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R. Tsheko , M. Tapela, N.J. Batisani Botswana College of Agriculture Crop and Rangeland Monitoring PowerPoint Presentation
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R. Tsheko , M. Tapela, N.J. Batisani Botswana College of Agriculture Crop and Rangeland Monitoring

R. Tsheko , M. Tapela, N.J. Batisani Botswana College of Agriculture Crop and Rangeland Monitoring

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R. Tsheko , M. Tapela, N.J. Batisani Botswana College of Agriculture Crop and Rangeland Monitoring

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  1. R. Tsheko, M. Tapela, N.J. Batisani Botswana College of Agriculture Crop and Rangeland Monitoring Agriculture Service

  2. Agenda SADC THEMA Services Course Content • Rainfall Products

  3. Rainfall products • What are RFEs?

  4. Rainfall products • Most of the developing world and huge water bodies like the ocean do not have adequate rainfall gauge networks and weather radars coverage Global telecommunication stations

  5. Rainfall products • Meteorological satellites are then only source of precipitation information to fill in the gaps. • Characterization of rainfall variation in time and space is very important for crop monitoring for food security in the SADC region • Satellite rainfall estimates could be fed into crop yield models

  6. Rainfall products • remote sensing systems unlike rain gauges, do not directly measure rainfall but rather rely indirectly measure the precipitation based on cloud reflectance, cloud-top temperature, and on the presence of frozen precipitation to estimation rainfall intensity

  7. Rainfall products • There are several different types of satellite rainfall estimation algorithms developed and these may use, only infrared (IR) data; passive microwave (PM) data; combination of IR and PM; assimilate available real-time gauge data and precipitation data onboard the Tropical Rainfall Measuring Mission (TRMM) satellite

  8. Rainfall products • The GOES Precipitation Index (GPI) is based on the thermal infrared information of the clouds (temperature of clouds-top is below 235 K and is assigned a rain rate of 3 mmhr-1 ). • MeteoSat data used to composite a CCD image at -38oC, a rainfall estimate is generated from the CCD using the GOES Precipitation Index (GPI) where GPI = CCD x 3

  9. Rainfall products • Microwave sensors are used to estimate rainfall based on the emmissivity of the cloud (ice particles and large rainfall drops reduces emmissivity hence reduces cloud brightness temperature) • The Tropical Applications of Meteorology using SATellite (TAMSAT) group at Reading produced daily CCD (Cold Cloud Duration) maps from raw Meteosat thermal infra-red (IR) images using a -38oC threshold temperature.

  10. Rainfall products • The Tropical Applications of Meteorology using SATellite (TAMSAT) group at Reading produced daily CCD (Cold Cloud Duration) maps from raw Meteosat thermal infra-red (IR) images using a -38oC threshold temperature. CCD – cold cloud duration Created from Thermal &IR images (Met Sats)

  11. Rainfall products • The NOAA Climate Prediction Center (CPC) used the Rainfall Estimation (RFE 1.0) algorithm from 1995 to 2000 • In 2001, the Rainfall Estimation Algorithm Version 2 (RFE 2.0) replaced REF 1.0 on operation status. • The REF 2.0 significantly reduced bias and random error hence increases the accuracy of the rainfall estimates.

  12. Rainfall products • REF 2.0 ingests four (4) different data sets namely; • 1) Daily Global Telecommunications Station (GTS) rainfall gauge data for up to 1000 stations • 2) AM SU microwave precipitation estimates • 3) Special Sensor Microwave/Imager (SSM/I) satellite rainfall estimates and • 4) GPI cloud-top IR temperature estimates.

  13. Rainfall products

  14. Rainfall Products

  15. The END Thank You.