Evaluation of Heavy Precipitation Forecasts Using Composite-Based Methods: A Distributions-Oriented Approach
Open Access
- 1 August 2005
- journal article
- Published by American Meteorological Society in Monthly Weather Review
- Vol. 133 (8) , 2163-2177
Abstract
Numerical forecasts of heavy warm-season precipitation events are verified using simple composite collection techniques. Various sampling methods and statistical measures are employed to evaluate the general characteristics of the precipitation forecasts. High natural variability is investigated in terms of its effects on the relevance of the resultant statistics. Natural variability decreases the ability of a verification scheme to discriminate between systematic and random error. The effects of natural variability can be mitigated by compositing multiple events with similar properties. However, considerable sample variance is inevitable because of the extreme diversity of mesoscale precipitation structures. The results indicate that forecasts of heavy precipitation were often correct in that heavy precipitation was observed relatively close to the predicted area. However, many heavy events were missed due in part to the poor prediction of convection. Targeted composites of the missed events ind... Abstract Numerical forecasts of heavy warm-season precipitation events are verified using simple composite collection techniques. Various sampling methods and statistical measures are employed to evaluate the general characteristics of the precipitation forecasts. High natural variability is investigated in terms of its effects on the relevance of the resultant statistics. Natural variability decreases the ability of a verification scheme to discriminate between systematic and random error. The effects of natural variability can be mitigated by compositing multiple events with similar properties. However, considerable sample variance is inevitable because of the extreme diversity of mesoscale precipitation structures. The results indicate that forecasts of heavy precipitation were often correct in that heavy precipitation was observed relatively close to the predicted area. However, many heavy events were missed due in part to the poor prediction of convection. Targeted composites of the missed events ind...Keywords
This publication has 16 references indexed in Scilit:
- A Description of the Impact of Changes to NOGAPS Convection Parameterization and the Increase in Resolution to T239L302002
- Does Increasing Horizontal Resolution Produce More Skillful Forecasts?Bulletin of the American Meteorological Society, 2002
- Verification of precipitation in weather systems: determination of systematic errorsJournal of Hydrology, 2000
- Space‐time rainfall organization and its role in validating quantitative precipitation forecastsJournal of Geophysical Research: Atmospheres, 2000
- Short-Term Forecast Validation of Six ModelsWeather and Forecasting, 1999
- The Naval Research Laboratory’s Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS)Monthly Weather Review, 1997
- Distortion Representation of Forecast ErrorsMonthly Weather Review, 1995
- Evaluation of 33 Years of Quantitative Precipitation Forecasting at the NMCWeather and Forecasting, 1995
- Convective Parameterization for Mesoscale Models: The Kain-Fritsch Scheme1993
- Design of the Navy's Multivariate Optimum Interpolation Analysis SystemWeather and Forecasting, 1992