Decorrelation of Satellite Precipitation Estimates in Space and Time

Abstract

Precise estimates of precipitation are required for many environmental tasks, including water resources management, improvement of numerical model outputs, nowcasting and evaluation of anthropogenic impacts on global climate. Nonetheless, the availability of such estimates is hindered by technical limitations. Rain gauge and ground radar measurements are limited to land, and the retrieval of quantitative precipitation estimates from satellite has several problems including the indirectness of infrared-based geostationary estimates, and the low orbit of those microwave instruments capable of providing a more precise measurement but suffering from poor temporal sampling. To overcome such problems, data fusion methods have been devised to take advantage of synergisms between available data, but these methods also present issues and limitations. Future improvements in satellite technology are likely to follow two strategies. One is to develop geostationary millimeter-submillimeter wave soundings, and the other is to deploy a constellation of improved polar microwave sensors. Here, we compare both strategies using a simulated precipitation field. Our results show that spatial correlation and RMSE would be little affected at the monthly scale in the constellation, but that the precise location of the maximum of precipitation could be compromised; depending on the application, this may be an issue.

Use of dual-polarization weather radar quantitative precipitation estimation for climatology

“…Precipitation data from satellites provides good spatial coverage, but still not in ve ry high temporal resolution, especially in higher latitudes (Sun et al, 2018). Polar orbiting satellites provide better spatial resolution data in highe r latitudes, but they are very limited in temporal resolution (Tapiador et al, 2018). In the last deca de various studies have used multi-year single polarization weather radar data to a good effect in deriving rainfall climatology with high spatiotemporal resolution 30 (Overeem et al, 2009;Goudenhoofdt et al, 2016).…”

Evaluation of the dual-polarization weather radar quantitative precipitation estimation using long-term datasets

“…The working range of measures is from 0 mm to 300 mm/h, with underestimation for high precipitation intensities. Such errors are corrected according to results of the WMO Field Intercomparison of Rainfall Intensity Gauges (Vuerich et al, 2009). An automatic data quality check is run on real-time data, followed by offline manned data validation.…”

“…Precipitation data from satellites provide good spatial coverage but still not in very high temporal resolution, especially in higher latitudes (Sun et al, 2018). Polar-orbiting satellites provide better spatial resolution data in higher latitudes, but they are very limited in temporal resolution (Tapiador et al, 2018). What is more, satellite-based precipitation estimates are limited by the accuracy of the estimates.…”

Editorial for Special Issue “Remote Sensing of Precipitation”

“…One is to develop geostationary millimeter-submillimeter wave soundings, and the other is to deploy a constellation of improved polar microwave sensors. Tapiador et al [28] compare both strategies using a simulated precipitation field. The results show that spatial correlation and RMSE would be little affected at the monthly scale in the constellation, but the precise location of the maximum of precipitation could be compromised.…”