Characteristics of warm season precipitating storms in the Arkansas–Red River basin

[1] Analysis of a multisensor precipitation product enables us to extract the precipitation from individual storms in the Arkansas–Red River drainage basin over a period of 11 years. We examine the year-to-year and intraseasonal variations of storm numbers, duration, sizes, and precipitation in the data set. Intraseasonal variations in numbers of storms exceed their year-to-year variations. More mountainous regions had greater numbers of storms than flatter regions. Most storms are small, last less than 2 h, and produce modest amounts of precipitation. The maximum size of storms and the number of storms are negatively correlated on a yearly basis. Midsummer months had a greater percentage of smaller storms but the storms were of longer average duration. We can roughly divide the storms into three different types, single ordinary cell storms, multiple storms (includes supercells), and mesoscale convective systems, and look at their year to year and intraseasonal variability in the data set. The most storms occur around 1700 local time but the most precipitation falls around 0100 local time. Storm duration was the most important factor determining how much precipitation storms generate per cell. We do not find that drought years or years with abundant precipitation had any particular characteristics but occur as a result of simultaneous occurrence of several features.

[1]  Mesoscale Convective Systems , 2001 .

[2]  D. R. Easterling,et al.  The Frequency Distribution of Thunderstorm Durations , 1988 .

[3]  James E. Hocker,et al.  A 10‐year spatial climatology of squall line storms across Oklahoma , 2008 .

[4]  Charles A. Doswell,et al.  Severe Convective Storms , 2001 .

[5]  Roscoe R. Braham,et al.  THE WATER AND ENERGY BUDGETS OF THE THUNDERSTORM AND THEIR RELATION TO THUNDERSTORM DEVELOPMENT , 1952 .

[6]  Witold F. Krajewski,et al.  Estimation of the mean field bias of radar rainfall estimates , 1991 .

[7]  Zong‐Liang Yang,et al.  Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event. , 2005, Journal of environmental management.

[8]  Dong-Jun Seo,et al.  Real-time estimation of mean field bias in radar rainfall data , 1999 .

[9]  T. Glickman,et al.  Glossary of Meteorology , 2000 .

[10]  Walker S. Ashley,et al.  Distribution of Mesoscale Convective Complex Rainfall in the United States , 2003 .

[11]  Emmanouil N. Anagnostou,et al.  Uncertainty Quantification of Mean-Areal Radar-Rainfall Estimates , 1999 .

[12]  Timothy D. Euler,et al.  2.4 EFFECT OF ATMOSPHERIC HYDROMETEORS ON MILLIMETER WAVE TRANSMISSIONS , 2008 .

[13]  Witold F. Krajewski,et al.  Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting , 2000 .

[14]  Yuh-Lang Lin,et al.  Mesoscale Dynamics: Contents , 2007 .

[15]  J. Fritsch,et al.  The Contribution of Mesoscale Convective Weather Systems to the Warm-Season Precipitation in the United States , 1986 .

[16]  R. Scofield,et al.  Precipitation Efficiency of Warm-Season Midwestern Mesoscale Convective Systems , 2003 .

[17]  S. Changnon Thunderstorm Rainfall in the Conterminous United States , 2001 .

[18]  Victor Koren,et al.  Comparing Mean Areal Precipitation Estimates from NEXRAD and Rain Gauge Networks , 1999 .

[19]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[20]  W. Krajewski,et al.  A large-sample investigation of statistical procedures for radar-based short-term quantitative precipitation forecasting , 2000 .

[21]  Dong-Jun Seo,et al.  The WSR-88D rainfall algorithm , 1998 .

[22]  C. W. Newton Circulations in large sheared cumulonimbus , 1966 .

[23]  Jeffrey B. Basara,et al.  A Geographic Information Systems-Based Analysis of Supercells across Oklahoma from 1994 to 2003 , 2008 .

[24]  Witold F. Krajewski,et al.  Radar hydrology: rainfall estimation. , 2002 .

[25]  Charles A. Doswell,et al.  Severe Convective Storms—An Overview , 2001 .

[26]  S. Lakshmivarahan,et al.  Development of an Automated Classification Procedure for Rainfall Systems , 2005 .