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Improving the Horizontal Transport in the Lower Troposphere with Four Dimensional Data Assimilation
Citation:
GILLIAM, R. C., J. M. GODOWITCH, AND S. T. RAO. Improving the Horizontal Transport in the Lower Troposphere with Four Dimensional Data Assimilation. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 53(June ):186-201, (2012).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
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, bservations 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.
URLs/Downloads:
Atmospheric Environment
Improving the Horizontal Transport in the Lower Troposphere with Four Dimensional Data Assimilation (PDF, NA pp, 2546 KB, about PDF)