Data assimilation impact studies with the AROME-WMED reanalysis of the first special observation period of the Hydrological cycle in the Mediterranean Experiment

Nadia Fourrié,Pierre Brousseau,Olivier Caumont,Mathieu Nuret

doi:10.5194/nhess-21-463-2021

Abstract

Abstract. This study was performed in the framework of HyMeX (Hydrological cycle in the Mediterranean Experiment), which aimed to study the heavy precipitation that regularly affects the Mediterranean area. A reanalysis with a convective-scale model AROME-WMED (Application of Research to Operations at MEsoscale western Mediterranean) was performed, which assimilated most of the available data for a 2-month period corresponding to the first special observation period of the field campaign (Fourrié et al., 2019). Among them, observations related to the low-level humidity flow were assimilated. Such observations are important for the description of the feeding of the convective mesoscale systems with humidity (Duffourg and Ducrocq, 2011; Bresson et al., 2012; Ricard et al., 2012). Among them there were a dense reprocessed network of high-quality Global Navigation Satellite System (GNSS) zenithal total delay (ZTD) observations, reprocessed data from wind profilers, lidar-derived vertical profiles of humidity (ground and airborne) and Spanish radar data. The aim of the paper is to assess the impact of the assimilation of these four observation types on the analyses and the forecasts from the 3 h forecast range (first guess) up to the 48 h forecast range. In order to assess this impact, several observing system experiments (OSEs) or so-called denial experiments, were carried out by removing one single data set from the observation data set assimilated in the reanalysis. Among the evaluated observations, it is found that the ground-based GNSS ZTD data set provides the largest impact on the analyses and the forecasts, as it represents an evenly spread and frequent data set providing information at each analysis time over the AROME-WMED domain. The impact of the reprocessing of GNSS ZTD data also improves the forecast quality, but this impact is not statistically significant. The assimilation of the Spanish radar data improves the 3 h precipitation forecast quality as well as the short-term (30 h) precipitation forecasts, but this impact remains located over Spain. Moreover, marginal impact from wind profilers was observed on wind background quality. No impacts have been found regarding lidar data, as they represent a very small data set, mainly located over the sea.

Highlights

Heavy precipitation regularly affects the Mediterranean area with huge damages and sometimes casualties
In REANA2, we considered here reprocessed data (REPROC-Global Navigation Satellite System (GNSS) in the following) with a homogeneous reprocessing using a single software and more precise satellite orbit position and clocks (Bock et al, 2016), which were available for the whole SOP1
Two reanalyses were produced after the Hydrological cycle in the Mediterranean Experiment (HyMeX) autumn campaign for the first special observation periods (SOPs)

Summary

Introduction

Heavy precipitation regularly affects the Mediterranean area with huge damages and sometimes casualties. The importance of an accurate description of the low-level humidity flow, which feeds the mesoscale systems, was shown in previous studies (Duffourg and Ducrocq, 2011; Bresson et al, 2012; Ricard et al, 2012). This is why during this period research observations were deployed over the northwestern Mediterranean area. These observations aimed at a better description of the humidity and wind fields. Particular attention was paid to the control of data quality

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