A new stochastic weather generator for a two-dimensional grid
A new stochastic weather generator for a two-dimensional grid which simulates high resolution climatic data in time (min) and space (km) has been published in the Journal of Advances in Modeling Earth Systems (JAMES).
Stochastic weather generators have become indispensible tools in hydrology. They are used to generate climatic input data for watershed models, quantify internal climate variability, and determine its impact on uncertainty in hydrological predictions.
A new stochastic weather generator (Advanced WEather GENerator for a two-dimensional grid AWE-GEN-2d) has recently been developed at the Hydrology and Water Resources Management Chair at IFU. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2x2 km and 5 min for precipitation and cloud cover and 100x100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious and computationally efficient, suitable for a range of applications with Monte Carlo simulation. The main application of the weather generator is in generating inputs for impact studies of environmental systems (hydrology-geomorphology-ecology), where high-resolution spatial and temporal meteorological forcing is needed.
Peleg, N., S. Fatichi, A. Paschalis, P. Molnar, and P. Burlando (2017), external pageAn advanced stochastic weather generator for simulating 2-D high-resolution climate variables, J. Adv. Model. Earth Syst., 9, doi:10.1002/2016MS000854.