Dependence of Predictability of Precipitation in the Northwestern Mediterranean Coastal Region on the Strength of Synoptic Control

Abstract

<jats:p>Abstract. The weather regime dependent predictability of precipitation in the convection permitting kilometric scale AROME-EPS is examined for the entire HyMeX SOP1 employing the convective adjustment timescale. This diagnostic quantifies variations in synoptic forcing on precipitation and is associated with different precipitation characteristics, forecast skill and predictability. During strong synoptic control, which is dominating the weather on 80 % of the days in the 2-months period, the domain integrated precipitation predictability assessed with the normalized ensemble standard deviation is above average, the wet bias is smaller and the forecast quality is generally better. In contrast, the spatial forecast quality of most intense precipitation in the afternoon, as quantified with its 95th percentiles, is superior during weakly forced synoptic regimes. The study also considers a prominent heavy precipitation event that occurred during the NAWDEX field campaign in the same region, and the predictability during this event is compared with the events that occurred during HyMeX. It is shown that the unconditional evaluation of precipitation widely parallels the strongly forced weather type evaluation and obscures forecast model characteristics typical for weak control. </jats:p>

Distributions and convergence of forecast variables in a 1,000‐member convection‐permitting ensemble

“…see table 1 in Leutbecher, 2019) and even fewer for limited area models (e.g. Gebhardt et al ., 2011; Bouttier et al ., 2012; Hagelin et al ., 2017; Schwartz et al ., 2017; Frogner et al ., 2019; Keil et al ., 2020). This is not enough to accurately represent the non‐linear evolution of the forecast distributions (Leutbecher, 2019).…”

Dynamics of forecast‐error growth along cut‐off Sanchez and its consequence for the prediction of a high‐impact weather event over southern France

“…A convection‐permitting model would be more appropriate to tackle this problem. Indeed, short‐range precipitation forecasts of the convection‐permitting AROME‐EPS (driven by global ARPEGE fields) capture the rainfall accurately in terms of intensity and location (Keil et al ., 2020).…”