Operational assimilation of space-borne radar and lidar cloud profile observations for numerical weather prediction. Conclusions and recommendations

TitleOperational assimilation of space-borne radar and lidar cloud profile observations for numerical weather prediction. Conclusions and recommendations
Publication TypeReport
Date Published2018
Series/CollectionESA Contract Report
Document NumberWP-6000
AuthorsJaniskova, M, Fielding, M
Event Series/CollectionESA Contract Report
Abstract

This report provides a summary of developments and experimentation studies towards monitoring and assimilation of space-borne radar and lidar cloud profile observations in Numerical Weather Prediction (NWP) model.

An overview of the required adjustments of assimilation tools, such as the observation operators, observation error definition, quality control, data screening and bias correction, in order to build a direct data assimilation and monitoring system for such observations is provided.

Conclusions from monitoring experiments for cloud radar and lidar observations using CloudSat (NASA's cloud radar mission) and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) data have suggested that the skill of monitoring system to detect a degradation in the quality of observations is improved when the first guess departures are used compared to using just observations alone.

Outcomes from 4D-Var assimilation experiments using CloudSat cloud radar reflectivity and CALIPSO lidar backscatter observations, either separately or in combination indicated that Four-Dimensional Variational (\mbox{4D-Var}) analyses get closer to assimilated observations. However, impact of the cloud radar reflectivity is larger than that of the lidar backscatter. Impact on the first-guess (FG) and analysis (AN) departure statistics when verified against other observation types assimilated in 4D-Var is most pronounced and positive for conventional observations, especially for wind. An impact of the new observations on the subsequent forecast is largest for zonal wind, relative to both operational analysis and conventional observations, such as radiosonde or aircraft data. Results also indicated an improved forecast, especially rain rates in the tropics.

Suggested perspectives for the future assimilation and a brief summary of work still required to complete a preparation for possible operational assimilation and monitoring of the EarthCARE radar and lidar cloud observations are also provided.

URLhttps://www.ecmwf.int/node/18500
PDF icon Download (6.48 MB)