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: The sensitivity of numerical weather forecasts to small changes in initial conditions is estimated using ensemble samples of analysis and forecast errors. Ensemble sensitivity is defined here by linear regression of analysis ...

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: he predictability of North Pacific cyclones can vary widely, from highly accurate prediction of storm intensity and location to forecast position errors of hundreds of kilometers and central pressure errors of tens of ...

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 ...