Decision support systems for weather forecasting have yet to tackle the key issues in formulating forecast policy, focussing instead on data presentation. Here we describe a method for eliciting forecasting information and outline a forecast ontology for codifying that information as a data management tool. The completed ontology will provide key ingredients for designing future decision suppor...

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather warning system is used. The work reported here test...

Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time. The growth of errors depends on the f...

Ensembles of forecasts are typically employed to account for the forecast uncertainties inherent in predictions of future weather states. However, biases and dispersion errors often present in forecast ensembles require statistical post-processing. Univariate post-processing models such as Bayesian model averaging (BMA) have been successfully applied for various weather quantities. Nonetheless,...

The meaning of probabilistic weather forecasts is discussed from the point of view of a subjectivist concept of probability. The prior degree of belief of probabilities of the weather in question, for a given forecast statement, is expressed analytically as a beta function. Bzyes’ theorem is used to modify this degree of belief in the light of experience, producing a posterior degree of belief ...

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...

A preliminary verification and evaluation is made of the forecast fields of the non-hydrostatic limited area model LME of the German Weather Service (DWD), for a recent three month period. For this purpose, observations from two synoptic stations in Cyprus are utilized. In addition, days with depressions over the area were selected in order to evaluate the model’s forecast skill in storm foreca...

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studie...

In order to provide an uncertainty estimate for short-term wind power predictions the accuracy of the underlying wind speed prediction is assessed quantitatively for different meteorological situations. With methods from synoptic climatology an automatic classification scheme is implemented using measurements of wind speed, wind direction and pressure at mean sea level to characterize the local...

The evaluation of weather forecast accuracy has always been a difficult subject to address for many reasons. In this study, a simple semiobjective method is used to examine the accuracy of zone forecasts issued by the Weldon Spring (Saint Louis) National Weather Service (NWS) Office for mid-Missouri over a period of 416 days with the goal of demonstrating the utility of this method. Zone foreca...