AbstractThis paper describes a versatile stochastic daily weather generator (WeaGETS) for producing daily precipitation, maximum and minimum temperatures (Tmax and Tmin). The performance of WeaGETS is demonstrated with respect to the generation of precipitation, Tmax and Tmin for two Canadian meteorological stations. The results show that the widely used first-order Markov model is adequate for producing precipitation occurrence, but it underestimates the longest dry spell for dry station. The higher-order models have positive effects. The gamma distribution is consistently better than the exponential distribution at generating precipitation quantity. The conditional scheme is good at simulating Tmax and Tmin. The spectral correction approa...
Abstract: This article reviews the historical development of statistical weather models, from simple...
Weather Generators (WGs) are widely used in water engineering, agriculture, ecosystem and climate ch...
Traditional stochastic approaches for synthetic generation of weather variables often assume a prior...
AbstractThis paper describes a versatile stochastic daily weather generator (WeaGETS) for producing ...
WeaGETS is a MATLAB-based versatile random day-to-day weather generator. It can produce everyday r...
s u m m a r y Weather generators are computer models that produce time series of meteorological data...
The objective of this study is to analyse the capability of a Weather Generator based on a multivari...
A stochastic weather generator is a model capable of generating daily weather patterns that are stat...
Weather generators are tools used to downscale monthly to seasonal climate forecasts, from numerical...
[EN] Temperature is one of the most influential weather variables necessary for numerous studies, su...
Abstract. The high-frequency and low-frequency variabilities, which are often misreproduced by the d...
dissertationStochastic weather generators (SWGs) are statistically-based point-scale models of meteo...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95112/1/wrcr11029.pd
Wilks, 1992] four-variate stochastic weather generator [Dubrovsky, 1997]. It is designed to provide ...
Capturing the spatial and temporal correlation of multiple variables in a weather generator is chall...
Abstract: This article reviews the historical development of statistical weather models, from simple...
Weather Generators (WGs) are widely used in water engineering, agriculture, ecosystem and climate ch...
Traditional stochastic approaches for synthetic generation of weather variables often assume a prior...
AbstractThis paper describes a versatile stochastic daily weather generator (WeaGETS) for producing ...
WeaGETS is a MATLAB-based versatile random day-to-day weather generator. It can produce everyday r...
s u m m a r y Weather generators are computer models that produce time series of meteorological data...
The objective of this study is to analyse the capability of a Weather Generator based on a multivari...
A stochastic weather generator is a model capable of generating daily weather patterns that are stat...
Weather generators are tools used to downscale monthly to seasonal climate forecasts, from numerical...
[EN] Temperature is one of the most influential weather variables necessary for numerous studies, su...
Abstract. The high-frequency and low-frequency variabilities, which are often misreproduced by the d...
dissertationStochastic weather generators (SWGs) are statistically-based point-scale models of meteo...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95112/1/wrcr11029.pd
Wilks, 1992] four-variate stochastic weather generator [Dubrovsky, 1997]. It is designed to provide ...
Capturing the spatial and temporal correlation of multiple variables in a weather generator is chall...
Abstract: This article reviews the historical development of statistical weather models, from simple...
Weather Generators (WGs) are widely used in water engineering, agriculture, ecosystem and climate ch...
Traditional stochastic approaches for synthetic generation of weather variables often assume a prior...