Lower and middle-tropospheric observations are disproportionately sparse, both temporally and geographically, when compared to surface observations. The limited density of observations is likely one of the largest constraints in numerical weather prediction. Atmospheric observations collected by a multi-function in-situ atmospheric sensor on 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 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 seven years, the equipage of the sensors has expanded beyond CONUS to include Alaska and Mexico on 10 fleets of regional airlines. In addition to the standard commercial airline program, a miniaturized version of the sensor has been deployed on several unmanned aerial vehicles (UAVs). Upon completion of the 2011 installations, more than 6000 daily sounding will be produced in North America. Short-range future equipage plans include a major domestic carrier with transoceanic routes, as well as a large European carrier.
An overview will be provided on the status of the TAMDAR sensor network deployment and data availability, as well as an update on data quality, error statistics, and operational forecasting utility, both from soundings and various data assimilation techniques. Current data assimilation optimizations include splitting the ascent, descent, and cruise observations into different phases of flight, correcting for the magnetic deviation bias in heading instrumentation, and isolating wind speed versus wind direction errors.