Abstract: esoscale atmospheric data assimilation is becoming an integral part of numerical weather prediction. Modern computational resources now allow assimilation and subsequent forecasting experiments ranging from resolutions of ...

Abstract: nsemble sensitivity can reveal features in the flow at early forecast times that are relevant to the predictability of chosen high-impact forecast aspects (e.g., heavy precipitation) later in time. In an operational ...

Abstract: nsemble forecasting is becoming an increasingly important aspect of numerical weather prediction. As ensemble perturbation evolution becomes more nonlinear as a forecast evolves, the ensemble mean can diverge from the model ...

Abstract: ind ramps present a significant challenge to the wind energy industry and are a source of inefficiency for wind farm owners and power grid operators. One approach to investigating wind ramp predictability is ensemble ...

Abstract: Adjoint sensitivity fields have generally been viewed deterministically in the atmospheric science literature. However, uncertainty exists in the components of the adjoint model, such as the physics and the basic-state ...

Abstract: orecast sensitivity of an April 2012 severe convection event in northern Texas is investigated with a high-resolution Weather Research and Forecasting (WRF) Model?based ensemble Kalman filter (EnKF). Through ensemble ...

Abstract: In this paper, the variation of adjoint sensitivities as horizontal and vertical resolutions are changed is investigated. The fifth-generation Pennsylvania State University?National Center for Atmospheric Research (PSU?NCAR) ...

Abstract: he use of ensembles in numerical weather prediction models is becoming an increasingly effective method of forecasting. Many studies have shown that using the mean of an ensemble as a deterministic solution produces the ...