AFFILIATIONS: MCENERY—Water Resource Center, Texas Tech University, Lubbock, Texas; INGRAM—Office of Hydrologic Development, NOAA’s National Weather Service, Silver Spring, Maryland; DUAN— Lawrence Livermore National Laboratory, Livermore, California; ADAMS— Ohio River Forecast Center, NOAA’s National Weather Service, Wilmington, Ohio; ANDERSON—Office of Science and Technology, NOAA’s National ...

Weather prediction is a real time challenging issue witnessed by the world in the last decade. The prediction is becoming more complex due to the ever changing weather conditions. Many models have been discussed for predicting the weather data assuming the related attributes as independent variables. For effective analysis of the weather, it is necessary to understand various influencing factor...

Complex numerical weather prediction models incorporate a variety of physical processes, each described by multiple alternative physical schemes with specific parameters. The selection of the physical schemes and the choice of the corresponding physical parameters during model configuration can significantly impact the accuracy of model forecasts. There is no combination of physical schemes tha...

The verification of a gridded forecast field, for example, one produced by numerical weather prediction (NWP) models, cannot be performed on a gridpoint-by-gridpoint basis; that type of approach would ignore the spatial structures present in both forecast and observation fields, leading to misinformative or noninformative verification results. A variety of methods have been proposed to acknowle...

Through a collaborative partnership, principally among NCAR, NOAA, DoD, OU/CAPS, FAA, and universities, the U.S. modeling community is developing a next-generation mesoscale model, known as the Weather Research and Forecasting (WRF) model. The goals of the WRF project are to develop an advanced mesoscale forecast and data assimilation system and to accelerate research advances into operations. ...

High-resolution synthetic aperture radar (SAR) wind observations provide fine structural information for tropical cycles and could be assimilated into numerical weather prediction (NWP) models. However, in the conventional method assimilating the u and v components for SAR wind observations (SAR_uv), the wind direction is not a state vector and its observational error is not considered during t...

Diabatic initialization of cloud-resolving forecast models such as MM5, RAMS, ARPS, and WRF allows these models to prognose the future of precipitating cloud systems such as snowstorms and thunderstorms that are present at the initial time. This is a solution to one of the most long-standing problems in NWP: the 1to 3-h spin-up of cloud systems caused by the use of traditional dry initialization.

INTRODUCTION An accurate early warning system to predict impending epidemics enhances the effectiveness of preventive measures against dengue fever. The aim of this study was to develop and validate a forecasting model that could predict dengue cases and provide timely early warning in Singapore. METHODOLOGY AND PRINCIPAL FINDINGS We developed a time series Poisson multivariate regression mod...

Weather forecasting in Antarctica is essential for US Antarctic Program (USAP) operations. However, forecasting in this region is extremely difficult both because the observational and modeling tools available are inadequate and because our understanding of the science behind the meteorology of Antarctica is incomplete. The weather of Antarctica is dominated by three factors: (1) the polar high...

Weather is one of the major causes of general aviation accidents. Researchers are addressing this problem from various perspectives including improving meteorological forecasting techniques, collecting additional weather data automatically via on-board sensors and "flight" modems, and improving weather data dissemination and presentation. We approach the problem from the improved presentation p...