Rainfall frequency Analysis Based in Long-Term High-Resolution Radar
Rainfall Fields: Spatial Heterogeneities and Temporal Nonstationarities
Abstract
Rainfall frequency analyses are presented for the Baltimore Metropolitan
region based on a 22-year, high-resolution radar rainfall data set.
Analyses focus on spatial heterogeneities and time trends in sub-daily
rainfall extremes.
The rainfall data set covers a domain of 4900 $km^2$, has a spatial
resolution of approximately 1 km and a time resolution of 15 minutes.
The data set combines reflectivity-based rainfall fields during the
period from 2000 - 2015 and operational polarimetric rainfall fields for
the period from 2012 - 2021.
Analyses of rainfall fields during the 2012 - 2015 overlap period
provide grounding for assessing time trends in rainfall frequency.
There are pronounced spatial gradients in short-duration rainfall
extremes over the study region, with peak values of rainfall between
Baltimore City and Chesapeake Bay.
Rainfall frequency analyses using both peaks-over-threshold and annual
peak methods point to increasing trends in short-duration rainfall
extremes over the period from 2000 to 2021.
Intercomparisons of sub-daily rainfall extremes with daily extremes show
significant differences.
Less than 50$\% $ of annual maximum hourly values
occur on the same day as the daily maximum and there is relatively weak
correlation between magnitudes when the hourly and daily maximum
overlap. Changing measurement properties are a key challenge for
application of radar rainfall data sets to detection of time trends.
Mean field bias correction of radar rainfall fields using rain gauge
observations is both an important component of the 22-year rainfall data
set and a useful tool for addressing problems associated with changing
radar measurement properties.