Development of a combined empirical index for a 5-day forecast of heavy precipitation over the Bernese Alps.

Affiliation

C-CIA - Climate Change Impacts and Risks in the Anthropocene, Institute for Environmental Sciences (ISE), University of Geneva, CH-1205 Geneva, Switzerland. Electronic address: [Email]

Abstract

The Bernese Alps are a region that is very prone for the initiation of thunderstorms. In fact, the flow and convergence of air and water vapor from the Swiss Plateau to the Swiss Alps is frequently favouring the formation of isolated rainfall events, which then may cause loss and damage in settlements. Due to the complex topography of the Bernese Alps, the forecasting and nowcasting of heavy convective precipitation remain challenging. A critical need therefore exists for the development of new forecasting tools so as to improve the predictability of convective precipitation events, also with the aim to alert first responders and to subsequently reduce damage. This study aims at developing an empirical index for the forecasting of heavy precipitation events in the Bernese Alps by using two reanalysis datasets, ECMWF's ERA-Interim and NASA's MERRA-2; in addition, the ICON-EU model is employed here to test and verify the index for the 2018 summer period. Our approach is based on the calculation of several convective indices as well as on the assessment of their relative forecast skills using a dichotomous scheme. The Heavy Precipitation Index (HPI) is then defined by combining the best performing combination of convective indices. HPI is aimed at forecasting heavy precipitation events over the Bernese Alps. We show that the combination of several indices, including DCI or KI, have a better capability to forecast heavy precipitation in the Bernese Alps than has the commonly used CAPE. Therefore, HPI should be seen as a pre-alert index when it comes to assist first responders in situations of crisis and in the process of decision making.

Keywords

Bernese Alps,CAPE,Convective indices,Heavy Precipitation Index,Heavy precipitation,Reanalysis,

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