Journal article
Statewide real-time quantitative precipitation estimation using weather radar and NWP model analysis: Algorithm description and product evaluation
Environmental modelling & software : with environment data news, Vol.132, p.104791
10/2020
DOI: 10.1016/j.envsoft.2020.104791
Abstract
This study describes an automated system that generates a statewide real-time quantitative precipitation estimation (QPE) product for flood forecasting in Iowa. The QPE system comprises, real-time data acquisition, processing, and product visualization subsystems. Combined with information retrieved from numerical weather prediction, the system processes data from multiple radars using various algorithms accounting for precipitation microphysics and radar remote sensing uncertainties. The system generates a composite rainfall map covering the entire state of Iowa at a resolution of 0.5 km, updated every 5 min. With the help of the system's flexible modular configuration, we have recently added a new polarimetric algorithm based on specific attenuation. Independent evaluations based on comparisons with rain gauge data and hydrologic model prediction of streamflow demonstrate that the new implementation significantly improves the rainfall estimation accuracy. The new QPE product shows performance comparable to the Multi-Radar Multi-Sensor product that contains a rain gauge correction.
•An automated QPE system generates a statewide real-time rainfall product for flood forecasting in Iowa.•The system processes NWP and radar data using algorithms accounting for precipitation microphysics and QPE uncertainties.•The system generates a rainfall map covering the entire state of Iowa at a resolution of 0.5 km, updated every 5 min.•The evaluation demonstrates that a new algorithm implementation significantly improves the rainfall estimation accuracy.
Details
- Title: Subtitle
- Statewide real-time quantitative precipitation estimation using weather radar and NWP model analysis: Algorithm description and product evaluation
- Creators
- Bong-Chul SeoWitold F Krajewski
- Resource Type
- Journal article
- Publication Details
- Environmental modelling & software : with environment data news, Vol.132, p.104791
- DOI
- 10.1016/j.envsoft.2020.104791
- ISSN
- 1364-8152
- eISSN
- 1873-6726
- Publisher
- Elsevier Ltd
- Grant note
- DOI: 10.13039/100000192, name: National Oceanic and Atmospheric Administration
- Language
- English
- Date published
- 10/2020
- Academic Unit
- Civil and Environmental Engineering; IIHR--Hydroscience and Engineering
- Record Identifier
- 9984066338502771
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