Precipitation has a direct impact on both the ecosystem and the human society, it affects groundwater and reservoirs, and constitutes a major environmental hazard. The accurate evaluation of the spatial distribution and intensity of precipitation at local scales is crucial for risk assessment and water management, especially in mountainous regions downstream of which human activities may be strongly impacted.

Climate models have a rather coarse resolution, are often biased, and in general unable to accurately represent precipitation at local scales: in regions of complex orography, the spatial patterns of precipitation exhibit abrupt discontinuities and a spatio-temporal variability at a much higher frequency. Statistical approaches can be used to correct model simulations making use of observations, yet observed rainfall data are in general too sparse to be representative of the topographic variations of the “true” precipitation field.

On May 29, 2018, researcher Paola Marson (CMCC CSP Division) presented a new statistical framework able to describe the spatial distribution and intensity of precipitation over complex terrain; deal with the relative spatial sparsity of observations by incorporating established analytical descriptions of processes involved; enhance numerical climate models capability.

Watch the video:

Download the webinar presentation (pdf) by P. Marson.