Commercial aircraft now provide more than 150,000 observations per day of winds and temperature aloft over the contiguous United States. The general term for these data is AMDAR (Aircraft Meteorological Data Reports). These data have been shown to improve both short-term and long-term weather forecasts (Moninger, et al., 2003). One weakness of the current AMDAR data set is the absence of data below 25,000 ft between major airline hubs and the almost complete absence of water vapor data at any altitude. To address this weakness, a sensor called TAMDAR (Tropospheric AMDAR), developed by AirDat, LLC, under sponsorship of the NASA Aviation Safety and Security Program, has been deployed on approximately 60 regional turboprop aircraft operated by Mesaba airlines flying over the middle U. S. (Daniels, et al., 2006) Like the rest of the AMDAR fleet, TAMDAR measures winds and temperature. But unlike most of the rest of the fleet, TAMDAR measures humidity, turbulence, and icing. By mid-2007, AirDat expects to have more than 400 aircraft operating in the U.S. GSD has built an extensive system for evaluating the quality of TAMDAR and AMDAR data, and has applied this system for the two years that TAMDAR has been in operation. Our evaluation system relies on the Rapid Update Cycle (RUC) numerical model and data assimilation system (Benjamin, et al., 2004a,b). The RUC provides a common background against which AMDAR and TAMDAR data are compared. In particular, we look at differences between RUC background fields (one-hour forecasts from the previous hour) and aircraft data. Results suggest that TAMDAR data have error characteristics different from those of traditional AMDAR fleets, which consist of long-haul jet aircraft, and that it may be useful and important to treat TAMDAR differently than data from other fleets when assimilating the data into models. This extends our presentation given at the AMS Annual Meeting last year (Moninger, et al., 2006): we now include results from 2006—a period during which TAMDAR data processing, data resolution, quality control, and assimilation into the RUC all changed. This is a companion paper to one by Benjamin et al. (2007), in which the impact of TAMDAR on the RUC is assessed, and one by Szoke, et al. (2007), in which the statistical impact of individual events is examined. We believe these studies are particularly important as the U.S. government considers paying a larger portion of the costs associated with aircraft-measured meteorological data. In this new era, the government will have to more carefully monitor the quality of data from a variety of aircraft fleets, and provide detailed data quality information to both data providers and data users.
This publication was presented at the following: