Abstract
Abstract. 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 CO2 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.
Highlights
The Earth system is a complex interplay of physical, chemical, and biological processes that interact in nonlinear ways (Ladyman et al, 2013; Lorenz, 1963; Rind, 1999; Williams, 2005)
This paper describes the results of a 50-year simulation with a simple parameterization of fossil fuel CO2 emissions at model grid-point scale, integrating the POPEM module into the Community Earth System Model (CESM)
The paper is organized as follows: in Sect. 2, we present the validation of the POPEM stand-alone mode and set the framework for evaluating the impact of POPEM parameterization – its incorporation into the CESM and the testing framework; in Sect. 3, we compare the outputs of CONTROL and POPEM runs and see how they compare with observations
Summary
The Earth system is a complex interplay of physical, chemical, and biological processes that interact in nonlinear ways (Ladyman et al, 2013; Lorenz, 1963; Rind, 1999; Williams, 2005). One of the most important advances in this field has been the use of coupled numerical climate models, dubbed Earth system models or ESMs (Edwards, 2011; Flato, 2011; Schellnhuber, 1999). Unresolved processes (Williams, 2005), limited computational resources (Shukla et al, 2010; Washington et al, 2009), and model uncertainties (Baumberger et al, 2017; Lahsen, 2005; Steven and Bony, 2013) are ongoing issues that still require attention and further improvement
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