a kalman filter approach to blend various satellite rainfall estimates in cmorph robert joyce...
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A Kalman Filter Approach to Blend Various Satellite Rainfall Estimates in CMORPH
Robert Joyce NOAA/NCEP/CPC Wyle Information Systems
Pingping Xie NOAA/NCEP/CPC
Yelena Yarosh NOAA/NCEP/CPC Wyle Information Systems
International Precipitation Working Group 4October 12-16, 2008. Beijing China.
1. Current CMORPH operational status
2. Evaluation of CMORPH components
3. CMORPH Kalman filter versions
4. Gauge adjusted CMORPH
5. Conclusions and Future plans
Outline
Update on Retrospective CMORPH Processing
• Currently CMORPH archive extended backward from 7 December thru 30 October 2002• Improved quality of retrospective CMORPH relative to operational CMORPH in early Dec 2002• Reprocessing rate is currently 4 days per working day• ftp.cpc.ncep.noaa.gov: precip/global_CMORPH_3-hourly_0.25deg/
Propagated forward
t = 0 t + 0.5 hr t + 1hr t + 1.5 hr
0330 GMT 0400 GMT 0430 GMT 0500 GMT
t = 0 t + 0.5 hr t + 1 hr t + 1.5 hr
0330 GMT 0400 GMT 0430 GMT 0500 GMT
Propagated backward
a
b
Observed
c 0330 GMT 0400 GMT 0430 GMT 0500 GMT
0.67 0.33
0.670.33
Time InterpolationWeights
Propagated & “Morphed”
The microwave precip. features are propagated forward and backward in time.
Then the features are “morphed” by linearly interpolating in time as depicted in panel “c”
each grid value for the 0400 & 0430 GMT images is obtained by:
P0400= 0.67 x P0330 + 0.33 x P0500
P0430= 0.33 x P0330 + 0.67 x P0500
• Correlation of 0.25 degree lat/lon propagated PMW rainfall w/ Stage II radar rainfallCorrelation of 0.25 degree lat/lon propagated PMW rainfall w/ Stage II radar rainfall
• JJAS 2007JJAS 2007
•
•Cumulative rain rate distribution of Kalman filtered rainfall, PDF adjusted Kalman filtered, and radar rainfall.
• IPWG U.S. daily 0.25 degree rainfall validation
Kalman filter CMORPH
no PDF adjustment
Kalman filter
CMORPH PDF adjusted
NEXRAD Stage II
radar rainfall
Cross-Validation Tests over ChinaCross-Validation Tests over China May-Sept 2007 Time SeriesTime Series
Gauge-adjusted CMORPHsee poster by Xiong session 2B
Cross-Validation Test SummaryCross-Validation Test SummaryCombined space / time domain Combined space / time domain
CMORPHCMORPH Bias (%)Bias (%) CorrelationCorrelation
OriginalOriginal -9.7%-9.7% 0.7060.706
Adjusted (7days)Adjusted (7days) -0.0%-0.0% 0.7850.785
Successful correction of the bias;
Substantial improvements in correlation
1. Retrospective CMORPH reprocessing is underway! Will update ftp archives after a few more QC checks … looks good so far.
2. For convective-dominated rainfall regimes, the inclusion of the
IR derived estimates in the Kalman filtering process substantially improves the combined satellite rainfall product.
3. Use of instantaneous rain rate PDFs eliminate the rain rate damping and increase of spatial coverage created by the filtering process.
4. The gauge adjusted CMORPH tests over China have encouraging
results for both increase in skill and reduction in bias.
SUMMARY
• Continue retrospective CMORPH reprocessing … our goal is to have CMORPH back to beginning of TRMM era (Jan 1998) by October 2009. Will fuse IR derived estimates for pre-AMSU period.
• Translate lessons learned from this NEXRAD study for use with TRMM TMI (GPM in the future) for regional/seasonal depiction of skill/error variance of each sensor/algorithm.
• Continue gauge adjusted CMORPH project to achieve globally adjusted product
FUTURE WORK