Validation and Inter-comparison of Validation and Inter-comparison of Satellite Rainfall Products over Satellite Rainfall Products over

Complex TopographyComplex Topography

T. Dinku, P. Ceccato, E. Grover-Kopec, T. Dinku, P. Ceccato, E. Grover-Kopec, S. J. Connor and C. F. RopelewskiS. J. Connor and C. F. Ropelewski

tufa@iri.columbia.edu

International Research Institute for climate and society (IRI)

The Earth Institute at Columbia University

MotivationMotivation Questions from users of IRI Data Library on Questions from users of IRI Data Library on

quality of the different rainfall estimatesquality of the different rainfall estimates

IRI uses/intends to use satellite rainfall IRI uses/intends to use satellite rainfall estimates mainly fro famine early warning and estimates mainly fro famine early warning and epidemic (Malaria/Rift valley fever) monitoringepidemic (Malaria/Rift valley fever) monitoring

Which data should be useWhich data should be use

Plans to help NMS to merge their gauge data Plans to help NMS to merge their gauge data with the “best” satellite productwith the “best” satellite product

Which is the best product?Which is the best product?

OutlineOutline Study regionStudy region

Gauge and satellite data usedGauge and satellite data used

Monthly products at 2.5-deg resolutionMonthly products at 2.5-deg resolution

Ten-daily accumulation at 1-deg resolutionTen-daily accumulation at 1-deg resolution

- Effects of topography, PM input and Calibration- Effects of topography, PM input and Calibration

Daily products at 0.25 degreeDaily products at 0.25 degree

SummarySummary

Study areasStudy areas

EthiopiaEthiopia

ZimbabweZimbabwe

Ethiopia: Mean Annual RainfallEthiopia: Mean Annual Rainfall

New_LocClim (FAO)

Ethiopia: Topography vs. RainfallEthiopia: Topography vs. Rainfall

NewLocClimNew_LocClim (FAO)

Gauge Data- 147 Station total, 120 used147 Station total, 120 used

- - 1990-2004 for monthly @ 1990-2004 for monthly @ 2.5 deg2.5 deg

-2000-2004 for 10-daily @ 1 2000-2004 for 10-daily @ 1 degdeg

-2003 and 2004 for daily at 2003 and 2004 for daily at 0.25 deg0.25 deg

- Gauge data gridded using Gauge data gridded using Climate Aided Interpolation Climate Aided Interpolation

- Kriging for interpolating Kriging for interpolating the meansthe means

- Angular-Distance Angular-Distance Weighting for anomaliesWeighting for anomalies

Raingauge UsedRaingauge Used

22

35 39

22

Elevation [meters]

Seasonal variation of rainfallSeasonal variation of rainfall

Satellite data usedSatellite data usedProduct Temporal Res. Spatial Res.GPCP Monthly 2.5 deg

CMAP Monthly 2.5 deg

TRMM-3B43 Monthly 2.5 deg

TAMSAT 10-daily 1.0 deg

GPCP-1DD 10-Daily 1.0 deg

RFE/ARC 10-Daily 1.0 deg

CMORPH 10-daily 1.0 deg

TRMM-3B42/RT 10-daily 1.0 deg RFE Daily 0.25 degCMORPH Daily 0.25 deg TRMM-3B42/RT Daily 0.25 deg NRL Daily 0.25.degPERSIANN Daily 0.25.deg

Comparisons: monthly @ 2.5 degComparisons: monthly @ 2.5 deg

Monthly at 2.5-degree Monthly at 2.5-degree (1/2)(1/2)

N = 360N = 360 GPCPGPCP CMAPCMAP 3B433B43

CCCC 0.920.92 0.920.92 0.920.92

EffEff 0.740.74 0.830.83 0.810.81

BiasBias 0.800.80 0.910.91 0.920.92

MEME -30-30 -12-12 -12-12

RMSRMS 3030 2424 2525

Data: 1998-2004

Monthly at 2.5-degree Monthly at 2.5-degree (2/2)(2/2)

Comparisons: 10-daily @ 1.0 degComparisons: 10-daily @ 1.0 deg

10-day @ 110-day @ 1o o x 1x 1oo

N=476N=476 RFE1RFE1 RFE2RFE2

CCCC 0.780.78 0.750.75

EffEff 0.410.41 -0.16-0.16

BiasBias 0.850.85 0.440.44

MEME -8-8 -30-30

RMSRMS 5353 7474

RFE1 vs RFE2: RFE1 vs RFE2: Effect of topographyEffect of topography

Data: March to September 2000

10-day @ 110-day @ 1o o x 1x 1oo

0

25

50

75

100

125

150

175

200

0 25 50 75 100 125 150 175 200Gauge[mm]

Sate

llite

[mm

]

RFE2

ARC

RFE2RFE2 vs ARC: vs ARC: Effect of PM data and sampling?Effect of PM data and sampling?

