Most precipitation in the mid-latitudes is attributable to convective clouds and frontal systems. Although their development is not induced by the underlying terrain, the orography can play a substantial role in altering their features. The orographic moist flow dynamic interacts synergistically with thermodynamic and microphysical processes as well as with the large-scale flow. A potential consequence is the modification of the spatial distribution of precipitation at the ground, which likely exhibits a highly segmented nature in both space and time. Observed precipitation data are in general too coarse in space to be representative of the topographic variations of the "true" precipitation field. Aiming at describing the spatial distribution of precipitation over complex terrain, we specify a statistical model which does not solely rely on observed data but also incorporates established analytical descriptions of the physical processes involved. We derived a 2-dimensional advection equation for the column integrated hydreometeor density modifying the quasi-analytical upslope model by R.B. Smith, 2003. A Simultaneously Autoregressive model has then been derived discretizing the advection equation and perturbing it by means of a stochastic noise.

A statistical framework for modeling the spatial distribution and intensity of orographic precipitation / Marson, Paola. - (2018 Jul 04).

A statistical framework for modeling the spatial distribution and intensity of orographic precipitation

Marson, Paola
2018-07-04

Abstract

Most precipitation in the mid-latitudes is attributable to convective clouds and frontal systems. Although their development is not induced by the underlying terrain, the orography can play a substantial role in altering their features. The orographic moist flow dynamic interacts synergistically with thermodynamic and microphysical processes as well as with the large-scale flow. A potential consequence is the modification of the spatial distribution of precipitation at the ground, which likely exhibits a highly segmented nature in both space and time. Observed precipitation data are in general too coarse in space to be representative of the topographic variations of the "true" precipitation field. Aiming at describing the spatial distribution of precipitation over complex terrain, we specify a statistical model which does not solely rely on observed data but also incorporates established analytical descriptions of the physical processes involved. We derived a 2-dimensional advection equation for the column integrated hydreometeor density modifying the quasi-analytical upslope model by R.B. Smith, 2003. A Simultaneously Autoregressive model has then been derived discretizing the advection equation and perturbing it by means of a stochastic noise.
4-lug-2018
30
Scienza e gestione dei cambiamenti climatici
Gualdi, Silvio
Materia, Stefano
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10579/15563
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