Assimilating high-density flight-level and dropsonde data from operational reconnaissance aircraft at reduced spatial density in NAVDAS-AR

The NOAA P-3 and USAF WC-130J reconnaissance aircraft have provided automated high-density high-accuracy (HDOB) flight-level observations of temperature, humidity, and winds on a campaign basis for the past few years. A preliminary examination of data from several 2009 flights shows that these data are in reasonable agreement with background fields from NOGAPS, the U.S. Navy's operational global numerical weather prediction model. This suggests that they might be beneficial for use in NAVDAS-AR, the U.S. Navy's operational 4DVAR data assimilation system, especially since these aircraft are typically flying in tropical or winter storms that other aircraft are actively avoiding. However, the usual 30sec sampling frequency makes the HDOB data much denser along the aircraft's track than conventional aircraft observations from jet-powered commercial carriers, which use a sampling frequency of no less than 60sec in level flight mode and which are traveling much faster than these turbo-prop powered aircraft. In addition, HDOB data in the core of a hurricane depict a more intense storm with stronger gradients than NOGAPS is capable of resolving. The HDOB data must therefore be preprocessed to reduce the data density and to exclude observations from regions of strong gradients such as hurricane cores.

Dropsondes from these same aircraft are being deployed at increased spatial densities in recent years, sometimes into the core of the hurricane as well, calling into question the current practice of using all available dropsondes NAVDAS-AR. The same two issues—reducing data density and excluding observations from hurricane cores—must be addressed for these data as well. Preprocessing strategies are discussed in this presentation, together with results from selected flights during 2009 and 2010.