In this paper we present a novel approach (SDSM) that incorporates structure in distributional semantics. SDSM represents meaning as relation specific distributions over syntactic neighborhoods. We empirically show that the model can effectively represent the semantics of single words and provides significant advantages when dealing with phrasal units that involve word composition. In particula...

The coupling of hydrological distributed models to numerical weather prediction outputs is an important issue for hydrological applications such as forecasting of flood events. Downscaling meteorological predictions to the hydrological scales requires the resolution of two fundamental issues regarding precipitation, namely, (1) understanding the statistical properties and scaling laws of rainfa...

To assess a species' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved...

abstract due to low spatial resolution or simplifying of some micrometeorological phenomena, atmospheric general circulation models are not able to give a good estimation for weather conditions over study area. so their outputs should downscale into weather stations scales. in this research data of hadcm3 downscaled by using lars-wg5 with three scenarios, confirmed by ipcc including a1b, a2 and...

a methodology is presented for the stochastic generation of daily rainfall which accounts for changes to the climatic inputs. the focus of the study is an example catchment in iran. the methodology addresses the inability of gcms to provide suitable future scenarios for the time and space scales required for a water resource impact assessment for a small catchment. one stochastic model for rain...

A comparison of two statistical downscaling methods for daily maximum and minimum surface air temperature, total daily precipitation and total monthly precipitation at Indianapolis, IN, USA, is presented. The analysis is conducted for two seasons, the growing season and the non-growing season, defined based on variability of surface air temperature. The predictors used in the downscaling are in...