Short-range forecasts of precipitation fields are needed 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 accumulation...

The use of state-of-the-art hyperspectral sensors--such as the Atmospheric InfraRed Sounder (AIRS) on NASA’s polar-orbiting Aqua satellite--to retrieve high vertical resolution thermodynamic profiles and their subsequent assimilation into forecast models holds promise in improving weather predictions. This improved vertical resolution over previous capabilities results from the use of thousands...

ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for MediumRange Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanaly...

Probabilistic forecasts of wind speed are becoming critical as interest grows in wind as a clean and renewable source of energy, in addition to a wide range of other uses, from aviation to recreational boating. Statistical approaches to wind forecasting offer two particular challenges: the distribution of wind speeds is highly skewed, and wind observations are reported to the nearest whole knot...

Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF) temperature and wind...

For many applications, expected local weather conditions during the next day or two are critical factors in planning operations and making effective decisions. Typically, what optimization that is applied to these processes to enable proactive efforts utilize either historical weather data as a predictor of trends or the results of synoptic-scale weather models. Alternatively, mesos-cale numeri...

The accuracy of numerical weather forecasts is crucial in many engineering applications, especially for the management of renewable energy. In this paper, we give a short overview of methods used to improve local weather forecast. Then we propose a new state space model in order to correct bias and phase errors in numerical wind forecasts. We present some results for real life data.

The results of recent studies on prediction markets are encouraging. Prior experience demonstrates that markets with different incentive schemes predicted uncertain future events at a remarkable accuracy. In this paper, we study the impact of different monetary incentives on the prediction accuracy in a field experiment. In order to do so, we compare three groups of users, corresponding to thre...