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precipitation estimation
Due to the scarcity of sufficient spatial ground-based rainfall data in hill areas, quantitative precipitation estimation using remote-sensing techniques such as radar and satellite is needed for debris flow pre-warning.
      
Automatic calibration and verification of radar accuracy for precipitation estimation.
      
In general, the scattering of the observational products may represent the uncertainty in global precipitation estimation.
      
Over the past three decades there have been numerous attempts to use satellite measurements for precipitation estimation.
      
Precipitation estimation from remotely sensed information using artificial neural networks.
      
Precipitation estimation accuracy and reliability is tested against data from more than one hundred rain gages.
      
This is followed by propagating the joint distribution of the errors through the specific WSR-88D precipitation estimation algorithm.
      
Thus over land, only considerable scattering by ice particles aloft allows a rather indirect precipitation estimation.
      
These more stringent requirements relate to both the support of the automated algorithms and the move to quantitative precipitation estimation.
      
The authors describe a comprehensive plan of introducing probabilistic quantitative precipitation estimation into the operational NWS environment.
      
 

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