Extended Abstract (1.9M)J11.6
The Potential Utility of TAMDAR Data in Air Quality Forecasting
Neil A. Jacobs, AirDat LLC, Morrisville, NC; and M. Croke, P. Childs, and Y. Liu
Observations collected by a multi-function in-situ atmospheric sensor on commercial aircraft, called the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) sensor, contain measurements of humidity, pressure, temperature, winds aloft, icing, and turbulence, along with the corresponding location, time, and altitude from built-in GPS are relayed via satellite in real-time to a ground-based network operations center.
The TAMDAR sensor was originally deployed by AIrDat in December 2004 on a fleet of 63 Saab 340s operated by Mesaba Airlines in the Great Lakes region as a part of the NASA-sponsored Great Lakes Fleet Experiment (GLFE). Over the last five years, the equipage of the sensors has expanded beyond CONUS to include Alaska and Mexico on Horizon, Republic, Chautauqua, Shuttle America, PenAir, Piedmont, Frontier Alaska, AeroMexico Connect and Mesaba Airlines, as well as a few research aircraft. Upon completion of the 2009 installations, more than 6000 daily sounding will be produced in North America at more than 360 locations.
The data is presently being assimilated into an operational high-resolution (4km grid) CONUS-scale Advanced Research WRF (ARW), known as the NCAR-AirDat RTFDDA-WRF, using the NCAR/ATEC Real-Time Four-Dimensional Data Assimilation (RTFDDA) technologies. The system is built upon the WRF model framework, but uses a Newtonian relaxation observational nudging data assimilation engine, which allows the model to more effectively assimilate asynoptic measurements.
This new TAMDAR data set will be discussed in terms of the potential utility in air quality research and applications, including determining mixing-layer heights and evolutions, observation-based forecast adjustments, as well as forecast verification. In addition to the direct use of the TAMDAR soundings, the output from the NCAR-AirDat RTFDDA-WRF, which effectively assimilates TAMDAR data and other diverse observations, provides a unique and useful initialization for air quality models.
Joint Session 11, Air Quality Forecasting II
Thursday, 21 January 2010, 3:30 PM-5:00 PM, B316
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