In our group, we develop 2-dimensional rainfall and climate models that can be used to study past, present, and future climate impacts. The models are useful for modeling environmental systems in which high spatial and temporal resolution of meteorological forcing is essential for the correct simulation of hydrological, ecological, agricultural, and geomorphological processes. Below are brief descriptions of two such models.
The AWE-GEN-2d model
AWE-GEN-2d (Advanced WEather GENerator for a 2-dimensional grid) is a stochastic weather generator that simulates gridded climate variables at high spatial and temporal resolution for past, present, and future climates. In AWE-GEN-2d, physical and stochastic approaches are combined to simulate key climate variables (e.g. precipitation, cloud cover, near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind). Through the use of a combination of stochastic-physical methods, it is possible to simulate meteorological variables on a sub-daily time scale and to consider their dependence. In terms of computation, the model is reasonably efficient and can be used on a desktop computer. It can be used to study stochastic climate variability, spatial heterogeneity, and temporal and spatial resolutions of climate forcing, as well as to downscale climate.
The HiReS-WG model
The High-Resolution Synoptically conditioned Weather Generator (HiReS-WG) is a stochastic rainfall model that generates rain fields with a substantial proportion of convective features. The rain fields are generated based on the empirical distributions of the rainfall characteristics subjected to the classified synoptic system. The model is composed of four modules: (1) synoptic generator; (2) motion vector generator, i.e. advecion component; (3) convective rain cell generator; and (4) low-intensity rainfall generator. HiReS-WG is parsimonious in computational demands and is encoded in Matlab.