Improving the representation of anthropogenic CO<sub>2</sub> emissions in climate models: impact of a new parameterization for the Community Earth System Model (CESM)

<p>ESMs (Earth system models) are important tools that help scientists understand the complexities of the Earth's climate. Advances in computing power have permitted the development of increasingly complex ESMs and the introduction of better, more accurate parameterizations of processe...

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Bibliographic Details
Main Authors: A. Navarro, R. Moreno, F. J. Tapiador
Format: Article
Language:English
Published: Copernicus Publications 2018-08-01
Series:Earth System Dynamics
Online Access:https://www.earth-syst-dynam.net/9/1045/2018/esd-9-1045-2018.pdf
Description
Summary:<p>ESMs (Earth system models) are important tools that help scientists understand the complexities of the Earth's climate. Advances in computing power have permitted the development of increasingly complex ESMs and the introduction of better, more accurate parameterizations of processes that are too complex to be described in detail. One of the least well-controlled parameterizations involves human activities and their direct impact at local and regional scales. In order to improve the direct representation of human activities and climate, we have developed a simple, scalable approach that we have named the POPEM module (POpulation Parameterization for Earth Models). This module computes monthly fossil fuel emissions at grid-point scale using the modeled population projections. This paper shows how integrating POPEM parameterization into the CESM (Community Earth System Model) enhances the realism of global climate modeling, improving this beyond simpler approaches. The results show that it is indeed advantageous to model CO<sub>2</sub> emissions and pollutants directly at model grid points rather than using the same mean value globally. A major bonus of this approach is the increased capacity to understand the potential effects of localized pollutant emissions on long-term global climate statistics, thus assisting adaptation and mitigation policies.</p>
ISSN:2190-4979
2190-4987