N=1020N=1020 RFE2RFE2 ARCARC

CCCC 0.660.66 0.660.66

EffEff -0.45-0.45 -0.88-0.88BiasBias 0.550.55 0.450.45

MEME -30-30 -38-38

RMSRMS 5858 6666

10-day @ 110-day @ 1o o x 1x 1oo

RFE2 vs 3B42RT: RFE2 vs 3B42RT: Effect of calibration(?)Effect of calibration(?)

N=828N=828 3B423B42 3B42RT3B42RT RFE2RFE2CCCC 0.700.70 0.720.72 0.700.70

EffEff 0.300.30 -0.07-0.07 -0.13-0.13

BiasBias 0.860.86 0.950.95 0.620.62

MEME -9-9 -4-4 -26-26

RMSRMS 4141 5050 5252

10-day @ 110-day @ 1o o x 1x 1oo

1DD, 3B42, TAMSAT and CMORPH1DD, 3B42, TAMSAT and CMORPH

N=306N=306 1DD 3B42 TAMSAT

CMORPH

CC 0.68 0.68 0.79 0.83Eff 0.04 0.26 0.53 0.49Bias 0.77 0.94 0.86 0.98ME -16 -4 -9 -1

. . -20

.. -30ОО -40

.. -50

.. -60

Ethiopia: CCD Thresholds(oC)

10-day @ 0.2510-day @ 0.25o o

RFE2, 3B42, CMORPHRFE2, 3B42, CMORPH

N=2448N=2448 RFE2RFE2 3B423B42 CMORPHCMORPH

CCCC 0.550.55 0.550.55 0.740.74

EffEff -0.23-0.23 0.020.02 0.350.35

BiasBias 0.590.59 0.920.92 0.980.98

MEME -27-27 -5-5 -1-1

RMSRMS 6262 5656 4646

Comparisons: Daily @ 0.25 degComparisons: Daily @ 0.25 deg

Daily @ 0.25Daily @ 0.25o o

EthiopiaEthiopiaRFE PERSIAN NRL 3B42 3B42RT CMORPH

Corr 0.08 0.14 0.12 0.11 0.12 0.14MnErr -2.37 3.26 -0.83 -0.34 0.00 0.09RMSE 10.22 18.13 12.24 11.27 13.81 10.45

Bias 0.65 1.48 0.88 0.95 1.00 1.01CSI 0.62 0.57 0.51 0.60 0.54 0.68

POD 0.71 0.64 0.57 0.69 0.62 0.80FAR 0.18 0.17 0.17 0.18 0.19 0.19HSS 0.18 0.18 0.14 0.16 0.13 0.21

Daily @ 0.25Daily @ 0.25o o

RFE PERSIANN NRL 3B42 3B42RT CMORPHCorr 0.74 0.42 0.34 0.62 0.39 0.54

MnErr -1.08 7.84 -1.12 -0.80 -0.88 -1.29RMSE 10.19 28.91 15.45 11.94 15.26 13.05

Bias 0.80 2.42 0.80 0.85 0.84 0.77CSI 0.59 0.46 0.42 0.53 0.44 0.51

POD 0.86 0.71 0.59 0.72 0.58 0.67FAR 0.34 0.43 0.40 0.33 0.35 0.32HSS 0.60 0.43 0.41 0.54 0.45 0.53

Zimbabwe: Zimbabwe: - - 43 Stations(12 GTS)43 Stations(12 GTS)

- No griding- No griding

- Data from Jan, Feb, Mar, Nov & Dec 2003- Data from Jan, Feb, Mar, Nov & Dec 2003

Daily @ 0.25Daily @ 0.25o o

SummarySummary

Results very good for monthly products @ 2.5 deg, good for 10-Results very good for monthly products @ 2.5 deg, good for 10-day products @ 1 deg, but poor for the daily products @ 0.25 day products @ 1 deg, but poor for the daily products @ 0.25 degdeg

There is significant influence of topography, which should be There is significant influence of topography, which should be taken into accounttaken into account

Spatially (and temporally) varying temperature thresholds and Spatially (and temporally) varying temperature thresholds and regression parameters improve the accuracy significantly.regression parameters improve the accuracy significantly.

-> TAMSAT performed as well as CMORPH-> TAMSAT performed as well as CMORPH