Assimilating Aeolus Wind Profiles – Assessing the Benefit of Using Variational Quality Control During Tropical Cyclones
First evaluation of Aeolus winds profiles with NOAA’s global data assimilation and forecast system showed promising data quality characteristics. In an effort to improve the benefits from the assimilation of Aeolus Mie-cloudy and Rayleigh-clear winds in NOAA’s global , the NCEP variational quality control (NCEP-VQC) algorithm was implemented for the Aeolus observations. This algorithm is applied during the minimization process and uses optimal control theory principles to treat outliers in the probability density function (PDF) of departure statistics assuming observation errors follow a family of logistic distributions. In the case of Aeolus Mie-cloudy and Rayleigh-clear winds, the NCEP-VQC algorithm permitted the relaxation of the gross error and one of the recommended ESA quality controls, assigned adaptive observation weights on a range from 0 to 1, and led to an increase in the number of retained observations for the calculation of global analyses. We will discuss the advantages of implementing the NCEP-VQC algorithm in the Aeolus assimilation and the benefits in retaining more wind profiles to contribute to the analysis calculation, and will show improvements on the initialization and short-term forecasts on several tropical cyclone cases.
