The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory
Abstract
Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. One of the challenges is how to design strategies to best use these observations to understand these properties and evaluate weather and climate models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud resolving models (CRMs) to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (radar and lidar) products. CR-SIM allows direct comparison between an atmospheric model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical assumptions used in the atmospheric model. CR-SIM has the flexibility to easily incorporate additional microphysical modules, such as microphysical schemes and scattering calculations, and expand the applications to simulate multi-sensor retrieval products. In this paper, we present several applications of CR-SIM for evaluating the representativeness of cloud microphysics and dynamics in a CRM, quantifying uncertainties in radar-lidar integrated cloud products and multi-Doppler wind retrievals, and optimizing radar sampling strategy using observing system simulation experiments. These applications demonstrate the application of CR-SIM as a virtual observatory operator on high-resolution model output for a consistent comparison between model results and observations to aid interpretation of the differences and improve understanding of the representativeness errorsmore »
- Authors:
-
[4]
- Stony Brook Univ., NY (United States)
- McGill Univ., Montreal, QC (Canada)
- Stony Brook Univ., NY (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
- Brookhaven National Lab. (BNL), Upton, NY (United States)
- Publication Date:
- Research Org.:
- Brookhaven National Laboratory (BNL), Upton, NY (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1605677
- Report Number(s):
- BNL-213732-2020-JAAM
Journal ID: ISSN 1991-959X.
- Grant/Contract Number:
- SC0012704; KP170304
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Geoscientific Model Development
- Additional Journal Information:
- Journal Volume: 13; Journal Issue: 4; Journal ID: ISSN 1991-959X.
- Publisher:
- European Geosciences Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Oue, Mariko, Tatarevic, Aleksandra, Kollias, Pavlos, Wang, Dié, Yu, Kwangmin, and Vogelmann, Andrew. The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory. United States: N. p., 2020.
Web. doi:10.5194/gmd-13-1975-2020.
Oue, Mariko, Tatarevic, Aleksandra, Kollias, Pavlos, Wang, Dié, Yu, Kwangmin, & Vogelmann, Andrew. The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory. United States. https://doi.org/10.5194/gmd-13-1975-2020
Oue, Mariko, Tatarevic, Aleksandra, Kollias, Pavlos, Wang, Dié, Yu, Kwangmin, and Vogelmann, Andrew. Tue .
"The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory". United States. https://doi.org/10.5194/gmd-13-1975-2020. https://www.osti.gov/servlets/purl/1605677.
@article{osti_1605677,
title = {The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory},
author = {Oue, Mariko and Tatarevic, Aleksandra and Kollias, Pavlos and Wang, Dié and Yu, Kwangmin and Vogelmann, Andrew},
abstractNote = {Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. One of the challenges is how to design strategies to best use these observations to understand these properties and evaluate weather and climate models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud resolving models (CRMs) to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (radar and lidar) products. CR-SIM allows direct comparison between an atmospheric model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical assumptions used in the atmospheric model. CR-SIM has the flexibility to easily incorporate additional microphysical modules, such as microphysical schemes and scattering calculations, and expand the applications to simulate multi-sensor retrieval products. In this paper, we present several applications of CR-SIM for evaluating the representativeness of cloud microphysics and dynamics in a CRM, quantifying uncertainties in radar-lidar integrated cloud products and multi-Doppler wind retrievals, and optimizing radar sampling strategy using observing system simulation experiments. These applications demonstrate the application of CR-SIM as a virtual observatory operator on high-resolution model output for a consistent comparison between model results and observations to aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are publicly available to the scientific community.},
doi = {10.5194/gmd-13-1975-2020},
journal = {Geoscientific Model Development},
number = 4,
volume = 13,
place = {United States},
year = {Tue Apr 21 00:00:00 EDT 2020},
month = {Tue Apr 21 00:00:00 EDT 2020}
}
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