# A Study on Assimilation of CYGNSS Wind Speed Data for Tropical Convection during 2018 January MJO
## Data and Methods
### Data Assimilation Experiments  
The advanced research Weather Research and Forecasting (WRF-ARW; [50]) model and the WRF Data Assimilation (WRFDA) system ([51]) were used in this study. The WRF model and WRFDA system are open-source and can be downloaded from [[https://www2.mmm.ucar.edu/wrf/users/downloads.html](https://www2.mmm.ucar.edu/wrf/users/downloads.html)]([https://www2.mmm.ucar.edu/wrf/users/downloads.html](https://www2.mmm.ucar.edu/wrf/users/downloads.html)). This study used a double nested domain with resolutions of 9- and 3-km to simulate TC Irving and the WWB event (Figure 2a). The following model physics schemes were used: the rapid radiative transfer model (RRTM; [52]) long-wave radiation, Dudhia shortwave radiation [53], Betts-Miller-Janic cumulus parameterization [54], Mellor-Yamada_Janjic (MYJ) planetary boundary layer (PBL) schemes [54], Morrison 2-moment microphysical scheme [55], and the Unified Noah land-surface model [56]. The cumulus parameterization was only used for the outer domain. The WRFDA system was used to conduct data assimilation with the hybrid ensemble variational technique. WRFDA is a unified community data assimilation system that has 3-dimensional variational (3 DVAR) and 4-dimensional ensemble variational (4 DVAR) capabilities, a hybrid variational ensemble algorithm (EnVar) and ensemble transform Kalman Filter technique. Being built in model-space, WRFDA is a flexible, state-of-the-art atmospheric data assimilation system that is portable and efficient for various platforms and for multiple models. WRFDA is suitable for the assimilation of a wide variety of observations, including conventional surface and upper-air soundings, ship, buoy, aircraft, satellite retrieved products, satellite radiance, radar, surface precipitation, etc. In this research, data assimilation is conducted with \"cv option 5\" which defines streamfunction, unbalanced velocity potential, unbalanced temperature, pseudo relative humidity, and unbalanced surface pressure as the control variables. The wind observations were assimilated using the wind speed and direction assimilation package based on [PERSON] et al. [57]. Four different experiments were conducted. Table 1 lists the observation data assimilated in each experiment and the data assimilation analysis times. All experiments began at 0000 UTC on 6 January and ended at 0000 UTC on 9 January 2018. The control experiment (CTRL) was a WRF regional simulation. The initial and boundary conditions were interpolated from the 0.25\({}^{\circ}\) resolution global NCEP Final Analysis (FNL). The impact of the CYGNSS data was firstly examined with two experiments--DA_cyg_fd and DA_cyg_lf, in which the 3-dimensional ensemble variational (3 DEnVar) technique was adopted in the assimilation of only CYGNSS FDS and YSLF data, respectively. Ensemble WRF forecasts with 12 members were generated with randomly perturbed initial conditions created using the ensemble transform Kalman filter (ETKF) technique [58]. The ensemble forecast was used to produce a flow-dependent background error matrix. Cycled assimilation of the CYGNSS data was conducted at 0000, 1200, 1500, and 2100 UTC from 6 to 8 January, based on the data availability. There are more CYGNSS data available for TC Irving and the WWB event at 0000 and 1500 UTC than at other times. The observational error was set as 2 m s\({}^{-1}\) for winds below 20 m s\({}^{-1}\) and 10% for winds above 20 m s\({}^{-1}\) based on the general guidance from [PERSON] et al. [40]. If there were multiple observations within a model grid box, a distance-weighted average of all observations was calculated and assimilated. The last experiment (DA_com) assimilated the combined CYGNSS wind speed, IMERG rainrate, and ASCAT vector wind data using the 4-dimensional ensemble variational (4 DEnVar) technique. The 4 DEnVar also used 12-member ensemble WRF forecasts to generate the flow dependent background error matrix. In this experiment, the CYGNSS data include YSLF data within 800 km from the center of TC Irving and FDS data elsewhere.