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. 

An example of the high-resolution simulation of AWE-​GEN-2d. Incoming short-wave radiation (left) and temperature (right) are simulated for spatial resolution of 100 x 100 m2 and 1 h in time. The example presented is taken from one member (year) from the ensemble that was simulated for the Engelberg area (Switzerland).


Peleg, N., Fatichi, S., Paschalis, A., Molnar, P. and Burlando, P., 2017. An advanced stochastic weather generator for simulating 2‐D high‐resolution climate variables. Journal of Advances in Modeling Earth Systems, 9(3), pp.1595-1627.

Peleg, N., Molnar, P., Burlando, P. and Fatichi, S., 2019. Exploring stochastic climate uncertainty in space and time using a gridded hourly weather generator. Journal of Hydrology, 571, pp.627-641.


Peleg, N., & Fatichi, S. (2017). Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d). Zenodo.

Further development: the AWE-GEN-2d-CC model

A newer version of the AWE-GEN-2d model was developed in 2023, explicitly simulating the changes of extreme precipitation with increasing temperature following the Clausius–Clapeyron (CC) relation. See the references to the paper and code below for further details.


The paper is currently under review.


Moraga, J. S., & Peleg, N. (2023). AWE-GEN-2d-CC. Zenodo.