A New Method for Near Real-Time Precipitation Estimates and Realistic Minimum Detection Times Using Remotely Sensed PWV.

摘要

Satellite remote sensing of Precipitable Water Vapor (PWV) is essential for monitoring moisture in real-time for weather applications, as well as tracking the long-term changes in PWV for climate change trend detection. The first part of this study assesses the accuracies of the current satellite observing system, specifically the Atmospheric Infrared Sounder (AIRS) v6 PWV product and the Infrared Atmospheric Sounding Interferometer (IASI) v6 PWV product, using Ground-Based SuomiNet Global Positioning System (GPS) network as truth. Elevation-corrected collocated matchups to each SuomiNet GPS station in North America and around the world was created and results were broken down by station, ARM-region, climate zone, and latitude zone. The operational IR satellite products are able to capture the mean PWV but degrade in the extreme dry and wet regimes.;The second part of this study is to combine the predicted GCM trends in the PWV probability distribution over the time period 2000--2100 with uncertainty estimates from the new generation of infrared spectrometers to estimate minimum trend detection times on spatial scales that vary from regional to global. The product accuracies used in this conceptual study are recent estimates from the high spectral resolution infrared spectrometers, the NASA AIRS version 6 and the EUMETSAT IASI version 6 official products. A fractional measurement error of about 3% is needed to detect predicted climate trends within 15 years or less.;For the final part of this study, a 10-year global statistical climatological relationship will be derived between PWV and precipitation by using the AIRS daily gridded PWV product and a NASA Tropical Rainfall Measuring Mission (TRMM) daily gridded precipitation total. The statistical distributions used in the regression fit will be described in detail. An assessment of the TRMM/AIRS relationship will be examined using a National Weather Service (NWS) radar precipitation dataset over the continental United States (CONUS) and the application of this relationship will be characterized through case studies. The analysis will highlight the advantages of applying this relationship in near-real time for flash flood monitoring and risk management.