Improving the radar Z-R relationships over Puerto Rico

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Sunday, 17 January 2010
Exhibit Hall B2 (GWCC)
Nazario D. Ramirez-Beltran, Univ. of Puerto Rico, Mayaguez, Puerto Rico, PR; and C. J. Carrasquillo and S. Cruz-Pol

Handout (481.1 kB)

Improving rainfall estimates during heavy storms is especially important to save human lives and to protect property. Warning people about the occurrence of flash-flood and/or the landslide events may help to mitigate their catastrophic effects. Puerto Rico (PR) has a dense rain-gauge network and during the rainy season severe rainstorms develop due to geographical location and complex orographical attributes. The easterly winds are coming from the eastern Atlantic during almost all year and play an important role bringing humidity into the island and stimulating orographical rainfall over the mountains of PR. Cold fronts dominate the weather pattern during wintertime. The tropical waves occur during the rainy season and frequently generate large amount of rainfall in the Caribbean basin. These tropical waves are largely the precursor of the tropical storms and hurricanes in the North Atlantic basin during the hurricane season (June to November). A validation algorithm was developed to enhance the NEXRAD-rain-rate measurements. A dense rain gauges network was installed in Puerto Rico and collect data every 15 minutes. Radar data were aggregated to obtain 15 minutes of accumulation rainfall. PR was divided in 3 zones according to the distance from radar to rain gauge location for purposes of developing a radar correction factor. NEXRAD measurements over the western part of PR are frequently inaccurate. This is because reflectivity measurements are conducted at about 2000m above the surface as a result of the elevated location of the radar and a relatively high scan angle which was selected to minimize beam block by nearby mountains. The NEXRAD bias is measured with the purpose of developing a bias correction algorithm to improve rain rate estimations especially over the western part of PR. The bias correction algorithm will be based on high resolution observations obtained from Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network that is being installed in the western part of PR. Although, the validation algorithm was developed by PR, it can be applied to other place characterized by tropical climate conditions.