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Jorge Sánchez-Sesma Marco Antonio Sosa Chiñas* IPWG, October 2004, Monterey, California, USA EPPrePMex, A Real-time Rainfall Estimation System Based on.

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Presentation on theme: "Jorge Sánchez-Sesma Marco Antonio Sosa Chiñas* IPWG, October 2004, Monterey, California, USA EPPrePMex, A Real-time Rainfall Estimation System Based on."— Presentation transcript:

1 Jorge Sánchez-Sesma Marco Antonio Sosa Chiñas* IPWG, October 2004, Monterey, California, USA EPPrePMex, A Real-time Rainfall Estimation System Based on GOES-IR Satellite Imagery

2 Conclusions

3 Introduction

4 Theory and Techniques u Georeference u (IR Brightness)-(Cloud Top Temperature) Relationship u The Convective and Stratiform Technique (CST) u Storm Localization and Assesment

5 Georeference

6

7 Relationship T-B

8 Convective and Stratiform Technique (CST) u Detection of Convective, stratiform and cirrus clouds  T min < 253°K  For each convective storm its intensity, r C, is: u Over an area u Where r C = r C0 - r C1 T C

9 Convective and Stratiform Technique (CST) (Storm radius)-(Cloud top temperature) A Relationship for Mexico

10 Implementation u Algorithm u Images u Products u Webpage

11 Operational Results: Pseudo-imagery A:IR Images B:Intensity P-Image C:Acumulated P-Image CB A

12 Operational Results : Numerical Reports u For basins and sites Lluvia acumulada promedio de ACU en las regiones de cuencas.pol Región PromedioMillones de m3 Lerma - Santiago Balsas Guerrero - Costa Pinotepa Huatulco Tehuantepec Chiapas - Pacífico Zacatecas - Nuevo León - San Luis Potosí Tamaulipas Huasteca Pánuco Papaloapan Istmo - Golfo Grijalva Campeche Promedio en la proximidad de puntos, tomado de ACU Distancia para promedio: 7 Nombre Long. Lat. Prom. Centro Min. Max... #1022 VER Jalapa #1023 VER La Cangrejera #1024 VER La Joya #1025 VER Las Perlas #1026 VER Los Hules #1027 VER Martinez De La Torre #1028 VER Mizantla #1029 VER Minzapan #1030 VER Rio Grande #1031 VER Orizaba #1032 VER Oxtlapa #1033 VER Panuco

13 Graphical Binnacle u A graphical binnacle displays the processed images. Each dot indicate a processed image and its size indicates the number of storms.

14 Web page u A web page was designed and instaled in the same server nimbus, in which EPPrePMex is running in IMTA´s Offices. u Its adress is u It is working since the summer 1999.

15 Evaluation u NOAA comparison u Site comparison u Basin comparison

16 Evaluation u In 1998 the NOAA has made a comparison of estimated (Autoestimator and EPPrePMex) and measured daily accumulated rainfalls for Southern Texas

17 Evaluation Correlation between EPPrePMex estimations & RFCwide stations measurements of daily rainfall for July-Oct 1999

18 Evaluation Correlation between EPPrePMex estimations & NW Mexico stations measurements of daily rainfall for July-Oct 1998

19 Rainfall measurements made by the operational hydrological network Evaluation

20 Measured (gage)Estimated (GOES satellite) Evaluation A B A’ B’ INCOMPATIBLE COMPATIBLE

21 Evaluation

22

23

24 Evaluation (Bias correction)

25 Evaluation

26

27 Present Research u Operational rainfall estimation based of GOES-12 and GOES-10, radars and weather stations u Real-time Calibration of rainfall estimation with satellites and radar u Detection and analysis of MCC u Clasification of storms u Calibration of GOES based estimation with other satellites (Tiros, SSMI, TRMM, Acqua, etc). u Integration with modern (distributed) hydrological models (MIT and others)

28 GOES-12 complemented with GOES-10 During eclipses GOES-10 imagery will complement GOES-12.

29 GOES-12 complemented with Radar Rainfall Intensity (Radar) 6 hour animation: 17:45 a 23:45 Z Accumulated Rainfall (Satellite) 3 hours: 18:00 a 21:00 Z

30 Storm Development Stage

31 Clasification of Storms

32 Conclusions

33 The End ¡Thank you very much!


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