Relationship Among High Rainfall Rates, Atmospheric Moisture, and Temperature Based on High-Resolution Radar-Based Precipitation Estimates

Wednesday, 17 December 2014: 4:15 PM
Scott E Stevens1, Brian R Nelson2, Kenneth Kunkel1, Olivier P Prat1 and Thomas Richard Karl2, (1)Cooperative Institute for Climate and Satellites (CICS), North Carolina State University, and NOAA's National Climatic Data Center (NCDC), Asheville, NC, United States, (2)NOAA's National Climatic Data Center (NCDC), Asheville, NC, United States
Global warming is expected to increase maximum rainfall rates in many areas. A primary factor for this expectation is the large increase in atmospheric water vapor content expected with global warming, a simple application of the Clausius-Clapeyron (C-C) relationship. However, the spatial variations of changes will also be modulated by changes in frequency, intensity and location of the storms that produce heavy rainfall. In this study, we explore one dimension of this complex issue, specifically the observational evidence for robust relationships among atmospheric temperature, total precipitable water, and the most extreme magnitudes of surface rainfall rates. We investigate the extent to which a C-C relationship is followed and whether this is dependent on rainstorm duration. This information is crucial to understanding how to incorporate climate change considerations into extreme rainfall design values.

Using high-frequency rainfall measurements from both in-situ networks such as the US Climate Reference Network (USCRN) and radar estimates such as the newly-developed National Mosaic and Multisensor Quantitative Precipitation Estimate (NMQ/Q2), rainfall rates and accumulations are compared to precipitable water estimates obtained from both radiosonde data and hourly gridded model analysis. A variety of durations are explored to determine if rising temperature, and thus rising precipitable water availability, corresponds to an increase in the most extreme values of short-term rainfall intensity, longer-term rainfall accumulation, both, or neither.