Poster Session P1.21 Analyzing low-level jets in their large-scale environment: Issues involving the combination of operational and research observations during IHOP

Monday, 25 June 2007
Summit C (The Yarrow Resort Hotel and Conference Center)
Edward I. Tollerud, NOAA/ESRL/GSD, Boulder, CO; and F. Caracena

Handout (399.0 kB)

Two aircraft missions during the International H20 Project (IHOP) in Oklahoma and Kansas during 2002 were dedicated to multi-scale observations of the Central Plains low-level jet (LLJ). A particular objective during these flights was a determination of the inherent scales of moisture flux within the LLJ. To accomplish this, two research platforms were utilized, each with its own observational characteristics: dropsondes with high vertical resolution released at 50 km intervals, and airborne lidar with resolvable scales of a few km in the horizontal. Given finite aircraft flight speeds, the depiction of the structure of the LLJs of necessity involved a rational juxtaposition of variations in both time and space. The addition of operational observations (profilers and radiosondes) to describe synoptic snapshots of the jets' larger-scale environment further complicates the interpretation of the LLJ structures that emerge from this witch's brew of observations.

Given the challenging analytic problem presented by these diverse observations, it is perhaps surprising that a coherent picture can in fact be constructed from them. However, in the process of analysis several observational limitations and questions of interpretation do become apparent. These include the extreme shallowness of the upslope (westward) edges of the jets that challenge the vertical resolution of operational analyses and model assimilation, and differences in scale of the longitudinal and lateral structures within the jet. We describe the large-scale fields for the two cases, and then attempt to deconvolve our set of observations into a picture of LLJs that adequately describes both their horizontal and temporal variability. Finally, we discuss issues these results raise for data assimilation.

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