Abstract
Abstract. The article reports on the impact of the assimilation of wind vertical profile data in a kilometre-scale NWP system on predicting heavy precipitation events in the north-western Mediterranean area. The data collected in diverse conditions by the airborne W-band radar RASTA (Radar Airborne System Tool for Atmosphere) during a 45-day period are assimilated in the 3 h 3DVAR assimilation system of AROME. The impact of the length of the assimilation window is investigated. The data assimilation experiments are performed for a heavy rainfall event, which occurred over south-eastern France on 26 September 2012 (IOP7a) and over a 45-day cycled period. Results indicate that the quality of the rainfall accumulation forecasts increases with the length of the assimilation window, which recommends using observations with a large period centred on the assimilation time. The positive impact of the assimilation of RASTA wind data is particularly evidenced for the IOP7a case since results indicate an improvement in the predicted wind at short-term ranges (2 and 3 h) and in the 11 h precipitation forecasts. However, in the 45-day cycled period, the comparison against other assimilated observations shows an overall neutral impact. Results are still encouraging since a slight positive improvement in the 5, 8 and 11 h precipitation forecasts was demonstrated.
Highlights
The Mediterranean area is frequently subject to heavy precipitation events, causing heavy damage and significant human loss (Ducrocq et al, 2014)
The impact of RASTA wind data is first illustrated on a heavy precipitation event which occurred during the Intensive Observation Period 7a (IOP7a) on 26 September 2012
This article reports on the first study in which vertical profiles of wind measured by vertically pointing airborne Doppler W-band radar are assimilated in a kilometre-scale numerical weather prediction (NWP) model
Summary
The Mediterranean area is frequently subject to heavy precipitation events, causing heavy damage and significant human loss (Ducrocq et al, 2014). Several studies suggested that the impact of the assimilation of wind observations was beneficial for analyses and forecasts (Horányi et al, 2015). Ground-based Doppler precipitation radar data are operationally assimilated in kilometre-scale NWP systems, since their potential to improve the short-term forecasts has been demonstrated (Montmerle and Faccani, 2009; Simonin et al, 2014). In clear-air conditions, wind observations can be provided by insect-derived Doppler radar measurements (Kawabata et al, 2007; Rennie et al, 2011) or by Doppler lidars (Weissmann et al, 2012; Kawabata et al, 2014). Several studies highlighted the benefit of the assimilation of these data into NWP models to improve short-term forecasts (Benjamin et al, 2004; Illingworth et al, 2015b). The main drawback of ground-based radars and radar profilers is that they are only distributed over land
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