Editorial Type:
Article
Article Type:
Research Article

Warm Season Mesoscale Superensemble Precipitation Forecasts in the Southeastern United States

T. J. Cartwright West Virginia State University, and West Virginia State Community and Technical College, Institute, West Virginia

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T. N. Krishnamurti The Florida State University, Tallahassee, Florida

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Print Publication:
01 Aug 2007
DOI:
https://doi.org/10.1175/WAF1023.1
Page(s):
873–886
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Abstract

With current computational limitations, the accuracy of high-resolution precipitation forecasts has limited temporal and spatial resolutions. However, with the recent development of the superensemble technique, the potential to improve precipitation forecasts at the regional resolution exists. The purpose of this study is to apply the superensemble technique to regional precipitation forecasts to generate more accurate forecasts pinpointing exact locations and intensities of strong precipitation systems. This study will determine the skill of a regional superensemble forecast out to 60 h by examining its equitable threat score and its false alarm ratio. The regional superensemble consists of 12–60-h daily quantitative precipitation forecasts from six models. Five are independent operational models, and one comes from the physically initialized Florida State University regional spectral model. The superensemble forecasts are verified during the summer 2003 season over the southeastern United States using merged River Forecast Center stage-IV radar–gauge and satellite analyses. Precipitation forecasts were skillful in outperforming the operational models at all model times. Precipitation results were stratified by time of day to allow detections of the diurnal cycle. As expected, warm season daytime precipitation is commonly forced by convection, which is difficult to accurately model. Major synoptic regimes, including subtropical highs, midlatitude troughs/fronts, and tropical cyclones, were examined to determine the skill of the superensemble under various synoptic conditions.

* Current affiliation: MU-ADVANCE Program, Marshall University, Huntington, West Virginia

Corresponding author address: Dr. Tina J. Cartwright, MU-ADVANCE Program, Marshall University, 241J Byrd Biotech Center, Huntington, WV 25755. Email: johnson516@marshall.edu

Abstract

With current computational limitations, the accuracy of high-resolution precipitation forecasts has limited temporal and spatial resolutions. However, with the recent development of the superensemble technique, the potential to improve precipitation forecasts at the regional resolution exists. The purpose of this study is to apply the superensemble technique to regional precipitation forecasts to generate more accurate forecasts pinpointing exact locations and intensities of strong precipitation systems. This study will determine the skill of a regional superensemble forecast out to 60 h by examining its equitable threat score and its false alarm ratio. The regional superensemble consists of 12–60-h daily quantitative precipitation forecasts from six models. Five are independent operational models, and one comes from the physically initialized Florida State University regional spectral model. The superensemble forecasts are verified during the summer 2003 season over the southeastern United States using merged River Forecast Center stage-IV radar–gauge and satellite analyses. Precipitation forecasts were skillful in outperforming the operational models at all model times. Precipitation results were stratified by time of day to allow detections of the diurnal cycle. As expected, warm season daytime precipitation is commonly forced by convection, which is difficult to accurately model. Major synoptic regimes, including subtropical highs, midlatitude troughs/fronts, and tropical cyclones, were examined to determine the skill of the superensemble under various synoptic conditions.

* Current affiliation: MU-ADVANCE Program, Marshall University, Huntington, West Virginia

Corresponding author address: Dr. Tina J. Cartwright, MU-ADVANCE Program, Marshall University, 241J Byrd Biotech Center, Huntington, WV 25755. Email: johnson516@marshall.edu

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