Probability distributions of multivariate random variables are generally more complex
compared to their univariate counterparts which is due to a possible nonlinear dependence …

This study attempts to analyze several drought features in South Korea from various
perspectives using a three‐month standard precipitation index. In particular, this study aims …

Weather-state models have been shown to be effective in downscaling the synoptic
atmospheric information to local daily precipitation patterns. We explore the ability of non …

Regional climate impact assessments require high-resolution projections to resolve local
factors that modify the impact of global-scale forcing. To generate these projections, global …

Atmosphere–ocean general circulation models (AOGCMs) are useful for assessing the state
of the climate at large scales. Unfortunately, they are not tractable for the finer-scale …

Downscaled rainfall projections from climate models are essential for many meteorological
and hydrological applications. The technique presented utilizes an approach that efficiently …

Daily global solar radiation (SR) is one of essential weather inputs for crop, hydrological,
and other simulation models to calculate biomass production and potential …

CLIGEN is a stochastic weather generator to statistically reproduce daily weather variables.
Weather observations from regions with significant climate variability could be used to …

Changes in precipitation directly impact river runoff volume, subsequently influencing food
production, and the security of downstream urban areas. In this study, we introduce a …

It is well recognized that statistical linear interpolation models are computationally
inexpensive and applicable to any climate data compared to the dynamic simulation method …