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Measuring the Eenergy for Thunderstorms
Published: March 21, 2017
Posted: May 10, 2017

ARM long-term datasets provide information to evaluate satellite estimates of convective available potential energy, a critical parameter in forecasting severe weather.

The Science  
Convective Available Potential Energy (CAPE) is a measure of the atmospheric energy available to thunderstorms. CAPE is one of the physical quantities used by operational meteorologists when issuing severe weather convective watches and warnings. Meteorologists usually estimate this parameter from weather balloon (radiosonde) observations.  The planned future operational weather satellite system will use advanced satellite technology to provide vertical profiles of temperature and moisture twice per day.  These profiles may be able to provide important information on CAPE in near real-time for weather forecasts.  In this study, scientists use 10 years of radiosonde observations from the ARM Southern Great Plains (SGP) site in Oklahoma to assess how well the new satellite system will be able to estimate CAPE.

The Impact
The long-term data sets from the ARM facility provided the dataset needed to make a statistical assessment of the satellite temperature and moisture profiles that accounted for systematic biases and random noise characteristics of the satellite retrievals.  If CAPE was calculated directly from the satellite measurements, it had a low correlation with the values calculated from the more detailed ARM radiosondes.  However, if the scientists combined the vertical profile from the satellite above 2 m with the surface values from the ARM data, they were able to get good agreement in the CAPE values.  These results suggest that merging surface observations with satellite derived thermodynamic profiles could make better use of the satellite spatial coverage and temporal sampling for estimation of CAPE in near-real time, potentially improving weather forecasts of severe weather.

Summary
Convective Available Potential Energy (CAPE) is one of the physical quantities used by operational meteorologists when issuing severe weather convective watches and warnings. Recent advances in satellite technology could provide timely observations of atmospheric temperature and water vapor profiles over the continental United States. However, only limited validation exists in the literature to characterize uncertainties in CAPE derived from the new satellite sensors. In this study, ten years of Vaisala RS92 radiosonde observations from the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (DOE ARM SGP) site were matched to overpasses of the NASA Aqua satellite from January 2005 through December 2014. Vertical profiles of temperature and water vapor from the NASA Atmospheric InfraRed Sounder (AIRS) were extracted in a region surrounding the DOE ARM SGP central facility near Lamont, Oklahoma. Surface-based CAPE was computed using software consistent with methods used by the National Weather Service Storm Prediction Center (SPC). The one-to-one correspondence of the AIRS-derived CAPE with the ARM radiosonde-derived CAPE has a correlation coefficient of only 0.34. Substitution of the ARM radiosonde surface values into the AIRS profiles improves the correlation to 0.95. The use of AIRS profiles above the surface level provides very similar surface-based CAPE values to those computed from Vaisala radiosondes.

Contacts (BER PM)
Sally McFarlane
ARM Program Manager
Sally.McFarlane@science.doe.gov

(PI Contact)
Robert Knuteson
University of Wisconsin-Madison
Space Science and Engineering Center
robert.knuteson@ssec.wisc.edu

Funding
This research was supported by NOAA grant NA10NES4400013.

Publication
Gartzke J, R Knuteson, G Przybyl, S Ackerman, and H Revercomb. 2017. "Comparison of Satellite, Model, and Radiosonde Derived Convective Available Potential Energy (Cape) in the Southern Great Plains Region." Journal of Applied Meteorology and Climatology.  DOI: 10.1175/jamc-d-16-0267.1 (Reference link)

Topic Areas:

  • Facility: DOE ARM User Facility

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

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