Abstract

Abstract. Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W−1 m2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.

Highlights

  • Climate change projections depend highly on future scenarios of climate mitigation actions

  • Scaling with ERFfsst allows for a simpler comparison of responses between different forcing agents, but it changes the sign of responses in the case of sulx5 experiments

  • The local temperature responses related to longwave and shortwave TOA components build up from a combination of the local instantaneous top-of-atmosphere radiative forcing and rapid adjustments associated with each term, as well as a temperature-dependent feedback which adjusts its magnitude as the surface temperature changes, as described in the end of Sect. 2.1

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Summary

Introduction

Climate change projections depend highly on future scenarios of climate mitigation actions. In addition to uncertainty arising from different possible futures in timescales of decades, the climate projection uncertainties are dominated by the climate model response uncertainty (Hawkins and Sutton, 2009; Lehner et al, 2020). This arises from structural differences between different climate models. Climate models differ in how they represent the radiative forcing of anthropogenic greenhouse gases and aerosols. K. Nordling et al.: Understanding the surface temperature response

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