Data Assimilation & Prediction

Enabling Cloud Condensate Cycling for All-Sky Radiance Assimilation in HWRF

Project Period: September 1, 2018 to August 31, 2020
Principal Investigator(s): Ting-Chi Wu
Co-Principal Investigator(s): Milija Zupanski and Lewis Grasso
Sponsor(s): National Oceanic and Atmospheric Administration (NOAA)


NOAA’s operational HWRF excludes assimilation of cloudy and precipitation affected satellite radiances. Instead, clear-sky radiances are assimilated. Since clouds are part of the dynamics of hurricane processes, subsequent neglect of clouds during a data assimilation process may have adverse consequences to the prediction of hurricane track and intensity. One main goal of the proposed research aims to improve hurricane forecasts by creating an improved initial state via enabling cloud condensate cycling in the HWRF system in order to facilitate the assimilation of all-sky satellite radiances.


To achieve the proposed goal, modifications to the following components of HWRF are required: 1) Vortex Improvement (VI; also known as Vortex Initialization or Vortex Relocation), 2) data assimilation, which uses the hybrid Gridpoint Statistical Interpolation (GSI), and 3) Merge (MG), a procedure that interpolates and merges resulting analyses to all domains in an HWRF forecast. As of this writing, cloud condensate variables are excluded during both the VI and MG steps. Specifically, values of cloud condensate are intentionally set to zero during both the VI and MG procedures. Although hybrid GSI has the general capability to include cloud condensate updates, exclusion of condensate variables in both the VI and MG procedures prevents condensate updates in an analysis field within an HWRF cycle. As a result, new development is necessary in order to assimilate all-sky satellite radiances in HWRF.


In the proposed work, the following modifications to the HWRF components that include 1) the VI, 2) the hybrid GSI, and 3) the MG are essential. Modifications to VI will add the inclusion of non-zero values of cloud condensate, which will be from a 6-h HWRF forecast of a previous cycle. Subsequently, a resulting background field will contain information of cloud condensate. Modifications to the hybrid GSI will allow the inclusion of cloud condensate variables to an existing set of control variables. Therefore, cloud information will be updated via assimilation of observed satellite radiances. Modifications to MG will include the interpolation and merging of cloud condensate information from the resulting analyses to all HWRF forecast domains. As a result, an initial state with updated cloud condensate information will be used for an HWRF forecast. One priority of the proposed work will be to use all-sky radiances from the Advanced Technology Microwave Sounder (ATMS) in order to align with similar efforts at Environmental Modeling Center (EMC), which pertain to global all-sky assimilation. Finally, a tropical cyclone case will be selected to conduct experiments using the modified HWRF system with cloud condensate cycling via the assimilation of ATMS radiances. Results from the experiments will be evaluated using standard tropical cyclone forecast metrics and data assimilation techniques.