1. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Ground Validation of Satellite Precipitation Estimates over Spain Francisco J. Tapiador Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha, UCLM Toledo, Spain francisco.tapiador@uclm.es With inputs from Antonio Rodriguez and Miguel A.Martínez, Spanish Nal. Meteorological Institute (INM), Madrid, Spain

2. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Introduction A. The UCLM’s Environmental Modeling Group -GCM and NWP– The PROMES model -Remote Sensing – Satellite Precipitation -Algorithm development -Some Validation B. Some examples of our validation work over Spain 1.Andalusia case study (METEOSAT+SSM/I) 2.IPWG satellite estimates over Spain (CICS, University of Maryland data) 3.EUMETSAT Convective Rain Rate product (INM, Spain) C. Some notes on Spain as validation site IntroVal example 1Val example 2ConclusionsAlgorithmsVal example 3

3. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Merged Satellite Rainfall Algorithms - EURAINSAT/A algorithm (Tapiador et al. 2004, IJRS) - PMW-calibrated IR -Neural Networks (Tapiador et al. 2004, Met App) -PMW+IR IR spatial and temporal resolution + PMW directness -4km/30 minutes resolution -Used by some farmers for irrigation planning – advised on shortcomings and limitations -Cloud motion winds PMW+IR estimate IntroVal example 1Val example 2AlgorithmsVal example 3Conclusions

4. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Neural Networks Product SSM/I only Neural Net (Meteosat+SSM/I) Histogram Matching (Meteosat+SSM/I) Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

5. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3Conclusions Cloud Motion Winds (CMW) Scheme -Similar to CPC Morphing -Difference: CMW are directly modeled using Navier-Stokes equations instead of spatial correlation windows: more physically- direct and more realistic fields -Reference: Tapiador, 2004. 2nd IPWG meeting, Monterey, CA -Used for data assimilation into GCM Intro

6. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 02:3003:0003:3004:3005:0005:30 ACTUAL RAIN MEASUREMENT RAIN ESTIMATE ACTUAL RAIN MEASUREMENT RAIN ESTIMATE Independent Validation CMW Diffusion

7. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Comparison between CMW estimate and (independent) reference rainfall for 02:30 TUC (2 hour step, forward propagation) Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

8. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 What if we use the 02:30 measure instead of the 04:30 CMW- scheme estimate when comparing @ 04:30? So, the CMW scheme is actually transporting rainfall Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

9. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Time degradation: Average for 31/OCT/2003 Using the CMW, we can maintain correlations > 0.80 for up to 2.5 hours The performances of the method when compared with ground rainfall at instantaneous scale will be linked with the performances of the rainfall to be transported: relevant perhaps for GPM Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

10. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro http://hermes.uclm.es

11. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

12. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Validation activities -Opportunity: we needed data for algorithm pre-calibration -Validation has a geographical component: validation results are different in different places, and we need the algorithms tuned for Spain. -Validation against gauge, GR; comparison with models IntroVal example 1Val example 2AlgorithmsVal example 3Conclusions

13. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3 Andalusia case study ConclusionsIntro

14. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Half-hourly raingauge data availability Neural network IR+PMW fusion Algorithm characteristics: High temporal resolution High spatial resolution High accuracy Tapiador, F.J., Kidd, C., Levizzani, V., Marzano, F.S., 2004. A Neural Networks-Based Fusion Technique to Estimate Half Hourly Rainfall Estimates at 0.1º Resolution from Satellite Passive Microwave and Infrared Data. Journal of Applied Meteorology, 43, 576-594. Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

15. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Rain Gauges in Andalusia Interpolation I – Kriging Interpolation II – Inverse distance SSM/I data Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

16. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Correlations at 0.1º (monthly) Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

17. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Correlations at 0.5º (monthly) Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

18. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3 Validation of IPWG Products on Spain ConclusionsIntro

19. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 NRL PMWCPC GeoNOGAPS Val example 1AlgorithmsVal example 3Conclusions (CICS, University of Maryland archive) 00Z-00Z products - NOGAPS - NRL GEO - NRL PWM - CPC Morphing - 3B42RT Val example 2Intro

20. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Rain Gauges Location Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

21. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

22. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1AlgorithmsVal example 3 Geolocation error surface analysis Data from 01/JAN/2005 to 01/SEP/2005 Satellite vs gauge Assuming 5km interval error in the nominal satellite data geolocation ConclusionsVal example 2Intro

23. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1AlgorithmsVal example 3 AlgorithmBest r 2 3BR420.30 CPC0.33 GEO0.09 PMW0.09 NOGAPS0.15 ConclusionsVal example 2 3B42RT CPC Morphing NRL GEO NRL PMWNOGAPS Intro

24. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3 EUMETSAT’s Convective Rain Rate Product (CRR) Nowcasting Satellite Application Facility (SAF) ConclusionsIntro

25. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

26. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsConclusionsVal example 3Intro

27. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsConclusionsVal example 3 Validation – Comparison data sources Intro

28. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Val example 1Val example 2AlgorithmsConclusionsVal example 3 GR Visual comparison Intro

29. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Spain as validation site Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

30. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Pros and Cons Many examples of frontal, convective and orographic precipitation – and mixed cases. Three rainfall regimes in 500,000 sq km (Texas= 696,000 sq Km) High N-S gradient. Well-calibrated, reliable validation net Rain gauges nets (INM, river authorities, etc.) Ground Radar TRMM coverage (South), MSG, SSM/I, AMSU, AVHRR, etc. Limited area Limited public availability of validation data – but this could be solved for GPM Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

31. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Available Validation Data INM gauges network GR River authorities networks Agrarian Meteo Nets Specifically-tailored nets and instrumentation Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

32. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 37N Val example 1Val example 2AlgorithmsVal example 3 Geography ConclusionsIntro

33. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005 Conclusions Suitability for validation site in Catalonia (Daniel Sempere, GRAHI): Experience in satellite rainfall estimates algorithms Interface with NWP modelers (NWP+Sat+Merged algorithms) Data availability and support from agencies Geography of Spain: very different from other validation places Val example 1Val example 2AlgorithmsVal example 3ConclusionsIntro

34. Institute of Environmental Sciences (ICAM) University of Castilla-La Mancha (UCLM), Toledo, Spain 2nd GPM GV Meeting, Taipei, Taiwan 27-29/Sep/2005