Assimilation of water‐vapour airborne lidar observations: impact study on the COPS precipitation forecasts

Abstract

The Convective and Orographically-driven Precipitation Study (COPS) carried out in summer 2007 over northeastern France and southwestern Germany provided a fairly comprehensive description of the low-troposphere water-vapour field, thanks in particular to the deployment of two airborne differential absorption lidar systems. These lidar observations were assimilated using the 3D-Var assimilation system of the Application of Research to Operations at MEsoscale (AROME) numerical weather prediction mesoscale model. The assimilation was carried out for the period 4 July-3 August by running a three-hour forward intermittent assimilation cycle. First, the impact of the lidar observations was assessed by comparing the analyses with a set of more than 200 independent soundings. The lidar observations were found to have a positive impact on the analyses by reducing the dry bias in the first 500 m above ground level and by diminishing the root-mean-square error by roughly 15% in the first km. Then the impact of the lidar observations was assessed by comparing the precipitation forecasts (obtained with and without the lidar observations for the period 15 July-2 August) with the gridded precipitation observations provided by the Vienna Enhanced Resolution Analysis. In general, the impact was found to be positive but not significant for the 24 h precipitation and positive and significant for the 6 h precipitation, with an improvement lasting up to 24 h. Some selected case studies show that the improvement was obtained through a better depiction of convection initiation or through a more accurate positioning of the precipitation systems.

Automated compact mobile Raman lidar for water vapor measurement: instrument description and validation by comparison with radiosonde, GNSS, and high-resolution objective analysis

“…As several studies have already demonstrated a strong and positive impact of the water vapor lidar data on the initial water vapor field of the numerical weather prediction mesoscale model by using the three-or four-dimensional variational method (Wulfmeyer et al, 2006;Grzeschik et al, 2008;Bielli et al, 2012), the MRL-measured data can be assimilated into a nonhydrostatic mesoscale model (NHM) (Saito et al, 2007) by the local ensemble transform Kalman filter (LETKF) method (Kunii, 2014) to improve the initial condition of the water vapor field and consequently the rainfall forecast. Given the temporal and vertical resolutions of the model and the assim-ilation window length, the required measurement resolutions are at most 30 min in time and 200 m in the vertical direction.…”

A posteriori diagnostics of the impact of observations on the AROME‐France convective‐scale data assimilation system

“…Moreover, the verification of forecast performance can be more difficult at convective than at global scales; observation networks are too sparse to easily validate all the field scales present in a high‐resolution model simulation. In the AROME–France framework, OSEs experiments have been made concerning total zenith delays from ground‐based GPS stations (Yan et al , 2009; Boniface et al , 2009), radial winds from doppler radars (Montmerle and Faccani, 2009), radar reflectivities (Wattrelow et al , 2008), brightness temperatures from IASI (Infrared Atmospheric Sounding Interferometer; Guidard et al , 2011), water vapour mixing ratios from airborne lidars (Bielli et al , 2012). …”

Airborne Lidar Observations of Water Vapor Variability in Tropical Shallow Convective Environment

“…Due to its capabilities the WALES airborne demonstrator has become a state-of-the-art instrument for climate and meteorological research. Over the past decade it successfully completed several hundreds of flight hours in national and international field campaigns (Schäfler et al, 2010;Bhawar et al, 2011;Kiemle et al, 2011;Bielli et al, 2012;Fischer et al, 2013;Groß et al, 2014;Trickl et al, 2016).…”