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

Conclusions

Introduction

Theory and Techniques

Georeference

(IR Brightness)-(Cloud Top Temperature) Relationship

The Convective and Stratiform Technique (CST)

Storm Localization and Assesment

Georeference

Georeference

Relationship T-B

Convective and Stratiform Technique (CST)

Detection of Convective, stratiform and cirrus clouds

Tmin < 253°K

For each convective storm its intensity, rC, is:

Over an area

WhereY

X

Z

rc

T

X

Ac

rC = rC0 - rC1 TC

Tc) - A(AC

CC = e A 10

KTTTTT

KTTT

MINCMINCMIN

MINMINC 200si)(

200si

01

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

Implementation

Algorithm

Images

Products

Webpage

Operational Results: Pseudo-imagery

A:IR Images B:Intensity P-Image C:Acumulated P-Image

CBA

Operational Results : Numerical Reports

For basins and sites Lluvia acumulada promedio de 10051503.ACU en las regiones de cuencas.polRegión Promedio Millones de m3Lerma - Santiago 1.661 226.489Balsas 7.625 899.673Guerrero - Costa 1.416 19.776Pinotepa 21.165 822.995Huatulco 20.368 225.329Tehuantepec 29.847 488.984Chiapas - Pacífico 2.248 27.191Zacatecas - Nuevo León - San Luis Potosí 0.054 4.850Tamaulipas 0.000 0.000Huasteca 10.020 972.349Pánuco 40.112 1081.230Papaloapan 42.953 2510.730Istmo - Golfo 11.258 331.346Grijalva 1.463 150.828Campeche 0.052 1.276

..

Promedio en la proximidad de puntos, tomado de 10051503.ACUDistancia para promedio: 7Nombre Long. Lat. Prom. Centro Min. Max...#1022 VER Jalapa -96.920 19.550 39.50 34.00 30.75 45.00#1023 VER La Cangrejera -94.900 17.980 17.08 28.25 8.12 29.25#1024 VER La Joya -97.620 20.560 34.41 39.25 15.25 39.25#1025 VER Las Perlas -94.650 17.770 0.56 1.00 0.00 1.00#1026 VER Los Hules -98.270 21.160 17.97 15.62 15.62 21.38#1027 VER Martinez De La Torre -97.050 20.067 70.81 70.62 70.62 71.12#1028 VER Mizantla -96.970 20.170 71.94 72.00 71.00 72.62#1029 VER Minzapan -96.890 20.000 71.92 72.25 71.38 72.38#1030 VER Rio Grande -94.370 17.280 3.22 3.25 3.12 3.25#1031 VER Orizaba -97.100 18.850 21.92 21.62 13.50 28.12#1032 VER Oxtlapa -97.100 19.350 33.47 24.62 14.25 45.88#1033 VER Panuco -98.170 20.510 29.07 32.50 24.25 33.25..

Graphical Binnacle

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

Web page

A web page was designed and instaled in the same server nimbus, in which EPPrePMex is running in IMTA´s Offices.

Its adress is http://nimbus.imta.mx

It is working since the summer 1999.

Evaluation

NOAA comparison 1998-1999

Site comparison 1997-2002

Basin comparison 1997-2002

Evaluation

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

Estimación de Precipitación con Satélite

TEXAS, 18-Oct-1998, 24 hr.

y = 0.9743x + 50.754

R2 = 0.4983

y = 0.7233x + 36.494

R2 = 0.6174

0

100

200

300

400

500

600

0 100 200 300 400 500 600

Medición (mm)

Es

tim

ac

ión

co

n S

até

lite

, p

rom

ed

io d

e 9

pix

(m

m)

Mejor

AutoEstimator

EPPrePMex

Lineal (AutoEstimator)

Lineal (EPPrePMex)

Evaluation

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

Evaluation

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

Rainfall measurementsmade by the operational hydrological network

Evaluation

Measured (gage) Estimated (GOES satellite)

Evaluation

A B

A’ B’

INCOMPATIBLE

COMPATIBLE

Evaluation

Evaluation

Evaluation

Evaluation (Bias correction)

Evaluation

Present Research Operational rainfall estimation based of GOES-12 and GOES-10, radars

and weather stations

Real-time Calibration of rainfall estimation with satellites and radar

Detection and analysis of MCC

Clasification of storms

Calibration of GOES based estimation with other satellites (Tiros, SSMI, TRMM, Acqua, etc).

Integration with modern (distributed) hydrological models (MIT and others)

GOES-12 complemented with GOES-10

During eclipses GOES-10 imagery will complement

GOES-12.

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

Storm Development Stage

Clasification of Storms

Conclusions

The End

¡Thank you very much!