1. Extreme Precipitation Frequencies
The Use of Multi-Sensor Quantitative Precipitation Estimates for Deriving
Extreme Precipitation Frequencies
Hisham El-Dardiry & Emad Habib
Department of Civil Engineering, University of Louisiana at Lafayette, LA, USA
Study Objectives and Motivation
Radar Data
Outlier Detection Test
Radar quantitative precipitation estimates (QPE) have been used for a long time in different applications including weather prediction models, flash floods prediction and monitoring systems.
The statistics of the extreme precipitation events have played an important role in various engineering disciplines including the hydrologic applications, for instance, the design of flood protection structures and the development of the roadway drainage systems.
The objective of this study is to examine the utility of radar-based precipitation frequency estimates (PFE) information with their associated uncertainties and comparing them with the NOAA ATLAS 14 gauge-based PFE.
Two sources of radar data are used in this study:
National Stage IV QPE mosaicked from individual RFC's multi-sensor precipitation analyses.
The Lower Mississippi River Forecast Center (LMRFC) selected product for hydrologic operations (XMRG).
The two products are available on a 4-km resolution polar-stereographic HRAP grid and are studied for the period from 2002 to 2012.
Grubbs-Beck Statistical test was used to identify the overestimated extreme events and consider them as outliers.
This test successfully removes most of the ring patterns, but it also deletes some of true extreme events which don’t seem to be artifacts.
The PDS in the Southeastern Coast after removing the outliers using Grubbs-Beck test
Stage IV QPE Product Vs. LMRFC Products
Some of the pixels, which show the ring pattern, are compared with the different LMRFC products and it was noticed that most of the overestimated values in the extreme series are due to gauges malfunctioning.
Stage IV Extreme Precipitation Series
For Stage IV QPE product, two extreme series are extracted; the annual maximum series (AMS) and the partial duration series (PDS).
Studying one of the rings in the
Southeastern Coast
The precipitation estimates in the ring under study with the corresponding date of occurrence
Comparing the precipitation estimates from Stage IV and LMRFC products
on October 5th in 2006 at 03 UTC
Preliminary Results for PFE Using LMRFC XMRG Product
The maximum estimates in the PDS over the CONUS domain for the period from 2002 to 2012
The maximum estimates over the CONUS domain in 2002
Artifacts Detected in Stage IV QPE Product
The two extreme series (AMS & PDS) show many rainfall estimates with very high values and most of these suspicious estimates are surrounded with lower estimates that form a ring pattern around some pixels.
10-year quantiles based on fitting
GEV distribution for each pixel in a domain
covering Louisiana State
25-year quantiles based on fitting
GEV distribution for each pixel in a domain
covering Louisiana State
PFE resulted from Pixel-based approach
for a pixel corresponding to Lafayette
( °, °)
Conclusions
The Stage IV real time data comprises some artifacts that should undergo some quality control operations to make it available for direct operational use.
It is recommended to use Multisensor Precipitation Reanalysis (MPR) to take full advantage of the additional rain gauge data that may not have been available in real time.
Ongoing work focuses on improving the estimation of PFE from radar QPE using different estimation techniques (e.g., index flood method and other regional-based approaches).
Acknowledgment
Stage IV QPE data were provided by NCAR/EOL under sponsorship of the National Science Foundation. (
LMRFC QPE products used in this study were provided by the Lower Mississippi River Forecast Center.
Artifacts detected in the PDS in the Southeastern Coast
Artifacts detected in the PDS in the Western Coast