10th Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface (IOAS-AOLS)


AMDAR optimization studies at the Earth System Research Laboratory / Global Systems Division (Formerly paper P2.1 from 12 ARAM)

William R. Moninger, NOAA/ESRL/GSD, Boulder, CO; and S. G. Benjamin, D. Dévényi, B. D. Jamison, B. Schwartz, T. L. Smith, and E. Szoke

Commercial aircraft now provide more than 130,000 observations per day of winds and temperature aloft over the contiguous U.S. 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. The costs of gathering these observations (primarily communications costs) are large and will increase as the number of observations increases. For this reason there is considerable interest in finding the optimum number of observations that need to be taken and transmitted under various weather regimes.

The Earth System Research Laboratory / Global Systems Division (formerly the Forecast Systems Laboratory) has, under FAA sponsorship, embarked on a study to determine the optimal amount of data needed. We are approaching this problem in two ways. First, we are studying how human forecasters are currently using aircraft directly in their bench forecasting. Second, we are looking at the behavior of the RUC model as we vary the amount of AMDAR data input. We will look at the sensitivity of RUC forecast skill, verified against RAOBs, to AMDAR data. Also, using a method derived from the work of Grace Wahba, we will also look at analysis sensitivity to varying amounts of AMDAR data using cross-validation.

Ultimately, we hope to develop a RUC-based "aircraft data need field" that will predict the amount of AMDAR data needed to correctly forecast expected weather conditions.

We will report on the initial results of our studies.

extended abstract  Extended Abstract (380K)

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Session 6, Assimilation of Observations (Ocean, Atmosphere, and Land Surface) into Models: Assimilation Methods; Minimization Techniques; Forward Models and Their Adjoints; Incorporation of Constraints; Error Statistics
Wednesday, 1 February 2006, 8:30 AM-12:00 PM, A405

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