Prediction of annual average precipitation over a regin is one of important issues in watersherd management and natural resources planning. Geostatistics is one of the useful methods for precipitation prediction which varies based on type of the variable. This study was conducted in Karoon and Dez Basins located in southwertern of Iran. The data set including 20 years of annual precipitation of...

Climate generator (CLIGEN) is widely used in the United States to generate long-term climate scenarios for use with agricultural systems models. Its applicability needs to be evaluated for use in a new region or climate. The objectives were to: (1) evaluate the reproducibility of the latest version of CLIGEN v5.22564 in generating daily, monthly, and yearly precipitation depths at 12 stations, ...

comparison of linear and nonlinear (bilinear) time series models in reference crop evapotranspiration prediction in urmia synoptic stationreference crop evapotranspiration (eto) prediction is one of the important elements in optimizing agricultural water consumption. in this regard, one of the prediction approaches is to use the stochastic time series methods. in this research, ar (p) and arma(...

Topography is a significant factor influencing the spatial distribution of precipitation. This study developed a new methodology to evaluate and calibrate the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) products by merging geographic and topographic information. In the proposed method, firstly, the consistency rule was introduced to evaluate the fitness of ...

â â â  in this study, ability and skill of the nesting version of the regcm3 regional climate model in simulation of monthly and seasonal amount of precipitation and temperature using four different cumulus parameterization of grell-as, grell-fc, emanuel and kuo have been studied over khorasan area including three provinces of north khorasan, khorasan razavi and south khorasan. in this regards,...

Different prediction models (multiple linear regression, vector support machines, artificial neural networks and random forests) are applied to model the monthly global irradiation (MGI) from different input variables (latitude, longitude altitude of meteorological station, month, average temperatures, among others) areas Galicia (Spain). The were trained, validated queried using data three sta...

Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron MLP neural network. The MLP architecture was optimize...

New online prototypes have been developed to extend and enhance the previous effort by facilitating investigation of product characteristics and intercomparison of precipitation products in different algorithms as well as in different versions at different spatial scales ranging from local to global without downloading data and software. Several popular Tropical Rainfall Measuring Mission (TRMM...

Local dry/wet conditions are of great concern in regional water resource and floods/droughts disaster risk management. Satellite-based precipitation products have greatly improved their accuracy and applicability and are expected to offer an alternative to ground rain gauges data. This paper investigated the capability of Tropical Rainfall Measuring Mission (TRMM) rainfall data for monitoring t...

The objective of this study is to produce an observationally based monthly evapotranspiration (ET) product using the simple water balance equation across the conterminous United States (CONUS). We adopted the best quality ground and satellite-based observations of the water budget components, i.e., precipitation, runoff, and water storage change, while ET is computed as the residual. Precipitat...