Assimilating cloud-affected visible & infrared satellite observations in idealized simulations

Abstract

<p>Clouds are the first area-wide observable signal of convection. Although heavily used in nowcasting applications, the use of cloud-affected satellite observations in data assimilation is very limited.</p> <p>This work aims to estimate the potential impact of assimilating cloud-affected satellite observations of visible (0.6 µm) and near thermal infrared wavelength (6.2 µm and 7.3 µm) relative to the impact of assimilating radar reflectivity observations. The observation types are evaluated in observing system simulation experiments (OSSE) featuring two cases: isolated and scattered supercells. In the first case, a supercell is triggered by a warm bubble (temperature perturbation) with uncertain location and strength but equal evolution in time. In the second case, random perturbations give rise to numerous supercells scattered throughout the domain, which are in different stages of their lifetime. Observations are simulated using the radiative transfer model RTTOV/MFASIS and assimilated by the Ensemble Adjustment Kalman Filter in the Data Assimilation Research Testbed (DART). The Weather Research and Forecasting (WRF) model at 2-km grid resolution was used for forecasts. </p> <p>Results show that the forecast impact is notably different in the two cases. For example, the Fractions Skill Score of precipitation and cloudiness indicates that satellite observations can be as beneficial as three-dimensional radar reflectivity observations in the first case, in which the prior contains no error in the stage of storm development but only in horizontal position and strength. Hence, the vertical structure information contained in three-dimensional radar reflectivity does not seem to add value compared to satellite observations, resulting in a similar impact of both observation types. In the second case, however, three-dimensional radar observations constrain the vertical structure and improve upon forecasts that only use satellite observations.</p>