Storm-Scale Data Assimilation and Ensemble Forecasting with the NSSL Experimental Warn-on-Forecast System. Part II: Combined Radar and Satellite Data Experiments

Abstract

This research represents the second part of a two-part series describing the development of a prototype ensemble data assimilation system for the Warn-on-Forecast (WoF) project known as the NSSL Experimental WoF System for ensembles (NEWS-e). Part I describes the NEWS-e design and results from radar reflectivity and radial velocity data assimilation for six severe weather events occurring during 2013 and 2014. Part II describes the impact of assimilating satellite liquid and ice water path (LWP and IWP, respectively) retrievals from the GOES Imager along with the radar observations. Assimilating LWP and IWP observations may improve thermodynamic conditions at the surface over the storm-scale domain through better analysis of cloud coverage in the model compared to radar-only experiments. These improvements sometimes corresponded to an improved analysis of supercell storms leading to better forecasts of low-level vorticity. This positive impact was most evident for events where convection is not ongoing at the beginning of the radar and satellite data assimilation period. For more complex cases containing significant amounts of ongoing convection, only assimilating clear-sky satellite retrievals in place of clear-air reflectivity resulted in spurious regions of light precipitation compared to the radar-only experiments. The analyzed tornadic storms in these experiments are sometimes too weak and quickly diminished in intensity in the forecasts. The lessons learned as part of these experiments should lead to improved iterations of the NEWS-e system, building on the modestly successful results described here.

Impact of Moisture Information From Advanced Himawari Imager Measurements on Heavy Precipitation Forecasts in a Regional NWP Model

“…The temporal resolutions of 30 s in the mesoscale, 5 min over the contiguous United States, and 15 min over the full disk also provide unprecedented measurements that could capture the rapid evolution of convective situations which is useful for short‐term, severe storm forecasts. The assimilation of liquid and ice water path retrievals from the GOES Imager shows improvement of thermodynamic conditions at the surface layer (Jones et al, ). Taking full advantage of high spatial and temporal resolution in the regional‐/storm‐scale model will be the focus of future work.…”

Analysis and prediction of a mesoscale convective system over East China with an ensemble square root filter radar data assimilation approach

“…Recently, experimental real‐time ensemble predictions based on cycled EnKF data assimilation analyses have also been performed by the Center for Analysis and Prediction of Storms (Xue et al , ) during the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed Spring Experiments. A storm‐scale radar and satellite data assimilation system developed as part of the warn‐on forecast project was also run in real time (Jones et al , ; Wheatley et al , ).…”

Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres

“…High‐resolution AMVs from MSG are also available. A radar‐based precipitation rate analysis is assimilated via the technique of LHN (Jones and Macpherson, ; Macpherson, ) as well as Doppler radial wind data from UK weather radars (Simonin et al , ). A novel feature is the variational assimilation of visibility observations (Clark et al , ).…”