1. Phil Arkin, Earth System Science Interdisciplinary Center University of Maryland, College Park (Presenter) J. Janowiak, M. Sapiano, D. Vila, ESSIC/UMCP J. Turk, Naval Research Laboratory, Monterey, CA E. Ebert, Bureau of Meteorology, Melbourne, Australia R. Ferraro, NOAA/NESDIS/STAR, Camp Springs, MD C. Kidd, Univ. of Birmingham, UK 2008 EUMETSAT Meteorological Satellite Conference 8-12 September 2008, Darmstadt, Germany Satellite-Derived Precipitation Verification Activities of the International Precipitation Working Group (IPWG)

2. 2000: Endorsed by the 52 nd WMO Executive Council 2001: Formation Meeting, Fort Collins, CO US 2002: IPWG-1, INM, Spain: Chairs: Vincenzo Levizzani (ISAC/CNR), Arnold Gruber (NOAA/NESDIS) 2004: IPWG-2, NRL, Monterey, CA, US Chairs: Joe Turk (NRL), Peter Bauer (ECMWF) 2006: IPWG-3, Bureau of Meteorology, Melbourne, Australia Chairs: Chris Kidd (Univ of Birmingham, UK), Ralph Ferraro (NOAA/NESDIS) 2008: IPWG-4 (October 13-17), Chinese Meteorological Agency, Beijing, China IPWG Background 8 IPWG Objectives #2: Establish standards for validation and independent verification of precipitation measurements #7:Make recommendations to national and international agencies The IPWG was established to foster: Development of better measurements, and improvement of their utilization; Improvement of scientific understanding; Development of international partnerships.

3. Satellite precipitation estimates -- what do we especially want to get right? Climate – relative variations, absolute magnitude NWP data assimilation (physical initialization) - rain location and type Hydrologists - rain volume Forecasters and emergency managers - rain location and maximum intensity (Slide courtesy of E. Ebert)

4. Combining Information from Multiple Satellites  Many (most?) current precipitation products combine information from passive microwave on polar orbiting satellites with that from infrared imagery from geostationary satellites  CMORPH, TMPA, PERSIANN, GSMaP and others are examples of High-Resolution Precipitation Products (HRPP)  IPWG established a project to evaluate these products and to facilitate further developments

5. Program for the Evaluation of High Resolution Precipitation Products (PEHRPP) A collaborative effort to understand the capabilities and characteristics of these High Resolution Precipitation Products Sponsored by the International Precipitation Working Group with broad voluntary participation Capitalizing on existing research and operational activities/datasets Implemented specifically to recommend an Integrated Precipitation Product to the IGOS-P Global Water Cycle Observations Theme (IGWCO) Providing a link between the observational and application communities

6. PEHRPP is designed to exploit four kinds of validation opportunities –Networks based on national or regional operational rain gauges or radar networks –High quality time series from ongoing research programs GEWEX CEOP, TAO/TRITON buoy gauges Ethiopia, Sao Paolo –Field program data sets NAME, BALTEX –Coherent global scale variability as depicted by the various data sets - the big picture

7. Near-realtime intercomparison of model & satellite estimates against radar/gauge observations (slide courtesy of C. Kidd, with additions) (See Ebert et al., BAMS, 2007)

8. Validation against ongoing research- quality time series Compare nearest HRPP grid-point to high-resolution gauges on TAO/TRITON Buoy array (Tropical Pacific - 24 gauges) –Evaluate between Dec 2002 and March 2006; Split buoys into 2 groups at 150W –Estimate HRPP value as weighted average of the 4 0.25° grid-points nearest to gauge –Undercatch corrections applied based on wind and threshold rate –Exclude buoy stations with probability of precipitation <0.1 Sapiano and Arkin, J. Hydrometeorology, 2008 (in press)

9. Oceanic (TAO): % Bias Statistics calculated for the entire year (relatively little seasonality), but split into two groups east/west of 150˚ W Correlations between 3-hourly gauge values and satellite estimates range from 0.4 – 0.6 Spread of results is less west of 150˚ W –PERSIANN has mean bias of zero with corrected data –CMORPH and TMPA underestimate by 25% –Different results for uncorrected data (correction is somewhat uncertain!) All HRPPs underestimate precipitation East of 150˚ W (even for uncorrected values) –NRL has a single extreme value which skews means These results are consistent with other findings that satellite-derived estimates of precipitation are generally at the lower end of the available values –e.g.: GPCP vs. Atolls, models

10. North American Monsoon Experiment (NAME)

11. North American Monsoon Experiment Precipitation Daily Evolution: NERN vs Satellite over NAME Domain (Nesbitt)

12. Guangdong Validation Site: Jianyin Liang, CMA with Pingping Xie, NOAA Guang-Dong 394 hourly real-time gauges April – June 2005 period of initial data

13. April – June 2005 Mean Precipitation Seasonal Mean Bias Correlation (3-hourly/ 0.25 o) Gauge CMORPH GPCC 3B42RT 3B42 MWCOMB

14. First Workshop on the Program for the Evaluation of High Resolution Precipitation Products (PEHRPP) Hosted by the IPWG 3-5 December 2007, WMO, Geneva 40 attendees from 12 countries Presentations and working group reports on applications, validation and error metrics

15. Workshop on the Evaluation of High Resolution Precipitation Products Workshop focus areas included products, regional validation, error metrics and applications Workshop report submitted to BAMS (January 2008) Recommendations to be presented to IPWG: Several high resolution precipitation products exhibit useful skill, but clear superiority for one is not yet evident IPWG should establish a continuing effort to conduct, facilitate and coordinate validation and evaluation of such products A concerted validation/intercomparison campaign, covering multiple climatic regimes and seasons, should be designed and conducted

16. Web Page: http://www.isac.cnr.it/~ipwg/IPWG.html

17. Thank you for your attention!