Steven L. Mullen

REFORECASTS An Important Dataset for Improving Weather Predictions

A “reforecast” (retrospective forecast) dataset has been developed. This dataset is comprised of a 15-member ensemble run out to a 2-week lead. Forecasts have been run every day from 0000 UTC initial conditions from 1979 to the present. The model is a 1998 version of the National Centers for Environmental Predictions (NCEPs) Global Forecast System (GFS) at T62 resolution. The 15 initial conditions consist of a reanalysis and seven pairs of bred modes. This dataset facilitates a number of applications that were heretofore impossible. Model errors can be diagnosed from the past forecasts and corrected, thereby dramatically increasing the forecast skill. For example, calibrated precipitation forecasts over the United States based on the 1998 reforecast model are more skillful than precipitation forecasts from the 2002 higher-resolution version of the NCEP GFS. Other applications are also demonstrated, such as the diagnosis of the bias for model development and an identification of the most predictable patt...

Short-Range Ensemble Forecasting of Quantitative Precipitation

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 3.000. 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.

Water Vapor Transport Associated with the Summertime North American Monsoon as Depicted by ECMWF Analyses

Abstract The origins and transport of water vapor into the semi-arid Sonoran Desert region of southwestern North America are examined for the July–August wet season. Vertically integrated fluxes and flux divergences of water vapor are computed for the 8 summers 1985–1992 from ECMWF mandatory level analyses possessing a spectral resolution of triangular 106 (T106). The ECMWF analyses indicate that transports of water vapor by the time-mean flow dominate the transports by the transient eddies. Most of the moisture at upper levels (above 700 mb) over the Sonoran Desert arrives from over the Gulf of Mexico, while most moisture at low levels (below 700 mb) comes from the northern Gulf of California. There is no indication of moisture entering the Sonoran Desert at low levels directly from the southern Gulf of California or the tropical East Pacific. Water vapor from the tropical East Pacific can enter the region at upper levels after upward transport from low levels along the western slopes of the Sierra Madre...

Model Climatology of the Mexican Monsoon

Abstract The Mexican monsoon is a significant feature in the climate of the southwestern United States and Mexico during the summer months. Rainfall in northwestern Mexico during the months of July through September accounts for 60% to 80% of the total annual rainfall, while rainfall in Arizona for these same months accounts for over 40% of the total annual rainfall. Deep convection during the monsoon season produces frequent damaging surface winds, flash flooding, and hail and is a difficult forecast problem. Past numerical simulations frequently have been unable to reproduce the widespread, heavy rains over Mexico and the southwestern United States associated with the monsoon. The Pennsylvania State University/National Center for Atmospheric Research mesoscale model is used to simulate 32 successive 24-h periods during the monsoon season. Mean fields produced by the model simulations are compared against observations to validate the ability of the model to reproduce many of the observed features, includ...

Quantitative Precipitation Forecasts over the United States by the ECMWF Ensemble Prediction System

Abstract The performance of the ECMWF Ensemble Prediction System (EPS) is assessed for probabilistic forecasts of 24-h accumulated precipitation over the eastern United States. Daily forecasts for the period 1 January 1997 to 31 January 1999 are verified for projections of 1–10 days. Verification is performed separately for the cool and warm seasons, and the impact of changes to the EPS that occurred during the study period is assessed. Analyses of rain gauge data from the River Forecast Centers of NOAA are used for verification. Skill is measured relative to long-term climatic frequencies, and the statistical significance of differences in the accuracy and skill among forecasts is estimated. Overall, EPS forecasts are more skillful during the winter than the summer. The EPS produces significantly skillful forecasts to past 1 week for a threshold of 1 mm in both seasons. Accuracy decreases as the threshold increases, until forecasts of 50 mm are not significantly skillful at 1 day. The implementation of e...

Evaluation of a short-range multimodel ensemble system

Abstract 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, s...

The Sensitivity of the Numerical Simulation of the Southwest Monsoon Boundary Layer to the Choice of PBL Turbulence Parameterization in MM5

Summertime convection over Arizona typically begins in the early afternoon and continues into the night. This suggests that the evolution of the daytime planetary boundary layer is important to the development of Arizona convection. If numerical models are to provide useful guidance for forecasting convection during the monsoon, then the planetary boundary layer must be simulated as accurately as possible through utilization of the appropriate physical parameterizations. This study examines the most appropriate Pennsylvania State University‐National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5) planetary boundary layer parameterization(s) for deterministic and ensemble modeling of the monsoon. The four MM5 planetary boundary layer parameterizations tested are the Blackadar, Burk‐Thompson, Eta, and medium-range forecast (MRF) schemes. The Blackadar and MRF planetary boundary layer schemes correctly predict the development of the deep, monsoon planetary boundary layer, and consequently do a better job of predicting the convective available potential energy and downdraft convective available potential energy, but not the convective inhibition. Because the convective inhibition is not accurately predicted, it is possible that the MM5’s ability to initiate or ‘‘trigger’’ convection might be a limiting factor in the model’s ability to produce accurate quantitative precipitation forecasts during the monsoon. Since the MM5 planetary boundary layer predicted by the Burk‐Thompson and Eta schemes does not accurately reproduce the basic structure of the monsoon planetary boundary layer, their inclusion in a mixed physics ensemble is discussed.

Short-Range Ensemble Forecasts of Precipitation during the Southwest Monsoon

Abstract The skill and potential value of fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) ensembles are evaluated for short-range (24 h) probabilistic quantitative precipitation forecasts over Arizona during the Southwest monsoon. The sensitivity of different ensemble constructs is examined with respect to analysis uncertainty, model parameterization uncertainty, and a combination of both. Model uncertainty is addressed through different cumulus and planetary boundary layer parameterizations and through stochastic forcing representative of a component of subgrid-scale uncertainty, in which a first-order autoregression model adds a stochastic perturbation to the Kain–Fritsch cumulus scheme and Medium-Range Forecast Model PBL scheme. The results indicate that the precipitation forecasts are skillful and may assist operational weather forecasters during the monsoon; however, the forecasts are highly dependent on the cumulus parameterization. The a...

Ensemble Forecasting in the Short to Medium Range: Report from a Workshop

Contributors of meeting summaries to the Bulletin now have an option to have their summaries published within a quicker time frame than has previously been offered. To take advantage of this expedited publication process, these articles must be brief (no more than 24 manuscript pages), tightly written, and cannot contain tables, figures, or displayed mathematics. Furthermore, the meeting summary must be externally reviewed by at least one individual who attended the same meeting. This reviewer will be of the author’s choosing; this represents a departure from the conventional peer-review process.

The Impact of Horizontal Resolution and Ensemble Size on Probabilistic Forecasts of Precipitation by the ECMWF Ensemble Prediction System

Abstract The effect of horizontal resolution and ensemble size on the ECMWF Ensemble Prediction System (EPS) is assessed for probabilistic forecasts of 24-h accumulated precipitation. Two sets of experiments are analyzed. The primary experiment compares two spectral truncations (total wavenumbers 159 and 255) for 30 summer and 57 winter dates. An auxiliary experiment compares three truncations (total wavenumbers 159, 255, and 319) for 16 initial dates (8 cool- and 8 warm-season events) during which heavy precipitation (>50 mm) occurred over the eastern United States at day 5 of the forecast. Rain gauge data from the River Forecast Centers of NOAA are used for verification. Skill is measured relative to long-term climatic frequencies, and the statistical significance of differences in the accuracy among the forecasts is estimated. Finer model resolution produces statistically significant improvements in EPS performance for ensemble configurations with the same number of members, especially for lighter thre...