Sensitivity of Convective Initiation Prediction to Near - Surface Moisture 8 when Assimilating Radar Refractivity : Impact Tests using OSSEs

40 The ARPS 3DVAR system is enhanced to include the analysis of radar-derived 41 refractivity measurements. These refractivity data are most sensitive to atmospheric moisture 42 content and provide high-resolution information on near-surface moisture that is important to 43 convective initiation (CI) and precipitation forecasting. Observing system simulation 44 experiments (OSSEs) are performed using simulated refractivity data. The impacts of refractivity 45 on CI and subsequent forecasts are investigated in the presence of varying observation error, 46 radar location, data coverage, and different uncertainties in the background field. Cycled 47 refractivity assimilation and forecasts are performed and results compared to the truth. A 48 simulation for the May 19, 2010 Central Plain convection case is used for the OSSEs. It 49 involves a large storm system, large convective available potential energy (CAPE), and little 50 convective inhibition, allowing for CI along a warm front in northern Oklahoma and ahead of a 51 dryline later to the southwest. Emphasis is placed on the quality of moisture analyses and the 52 subsequent forecasts of CI. Results show the ability of refractivity assimilation to correct low53 level moisture errors, to lead to improved CI forecast. Equitable threat scores for reflectivity are 54 generally higher when refractivity data are assimilated. Tests show small sensitivity to increased 55 observational error or ground clutter coverage. There is a larger sensitivity to the data coverage 56 when a single radar is available. 57 58