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Open AccessArticle

An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator

1
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Department of Atmospheric Sciences, College of Geosciences, Texas A&M University, College Station, TX 77843-3150, USA
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(1), 95; https://doi.org/10.3390/atmos11010095
Received: 19 November 2019 / Revised: 28 December 2019 / Accepted: 10 January 2020 / Published: 13 January 2020
(This article belongs to the Section Climatology)
Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many parameters. The choice of parameters is of great importance to the reliability of the simulation. Therefore, parameter sensitivity analysis is needed to optimize the parameters for the model so that the physical process of nature can be reasonably simulated. In this study, we analyzed the parameter sensitivity of a simple carbon-cycle energy balance climate model, called the Minimum Complexity Earth Simulator (MiCES), in different periods using a multi-parameter sensitivity analysis method and output measurement method. The results show that the seven parameters related to heat and carbon transferred are most sensitive among all 37 parameters. Then uncertainties of the above key parameters are further analyzed by changing the input emission and temperature, providing reference bounds of parameters with 95% confidence intervals. Furthermore, we found that ocean heat capacity will be more sensitive if the simulation time becomes longer, indicating that ocean influence on climate is stronger in the future. View Full-Text
Keywords: parameter sensitivity; MiCES model; global warming; ocean heat capacity parameter sensitivity; MiCES model; global warming; ocean heat capacity
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Chen, J.; Cui, H.; Xu, Y.; Ge, Q. An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator. Atmosphere 2020, 11, 95.

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