Simplifications used in regional climate models decrease the accuracy of the regional climate models. To overcome this deficiency, usually a statistical technique of MOS is used to improve the skill of gridded outputs of the Numerical Weather Prediction (NWP) models. In this paper, an experimental synoptic-climatology based method has been used to calibrate, and decrease amount of errors in GFS...

I n 2003, the Meteorological Service of Canada (MSC) began a significant restructuring of its forecasting operations in response to financial pressures. Senior management proposed that the MSC could be made more cost effective while continuing to provide quality services by pursuing a more centralized forecasting approach and increasing the automation of forecasts via numerical weather predicti...

Manual surface measurements have traditionally formed the basis for hydrometeorological observation networks. Although automation and real-time data communication has gradually increased, sufficient area coverage for minimizing uncertainties associated with spatial averaging of hydrometeorological variables is still relatively rare. The limited availability of real-time precipitation data for t...

The long-term goal of this project is to develop robust global and mesoscale ensemble analysis and forecast systems that are able to provide probabilistic forecast guidance in an operational environment. Although most operational centers rely solely on single deterministic forecasts from numerical weather prediction models, recent advances in probabilistic prediction, or ensemble forecasting, h...

Short-range forecasts of precipitation fields are required in a wealth of agricultural, hydrological, ecological and other applications. Forecasts from numerical weather prediction models are often biased and do not provide uncertainty information. Here we present a postprocessing technique for such numerical forecasts that produces correlated probabilistic forecasts of precipitation accumulati...

The accurate parameterization of moist convection presents a major challenge for the accurate prediction of weather and climate through numerical models. Superparameterization is a promising recent alternative strategy for including the effects of moist convection through explicit turbulent fluxes calculated from a cloud-resolving model. Basic scales for cloud-resolving modeling are the microsc...

Numerical Weather Prediction (NWP) and climate simulations have been intimately connected with progress in supercomputing since the first numerical forecast wasmade about 65 years ago. The biggest challenge to state-of-the-art computational NWP arises today from its own software productivity shortfall. The application software at the heart of most NWP services is ill-equipped to efficiently ada...