A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations
Abstract
Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.
- Authors:
-
- Brookhaven National Laboratory (BNL), Upton, NY (United States)
- Brookhaven National Laboratory (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.
- Publication Date:
- Research Org.:
- Brookhaven National Laboratory (BNL), Upton, NY (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1176991
- Report Number(s):
- BNL-107327-2015-JA
Journal ID: ISSN 1748--9326; R&D Project: 2016-BNL-EE631EECA-Budg; KP1703020
- Grant/Contract Number:
- SC00112704
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Environmental Research Letters
- Additional Journal Information:
- Journal Volume: 9; Journal Issue: 12; Journal ID: ISSN 1748--9326
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Huang, Dong, and Liu, Yangang. A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations. United States: N. p., 2014.
Web. doi:10.1088/1748-9326/9/12/124022.
Huang, Dong, & Liu, Yangang. A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations. United States. https://doi.org/10.1088/1748-9326/9/12/124022
Huang, Dong, and Liu, Yangang. Thu .
"A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations". United States. https://doi.org/10.1088/1748-9326/9/12/124022. https://www.osti.gov/servlets/purl/1176991.
@article{osti_1176991,
title = {A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations},
author = {Huang, Dong and Liu, Yangang},
abstractNote = {Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.},
doi = {10.1088/1748-9326/9/12/124022},
journal = {Environmental Research Letters},
number = 12,
volume = 9,
place = {United States},
year = {Thu Dec 18 00:00:00 EST 2014},
month = {Thu Dec 18 00:00:00 EST 2014}
}
Web of Science
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