Improving the horizontal transport in the lower troposphere with four dimensional data assimilation

The physical processes involved in air quality modeling are governed by dynamically-generated meteorological model fields. This research focuses on reducing the uncertainty in the horizontal transport in the lower troposphere by improving the four dimensional data assimilation (FDDA) strategy in retrospective meteorological modeling. In particular, characterization of winds in the nocturnal low-level jet and overlying residual layer is crucial to accurately model regional-scale ozone transport in the key airsheds of the US. Since model errors in wind speed and direction lead to spatial displacements of pollution plumes, observations not routinely used in previous retrospective modeling are introduced through FDDA in an effort to help reduce this transport uncertainty. Prior to the main modeling sensitivity, an observational uncertainty analysis was pursued to identify uncertainties in the wind speed and direction in the lower 1-km of the troposphere that are inherent in the observational data sets used in FDDA. Comparisons of observations among various platforms (radar wind profilers, radiosonde soundings and weather radar profiles) taken in close proximity revealed that an uncertainty of approximately 1.8 m s(-1) for wind speed and about 20 for wind direction was intrinsic to the measurements. In the modeling sensitivities, some minimal improvement of modeled winds within the convective planetary boundary layer (PBL) was found when surface analysis nudging of wind was eliminated. Improvements in the nocturnal jet and residual layer winds at night are demonstrated as a reaction to the use of new observations in the data assimilation in layers above the stable PBL. There is also evidence that the assimilated observations above the convective PBL during the day led to improvements of winds within the PBL, which may relieve the need of nudging within the PBL, including surface analysis nudging. Published by Elsevier Ltd.