David R. Bright

Some Practical Considerations Regarding Horizontal Resolution in the First Generation of Operational Convection-Allowing NWP

Abstract During the 2005 NOAA Hazardous Weather Testbed Spring Experiment two different high-resolution configurations of the Weather Research and Forecasting-Advanced Research WRF (WRF-ARW) model were used to produce 30-h forecasts 5 days a week for a total of 7 weeks. These configurations used the same physical parameterizations and the same input dataset for the initial and boundary conditions, differing primarily in their spatial resolution. The first set of runs used 4-km horizontal grid spacing with 35 vertical levels while the second used 2-km grid spacing and 51 vertical levels. Output from these daily forecasts is analyzed to assess the numerical forecast sensitivity to spatial resolution in the upper end of the convection-allowing range of grid spacing. The focus is on the central United States and the time period 18–30 h after model initialization. The analysis is based on a combination of visual comparison, systematic subjective verification conducted during the Spring Experiment, and objectiv...

Next-Day Convection-Allowing WRF Model Guidance: A Second Look at 2-km versus 4-km Grid Spacing

Abstract During the 2007 NOAA Hazardous Weather Testbed (HWT) Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced convection-allowing forecasts from a single deterministic 2-km model and a 10-member 4-km-resolution ensemble. In this study, the 2-km deterministic output was compared with forecasts from the 4-km ensemble control member. Other than the difference in horizontal resolution, the two sets of forecasts featured identical Advanced Research Weather Research and Forecasting model (ARW-WRF) configurations, including vertical resolution, forecast domain, initial and lateral boundary conditions, and physical parameterizations. Therefore, forecast disparities were attributed solely to differences in horizontal grid spacing. This study is a follow-up to similar work that was based on results from the 2005 Spring Experiment. Unlike the 2005 experiment, however, model configurations were more rigorously controlled in the present study, providing...

Examination of Convection-Allowing Configurations of the WRF Model for the Prediction of Severe Convective Weather: The SPC/NSSL Spring Program 2004

Abstract Convection-allowing configurations of the Weather Research and Forecast (WRF) model were evaluated during the 2004 Storm Prediction Center–National Severe Storms Laboratory Spring Program in a simulated severe weather forecasting environment. The utility of the WRF forecasts was assessed in two different ways. First, WRF output was used in the preparation of daily experimental human forecasts for severe weather. These forecasts were compared with corresponding predictions made without access to WRF data to provide a measure of the impact of the experimental data on the human decision-making process. Second, WRF output was compared directly with output from current operational forecast models. Results indicate that human forecasts showed a small, but measurable, improvement when forecasters had access to the high-resolution WRF output and, in the mean, the WRF output received higher ratings than the operational Eta Model on subjective performance measures related to convective initiation, evolutio...

Toward Improved Convection-Allowing Ensembles: Model Physics Sensitivities and Optimizing Probabilistic Guidance with Small Ensemble Membership

Abstract During the 2007 NOAA Hazardous Weather Testbed Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced a daily 10-member 4-km horizontal resolution ensemble forecast covering approximately three-fourths of the continental United States. Each member used the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model core, which was initialized at 2100 UTC, ran for 33 h, and resolved convection explicitly. Different initial condition (IC), lateral boundary condition (LBC), and physics perturbations were introduced in 4 of the 10 ensemble members, while the remaining 6 members used identical ICs and LBCs, differing only in terms of microphysics (MP) and planetary boundary layer (PBL) parameterizations. This study focuses on precipitation forecasts from the ensemble. The ensemble forecasts reveal WRF-ARW sensitivity to MP and PBL schemes. For example, over the 7-week experiment, the Mellor–Yamada–Janjic PBL and Ferrier M...

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...

Probabilistic Forecast Guidance for Severe Thunderstorms Based on the Identification of Extreme Phenomena in Convection-Allowing Model Forecasts

AbstractWith the advent of convection-allowing NWP models (CAMs) comes the potential for new forms of forecast guidance. While CAMs lack the required resolution to simulate many severe phenomena associated with convection (e.g., large hail, downburst winds, and tornadoes), they can still provide unique guidance for the occurrence of these phenomena if “extreme” patterns of behavior in simulated storms are strongly correlated with observed severe phenomena. This concept is explored using output from a series of CAM forecasts generated on a daily basis during the spring of 2008. This output is mined for the presence of extreme values of updraft helicity (UH), a diagnostic field used to identify supercellular storms. Extreme values of the UH field are flagged as simulated “surrogate” severe weather reports and the spatial correspondence between these surrogate reports and actual observed severe reports is determined. In addition, probabilistic forecasts [surrogate severe probabilistic forecasts (SSPFs)] are ...

The Emergence of Weather-Related Test Beds Linking Research and Forecasting Operations

Test beds have emerged as a critical mechanism linking weather research with forecasting operations. The U.S. Weather Research Program (USWRP) was formed in the 1990s to help identify key gaps in research related to major weather prediction problems and the role of observations and numerical models. This planning effort ultimately revealed the need for greater capacity and new approaches to improve the connectivity between the research and forecasting enterprise. Out of this developed the seeds for what is now termed “test beds.” While many individual projects, and even more broadly the NOAA/National Weather Service (NWS) Modernization, were successful in advancing weather prediction services, it was recognized that specific forecast problems warranted a more focused and elevated level of effort. The USWRP helped develop these concepts with science teams and provided seed funding for several of the test beds described. Based on the varying NOAA mission requirements for forecasting, differences in the orga...

Operational Forecaster Uncertainty Needs and Future Roles

Abstract Key results of a comprehensive survey of U.S. National Weather Service operational forecast managers concerning the assessment and communication of forecast uncertainty are presented and discussed. The survey results revealed that forecasters are using uncertainty guidance to assess uncertainty, but that limited data access and ensemble underdispersion and biases are barriers to more effective use. Some respondents expressed skepticism as to the added value of formal ensemble guidance relative to simpler approaches of estimating uncertainty, and related the desire for feature-specific ensemble verification to address this skepticism. Respondents reported receiving requests for uncertainty information primarily from sophisticated users such as emergency managers, and most often during high-impact events. The largest request for additional training material called for simulator-based case studies that demonstrate how uncertainty information should be interpreted and communicated. Respondents were i...

Value of Human-Generated Perturbations in Short-Range Ensemble Forecasts of Severe Weather

Abstract During the spring of 2003, the Storm Prediction Center, in partnership with the National Severe Storms Laboratory, conducted an experiment to explore the value of having operational severe weather forecasters involved in the generation of a short-range ensemble forecasting system. The idea was to create a customized ensemble to provide guidance on the severe weather threat over the following 48 h. The forecaster was asked to highlight structures of interest in the control run and, using an adjoint model, a set of perturbations was obtained and used to generate a 32-member fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) ensemble. The performance of this experimental ensemble is objectively evaluated and compared with other available forecasts (both deterministic and ensemble) using real-time severe weather reports and precipitation in the central and eastern parts of the continental United States. The experimental ensemble outperforms t...