Verification of Land–Atmosphere Coupling in Forecast Models, Reanalyses, and Land Surface Models Using Flux Site Observations

An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations

Because land surface emissivity ( ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply constant, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, and 0.96 for bare soil as in the National Center for Atmospheric Research (NCAR) Commun...

Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures

3D Models Recognition in Fourier Domain Using Compression of the Spherical Mesh up to the Models Surface

Representing 3D models in diverse fields have automatically paved the way of storing, indexing, classifying, and retrieving 3D objects. Classification and retrieval of 3D models demand that the 3D models represent in a way to capture the local and global shape specifications of the object. This requires establishing a 3D descriptor or signature that summarizes the pivotal shape properties of th...

Ecopark Site Selection in the Central Cities of Ardabil Province, Using Multi-Criteria Analysis Models

Today, due to industrial advances and the expansion of urban environments, it is essential to create ecoparks as places that can provide natural environments for human. The current study performed a comparative ecopark site selection across Ardabil, Meshkinshahr, Sarein, Nir and Namin, using multi-criteria analysis models. To achieve the research objective, four criteria and 15 sub-criteria wer...

comparison of stochastic models and conceptual models in hydrological drought forecast (case study: karkheh river basin)

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...