Observing Profiles of Derived Kinematic Field Quantities Using a Network of Profiling Sites

Journal Article · 28 February 2022 · Journal of Atmospheric and Oceanic Technology

DOI: https://doi.org/10.1175/JTECH-D-21-0061.1 · OSTI ID:1855515

Wagner, Timothy J. ^[1]; Turner, David D. ^[2]; Heus, Thijs ^[3]; Blumberg, William G. ^[4]

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1. a Space Science and Engineering Center, University of Wisconsin–Madison, Madison, Wisconsin
2. b NOAA/Global Systems Laboratory, Boulder, Colorado
3. c Department of Physics, Cleveland State University, Cleveland, Ohio
4. d NASA Goddard Space Flight Center, Greenbelt, Maryland

Abstract Observations of thermodynamic and kinematic parameters associated with derivatives of the thermodynamics and wind fields, namely, advection, vorticity, divergence, and deformation, can be obtained by applying Green’s theorem to a network of observing sites. The five nodes that comprise the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) profiling network, spaced 50–80 km apart, are used to obtain measurements of these parameters over a finite region. To demonstrate the applicability of this technique at this location, it is first applied to gridded model output from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model, using profiles from the locations of ARM network sites, so that values calculated from this method can be directly compared to finite difference calculations. Good agreement is found between both approaches as well as between the model and values calculated from the observations. Uncertainties for the observations are obtained via a Monte Carlo process in which the profiles are randomly perturbed in accordance with their known error characteristics. The existing size of the ARM network is well suited to capturing these parameters, with strong correlations to model values and smaller uncertainties than a more closely spaced network, yet it is small enough that it avoids the tendency for advection to go to zero over a large area.

• Research Organization: ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• Contributing Organization: ANL; BNL; ORNL; PNNL
• Grant/Contract Number: SC0020114
• OSTI ID: 1855515
• Journal Information: Journal of Atmospheric and Oceanic Technology, Journal Name: Journal of Atmospheric and Oceanic Technology Journal Issue: 3 Vol. 39; ISSN 0739-0572
• Publisher: American Meteorological SocietyCopyright Statement
• Country of Publication: United States
• Language: English