Abstract
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 dominates the weather on 80 % of the days in the 2-month 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 pure spatial forecast quality of the most intense precipitation in the afternoon, as quantified with its 95th percentile, 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.
Highlights
The Mediterranean region is affected by intense precipitation events every year, during the autumn months
The PEARP 35-member ensemble forecasts are classified by a complete-linkage clustering technique (Molteni et al, 2001). (iii) The initial conditions are provided by adding downscaled forecast perturbations of the selected PEARP members to the AROME operational analysis (Raynaud and Bouttier, 2017). (iv) Atmospheric model errors are represented through the so-called SPPT scheme described in Bouttier et al (2012), which simulates the effect of random errors due to physical parameterizations. (v) random perturbations are added to various parameters of the Surface Externalisée (SURFEX) surface scheme, including for instance seasurface temperature, soil moisture and temperature perturbations (Bouttier et al, 2016)
This study extends prior work documenting the performance of AROME-ensemble prediction systems (EPSs) during HyMeX-SOP1 (Bouttier et al, 2016; Nuissier et al, 2016) by the weather-regime-dependent aspect of precipitation predictability with a special focus on the spatial forecast quality
Summary
The Mediterranean region is affected by intense precipitation events every year, during the autumn months. In the present study we aim to systematically identify different predictability regimes of precipitation in southeast France and northwest Italy during autumn 2012, for which the HyMeX campaign offers an unprecedented transnational observational dataset to validate convective-scale ensemble prediction systems (Ducrocq et al, 2014) This period extends from 5 September to 5 November 2012 of which 59 d experienced noteworthy precipitation and includes numerous well-studied intensive observation periods (IOPs) of highimpact weather situations. Et al (2014) investigated the sensitivity of precipitation forecasts in an experimental convective-scale ensemble based on the Meso-NH model to diverse initial and boundary conditions and microphysical uncertainties for two IOPs (IOP6 and IOP7a in southeast France) Since both cases developed under strong synoptic forcing, the impact of atmospheric conditions on the spatiotemporal distribution of precipitation outweighs that of microphysical and surface perturbations. The remainder of the paper consists of a methods section, followed by a classification of the 2-month period into weather regimes, an illustration of three prominent cases, the verification using classical grid-point-based quality measures, probabilistic metrics and a spatial score to allow for location tolerance, and conclusions
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
