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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-207
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-207
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 02 Sep 2019

Submitted as: model description paper | 02 Sep 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

The Cloud Resolving Model Radar Simulator (CR-SIM) Version 3.2: Description and Applications of a Virtual Observatory

Mariko Oue1, Aleksandra Tatarevic2, Pavlos Kollias1,3, Dié Wang3, Kwangmin Yu4, and Andrew M. Vogelmann3 Mariko Oue et al.
  • 1School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, 11794, USA
  • 2Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, H3A 0G4, Canada
  • 3Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, 11973, USA
  • 4Computational Science Initiative, Brookhaven National Laboratory, Upton, 11973, USA

Abstract. Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. A challenge is how to design strategies to best use these observations to understand the atmosphere and evaluate atmospheric numerical prediction models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution atmospheric models to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (multi-radar and radar-lidar) integrated products. CR-SIM allows comparisons of the same variables between an atmospheric model simulation and remote sensing products using a forward modeling framework consistent with the microphysical assumptions used in the numerical model simulations. In this paper, we present several applications of CR-SIM for evaluation of a numerical model, quantification of retrieval uncertainty, and optimization of radar sampling strategy using observing system simulation experiments. These applications demonstrate that the application of CR-SIM as a virtual observatory operator on high-resolution model output helps interpret the differences between model results and observations and also improve under-standing of the representativeness errors due to the sampling limitations of the ground-based observatories. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are freely available to scientific community.

Mariko Oue et al.
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Status: open (until 28 Oct 2019)
Status: open (until 28 Oct 2019)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Mariko Oue et al.
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