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A Kalman Filter Approach to Blend Various Satellite Rainfall Estimates in CMORPH

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 4

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A Kalman Filter Approach to Blend Various Satellite Rainfall Estimates in CMORPH

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  1. 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 YaroshNOAA/NCEP/CPC Wyle Information Systems International Precipitation Working Group 4 October 12-16, 2008. Beijing China.

  2. Outline • 1. Current CMORPH operational status • 2. Evaluation of CMORPH components • 3. CMORPH Kalman filter versions • 4. Gauge adjusted CMORPH • 5. Conclusions and Future plans

  3. 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/

  4. Correlation of 0.25 degree lat/lon propagated PMW rainfall w/ Stage II radar rainfall • JJAS 2007

  5. Cumulative rain rate distribution of Kalman filtered rainfall, PDF adjusted Kalman filtered, and radar rainfall.

  6. IPWG U.S. daily 0.25 degree rainfall validation • Kalman filter CMORPH no PDF adjustment • NEXRAD Stage II radar rainfall • Kalman filter CMORPH PDF adjusted

  7. Gauge-adjusted CMORPHsee poster by Xiong session 2B Cross-Validation Tests over China May-Sept 2007Time Series

  8. Cross-Validation Test SummaryCombined space / time domain • Successful correction of the bias; • Substantial improvements in correlation

  9. SUMMARY 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.

  10. FUTURE WORK • 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

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