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Convective Parameters Derived from Radiosonde Data (SONDEPARAM) Value-Added Product Report

Technical Report ·
DOI:https://doi.org/10.2172/1909985· OSTI ID:1909985
 [1];  [1];  [1];  [1]
  1. Brookhaven National Laboratory (BNL), Upton, NY (United States)
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Radiosondes provide fundamental observations of the vertical profile of atmospheric state (pressure, temperature, humidity, and winds), with important implications for subsequent studies on environmental controls on cloud conditions. Within convective cloud environments, there is an increasing demand for additional value-added products (VAPs) to facilitate the use of U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility radiosonde data sets. Such VAPs should provide quick and reliable estimates for several standard radiosonde parameters or quantities of interest using common assumptions, as well as open, flexible code for visualization and user interaction. The Convective Parameters Derived from Radiosonde Data (SONDEPARAM) VAP will apply several robust algorithms used in Wang et al. (2020) for the calculation of useful radiosonde convective cloud parameters, including the convective available potential energy (CAPE), convective inhibition (CIN), and other convective parameters, for several different assumptions regarding the initial parcel characteristics (i.e., surface-based, most unstable, mixed layer). These ARM VAP codes are developed in open, flexible Python formats, with the intention that these parameters/calculations will be incorporated into traditional ARM quick-look radiosonde plotting, yet associated with user-available codes for ease in user reproduction and assumption modification.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM), Data Center
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Contributing Organization:
Pacific Northwest National Laboratory (PNNL), Brookhaven National Laboratory (BNL), Argonne National Laboratory (ANL), Oak Ridge National Laboratory (ORNL)
DOE Contract Number:
AC06-76RL01830
OSTI ID:
1909985
Report Number(s):
DOE/SC-ARM-TR-284
Country of Publication:
United States
Language:
English

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Related Subjects

54 ENVIRONMENTAL SCIENCES