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The impact of initial condition uncertainty (ICU) on quantitative precipitation forecasts (QPFs) is examined for a case of explosive cyclogenesis that occurred over the contiguous United States and produced widespread, substantial rainfall. The Pennsylvania State University-National Center for Atmospheric Research (NCAR) Mesoscale Model Version 4 (MM4), a limited-area model, is run at 80-km horizontal resolution and 15 layers to produce a 25-member, 36-h forecast ensemble. Lateral boundary conditions for MM4 are provided by ensemble forecasts from a global spectral model, the NCAR Community Climate Model Version 1 (CCM1). The initial perturbations of the ensemble members possess a magnitude and spatial decomposition that closely match estimates of global analysis error, but they are not dynamically conditioned. Results for the 80-km ensemble forecast are compared to forecasts from the then operational Nested Grid Model (NGM), a single 40-km/15layer MM4 forecast, a single 80-km/29-layer MM4 forecast, and a second 25-member MM4 ensemble based on a different cumulus parameterization and slightly different unperturbed initial conditions. Large sensitivity to ICU marks ensemble QPF. Extrema in 6-h accumulations at individual grid points vary by as much as 3.00Љ. Ensemble averaging reduces the root-mean-square error (rmse) for QPF. Nearly 90% of the improvement is obtainable using ensemble sizes as small as 8-10. Ensemble averaging can adversely affect the bias and equitable threat scores, however, because of its smoothing nature. Probabilistic forecasts for five mutually exclusive, completely exhaustive categories are found to be skillful relative to a climatological forecast. Ensemble sizes of approximately 10 can account for 90% of improvement in categorical forecasts relative to that for the average of individual forecasts. The improvements due to short-range ensemble forecasting (SREF) techniques exceed any due to doubling the resolution, and the error growth due to ICU greatly exceeds that due to different resolutions. If the authors' results are representative, they indicate that SREF can now provide useful QPF guidance and increase the accuracy of QPF when used with current analysis-forecast systems.

A "reforecast" (retrospective forecast) data set has been developed. This data set is comprised of a 15-member ensemble run out to two weeks lead. Forecasts have been run every day from 0000 UTC initial conditions from 1979 to present. The model is a 1998 version of the National Centers for Environmental Prediction's Global Forecast System (NCEP GFS) at T62 resolution. The 15 initial conditions consist of a reanalysis and seven pairs of bred modes.This data set facilitates a number of applications that were heretofore impossible.Model errors can be diagnosed from the past forecasts and corrected, thereby It is argued that the benefits of reforecasts are so large that they should become an integral part of the numerical weather prediction process. Methods for integrating reforecast approaches without seriously compromising the pace of model development are discussed.Users wishing to explore their own applications of reforecasts can download them through a web interface. 3 CAPSULE SUMMARY:Reforecasts (retrospective forecasts from the same model used operationally) can dramatically improve forecast skill through the statistical correction of the current forecast using the older forecasts.

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Forecasts from the National Centers for Environmental Prediction's experimental short-range ensemble system are examined and compared with a single run from a higher-resolution model using similar computational resources. The ensemble consists of five members from the Regional Spectral Model and 10 members from the 80-km Eta Model, with both in-house analyses and bred perturbations used as initial conditions. This configuration allows for a comparison of the two models and the two perturbation strategies, as well as a preliminary investigation of the relative merits of mixed-model, mixed-perturbation ensemble systems. The ensemble is also used to estimate the short-range predictability limits of forecasts of precipitation and fields relevant to the forecast of precipitation.Whereas error growth curves for the ensemble and its subgroups are in relative agreement with previous work for large-scale fields such as 500-mb heights, little or no error growth is found for fields of mesoscale interest, such as convective indices and precipitation. The difference in growth rates among the ensemble subgroups illustrates the role of both initial perturbation strategy and model formulation in creating ensemble dispersion. However, increase spread per se is not necessarily beneficial, as is indicated by the fact that the ensemble subgroup with the greatest spread is less skillful than the subgroup with the least spread.Further examination into the skill of the ensemble system for forecasts of precipitation shows the advantage gained from a mixed-model strategy, such that even the inclusion of the less skillful Regional Spectral Model members improves ensemble performance. For some aspects of forecast performance, even ensemble configurations with as few as five members are shown to significantly outperform the 29-km Meso-Eta Model.

Relationships between transient upper-tropospheric troughs and warm season convective activity over the southwest United States and northern Mexico are explored. Analysis of geopotential height and vorticity fields from the North American Regional Reanalysis and cloud-to-ground lightning data indicates that the passage of mobile inverted troughs (IVs) significantly enhances convection when it coincides with the peak diurnal cycle (1800-0900 UTC) over the North American monsoon (NAM) region. The preferred tracks of IVs during early summer are related to the dominant modes of Pacific sea surface temperature (SST) variability. When La Niñ a-like (El Niñ o-like) conditions prevail in the tropical Pacific and the eastern North Pacific has a horseshoe-shaped negative (positive) SST anomaly, IVs preferentially track farther north (south) and are slightly (typically one IV) more (less) numerous. These results point to the important role that synoptic-scale disturbances play in modulating the diurnal cycle of precipitation over the NAM region and the significant impact that the statistically supported low-frequency Pacific SST anomalies exert on the occurrence and track of these synoptic transients.

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