Toward the Assimilation of W-Band Radar Data in a Kilometer-Scale NWP Model

The high sensitivity of W-band radar data to cloud microphysical properties and dynamics makes them appealing for atmospheric model validation and data assimilation. To assess the potential of such data to improve the forecasting of heavy precipitation events, we take advantage of the data collected in diverse conditions by the airborne Doppler W-band radar RASTA (Radar Airborne System Tool for Atmosphere, Delanoë et al. 2013) during a two-month period over a region of the Mediterranean prone to intense rainfall. This unique instrument allows the documentation of the microphysical properties and the three components of the wind field quasi-continuously in time and at a vertical resolution of 60 m.

We first describe a reflectivity forward operator developed for the validation and assimilation of W-band radar data into regional convective-scale NWP models like AROME-WMed (Fourrié et al. 2015). The forward operator is consistent with the one-moment microphysical scheme ICE3 of AROME-WMed and is devised for airborne and ground-based vertically pointing radars (Borderies et al. 2017). A new neighborhood validation method, called the Most Resembling Column (MRC) method, is designed to disentangle spatial location model errors from errors in the forward operator. This novel method is applied to validate the forward operator and to retrieve, via the least-squares method, the optimal effective shapes (i.e. the mean axis ratios) of the predicted graupel, snow and pristine ice. Results indicate pristine ice can be approximated by a sphere while the optimal mean axis ratio is approximately 0.8 for snow and graupel.

The forward operator developed here is then employed to assimilate W-band radar reflectivity in AROME-WMed (1D+3D-Var, Caumont et al. 2010). Vertical profiles of relative humidity are retrieved and used as pseudo-observations in the 3D-Var data assimilation system of AROME-WMed. The respective roles of the W-band reflectivity observations and the Doppler velocity observations are investigated to improve the analyses and short-term forecasts of heavy precipitation events.

Borderies M., Caumont O., Augros C., Delanoë J., Ducrocq V., 2017. Simulation of W-band radar reflectivity for model validation and data assimilation. Quarterly Journal of the Royal Meteorological Society (Submitted)

Caumont O., Ducrocq V., Wattrelot É., Jaubert G., Pradier-Vabre S. (2010). 1D+ 3DVar assimilation of radar reflectivity data: a proof of concept. Tellus A, 62(2), 173-187.

Delanoë, J., Protat, A., Jourdan, O., Pelon, J., Papazzoni, M., Dupuy, R., ... & Jouan, C. (2013). Comparison of airborne in situ, airborne radar–lidar, and spaceborne radar–lidar retrievals of polar ice cloud properties sampled during the POLARCAT campaign. Journal of Atmospheric and Oceanic Technology, 30(1), 57-73.

Fourrié, N., Bresson, É., Nuret, M., Jany, C., Brousseau, P., Doerenbecher, A., ... & Amodei, M. (2015). AROME-WMED, a real-time mesoscale model designed for the HyMeX special observation periods. Geoscientific Model Development, 8(7), 1919.