The need for reliable predictions in environmental modelling is long known. Particularly, the predicted weather and meteorological information about the future atmospheric state is crucial and necessary for almost all other areas of environmental modelling. Additionally, right decisions to prevent damages and save lives could be taken depending on a reliable meteorological prediction process. L...

The high altitude meteorological parameters include longitude, latitude, atmospheric pressure, temperature, humidity, etc., which are influenced between each parameter, therefore, it is very important to deal with and analyze these parameters. In this paper, we employ MATLAB software, research the basic algorithm of BP neural network, compare resilient BP algorithm, the FletcherReeves algorithm...

The main aim of this paper is to overcome the drawbacks of LIDAR which are non-linearity in climatic physics based on statistical modeling and evaluation. However, modeling is shown to be a successful method to forecast weather parameters by using different types of Soft Computing Techniques such as Neural Networks, Fuzzy Logic and Probability Theory which are suitable to these meteorological p...

In this study, an artificial neural network (ANN) based model for prediction of solar energy potential in Kuala Lumpur, Malaysia was developed. Standard multilayered, feed-forward, back-propagation neural networks were designed using Microsoft Excel (MS Excel). The meteorological data were acquired from Malaysia Meteorological Department. The data was consists of meteorological data from one st...

Stepwise multiple regression analyses are used t o explore the statistical (linear regression) relationships between satellite-observed earth-atmosphere emission spectra and meteorological parameters. The stepwise regression technique permits screening of a large number of potentially useful spectral observations (predictors) to isolate those few tha t contribute most to the explanation of the ...

In this study, using the tephra dispersal model HAZMAP, we investigate the effect of using different meteorological datasets and eruption source parameters on tephra fallout hazard assessment for a sub-Plinian eruption of Vesuvius, which is considered as a reference case for hazard assessment analysis. We analyze the effect of using different meteorological data, from: i) radio-sounding carried...

River forecasts have two broad uncertainty classes: errors associated with meteorological forecasts, and those associated with the hydrologic model. We developed a technology (dubbed Absynthe) to address the latter error class in a practical and defensible way. The technique merges the proven, Monte Carlo-based Generalized Likelihood Uncertainty Estimation (GLUE) concept for model parameter ide...

An empirical tropospheric delay model, together with a mapping function, is commonly used to correct the tropospheric errors in global navigation satellite system (GNSS) processing. As is well-known, the accuracy of tropospheric delay models relies mainly on the correction efficiency for tropospheric wet delays. In this paper, we evaluate the accuracy of three tropospheric delay models, togethe...