Improving Convection Trigger Functions in Deep Convective Parameterization Schemes Using Machine Learning

Abstract Previous studies have documented that deep convection responds more strongly to above-the-cloud-base temperature perturbations in the lower troposphere than to those in the upper troposphere, a behavior that is important to the dynamics of large-scale moist flows, such as convectively coupled waves. A number of factors may contribute to this differing sensitivity, including differences in buoyancy, vertical velocity, and/or liquid water content in cloud updrafts in the lower versus upper troposphere. Quantifying the contributions from these factors can help to guide the development of convective parameterization schemes. We tackle this issue by tracking Lagrangian particles embedded in cloud-resolving simulations within a linear response framework. The results show that both the differences in updraft buoyancy and vertical velocity play a significant role, with the vertical velocity being the more important, and the effect of liquid water content is only secondary compared to the other two factors. These results indicate that cloud updraft vertical velocities need to be correctly modeled in convective parameterization schemes in order to properly account for the differing convective sensitivities to temperature perturbations at different heights of the free troposphere.

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Verification of precipitation forecasts of MM5 model over Epirus, NW Greece, for various convective parameterization schemes

Natural Hazards and Earth System Science ◽

10.5194/nhess-12-1393-2012 ◽

2012 ◽

Vol 12 (5) ◽

pp. 1393-1405 ◽

Cited By ~ 11

Author(s):

O. A. Sindosi ◽

A. Bartzokas ◽

V. Kotroni ◽

K. Lagouvardos

Keyword(s):

Horizontal Resolution ◽

Forecast Skill ◽

Precipitation Forecast ◽

Meteorological Model ◽

Convective Parameterization ◽

Parameterization Schemes ◽

Mm5 Model ◽

Convective Parameterization Scheme ◽

High Precipitation Events ◽

High Precipitation

Abstract. The mesoscale meteorological model MM5 is applied to 22 selected days with intense precipitation in the region of Epirus, NW Greece. At first, it was investigated whether and to what extend an increased horizontal resolution (from 8 to 2 km) improves the quantitative precipitation forecasts. The model skill was examined for the 12-h accumulated precipitation recorded at 14 meteorological stations located in Epirus and by using categorical and descriptive statistics. Then, the precipitation forecast skill for the 2 km grid was studied: (a) without and (b) with the activation of a convective parameterization scheme. From the above study, the necessity of the use of a scheme at the 2 km grid is assessed. Furthermore, three different convective parameterization schemes are compared: (a) Betts-Miller, (b) Grell and (c) Kain-Fritsch-2 in order to reveal the scheme, resulting in the best precipitation forecast skill in Epirus. Kain-Fritsch-2 and Grell give better results with the latter being the best for the high precipitation events.

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