The development of the adjoint of the forecast model and of the adjoint of the data assimilation system (adjointDAS) make feasible the evaluation of the derivative-based forecast sensitivity to DAS input parameters in numerical weather prediction (NWP). The adjoint estimation of the forecast sensitivity to the observation error covariance in the DAS is considered as a practical approach to prov...

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...

Information on land surface temperature (LST) is important for understanding climate change, modeling the hydrological and biogeochemical cycles, and is a prime candidate parameter for Numerical Weather Prediction assimilation models. In particular, the LST data derived from geostationary operational environmental satellite (GOES) provides unique opportunity for studying LST diurnal variation. ...

in the developing countries, where introduction and subsequent adoption of improved technologies is too slow to counteract the adverse effects of varying environmental conditions, there are increasing demands for meteorological information by farmers who are seriously in need of weather forecast information for their prompt operational decisions. the purpose of this study was to determine 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,...

Ensemble forecasting is used in numerical weather prediction to give an improved estimate of the atmospheric state and to improve measures of forecast accuracy. While the method is effective, there are some fundamental issues in interpreting the ensemble as a statistically valid representation of uncertainty in the state of the atmosphere. Coupled with this interpretation is the difficulty in t...

The two official sources for aviation weather reports both provide weather information to a pilot in a textual format. A number of systems have recently become available to help pilots with the visualization task by providing much of the data graphically. However, two types of aviation weather data are still not being presented graphically. These are airport-specific current weather reports (kn...

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 ...

It is important to forecast the pedestrian flows for organizing crowd activities and making risk assessments. In this article, the daily pedestrian flows in the Tiananmen Square are forecasted based on historical data, the distribution of holidays and weather conditions including rain, wind, temperature, relative humidity, and AQI (Air Quality Index). Three different methods have been discussed...