real-time intercomparison of model & satellite estimates vs radar/gauge
IPWG#5, Hamburg, 11-15 October 2010
Space-time dependency
3-hour
At full resolution the ‘accuracy’
accuracy of
estimated rain is low; averaging over
time and space improves the picture
day
5-day
Month
VAR vs. HQ (mm/hr) Feb. 2002 30°N-S
Fine-scale data allows users to
decide the averaging strategy
IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10
600
radar 1km
SREM2D KIDD 4km
500
3
Discharge
e (m /s)
500
400
300
400
300
200
200
100
100
0
0
20
40
60
80
100
120
140
0
0
160
20
40
60
250
120
140
160
100
120
140
160
radar 1km
SREM2D 3B42
200
Discharge (m /s)
150
3
3
Discharge (m /s)
100
250
radar 1km
SREM2D KIDD 4km
100
50
0
0
80
Time (hrs)
Time (hrs)
200
Posina
a (116 km2)
radar 1km
SREM2D 3B42
600
3
Anagnostou
& Hossain:
700
700
Discharge
e (m /s)
Bacch
higlione (1200 km2)
Satellite error propagation in flood prediction
150
100
50
20
40
60
80
100
120
140
160
Time (hrs)
0
0
20
40
60
80
Time (hrs)
PMIR: 4km/30min
3B42RT: 1deg/3hr
High:57.9
Low:1.6
0.5 km
1 km
2 km
4 km
A li ti
l ti critical
iti l
Applications
are resolution
IPWG#5, Hamburg, 11-15 October 2010
8 km
16 km
High latitude precipitation
Validation instrumentation at
high latitudes to observe and
measure precipitation
IPWG#5, Hamburg, 11-15 October 2010
Sounding MW techniques
07:35
183-WSLC
snowfall
snowfall
183-WSL
09:15
10:55
09:15
07:35
Use of AMSU 183GHz:
p
g
of retrieving
capable
precipitation (rain and
snow) over cold
backgrounds
183-WSLC
10:55
183-WSLC
Vincenzo Levizanni, ISAC
IPWG#5, Hamburg, 11-15 October 2010
NIMROD
22 November 2008
Summary
y
• 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
Future
challenges
h ll
• Future missions will advance satellite precipitation retrievals
through improved sensors and sampling
• Extensions of retrievals of p
precipitation
p
at higher
g
latitudes is
challenging:
- Light intensity, low-level, frozen precipitation
- Surface background contamination
- Monitoring changes critical for climate studies
IPWG#5, Hamburg, 11-15 October 2010