Inferring Northern Hemisphere Continental Warming Patterns from the Amplitude and Phase of the Seasonal Cycle in Surface Temperature

Author:

McKinnon Karen A.12ORCID,Huybers Peter3

Affiliation:

1. a Department of Statistics and Data Science, Institute of the Environment and Sustainability, University of California, Los Angeles, Los Angeles, California

2. b Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, Los Angeles, California

3. c Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts

Abstract

Abstract The seasonal cycle in temperature is a large and well-observed response to radiative forcing, suggesting its potential as a natural analog to human-caused climate change. Although there have been advances constraining some climate feedback parameters using seasonal observations, the seasonal cycle has not been used to inform about the local temperature sensitivity to greenhouse gas forcing. In this study, we uncover a nonlinear relationship between the amplitude and phase of the seasonal cycle and forced temperature trends in seven CMIP5-era large ensembles across the Northern Hemisphere extratropical continents. We develop a mixture energy balance model that reproduces this relationship and reveals the unexpected finding that the phasing of the seasonal cycle—in addition to the amplitude—contains information about local temperature sensitivity to seasonal forcing over land. Using this energy balance model framework, we compare the pattern and magnitude of the seasonally inferred sensitivity of the surface temperature response to anthropogenic radiative forcing. The seasonally constrained model largely reproduces the pattern of human-caused temperature trends seen in climate models (r = 0.81, p value < 0.01), including polar amplification, but the magnitude of the response is smaller by about a factor of 3. Our results show the relevance of both phasing and amplitude for constraining patterns of local feedbacks and suggest the utility of additional research to better understand the differences in sensitivity between seasonal and greenhouse gas forcing. Significance Statement Warming in response to increased greenhouse gases is not spatially uniform across land. We wanted to understand whether the familiar seasonal cycle in temperature could provide information about climate change. We found that climate models show a strong link between the seasonal cycle and future warming: places with a larger and more delayed temperature response to the seasonal cycle in solar forcing tend to warm more across the Northern Hemisphere midlatitudes. A very simple model for the climate system, whose parameters are based on the seasonal cycle, captures the pattern but not the magnitude of warming. Our findings suggest that there are some similarities between the processes that control temperature change on seasonal and climate change time scales, but that we must understand the difference between seasonal and longer-term sensitivity to warming before the seasonal cycle can be used to reduce uncertainty about climate change.

Funder

David and Lucile Packard Foundation

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference41 articles.

1. The dependence of radiative forcing and feedback on evolving patterns of surface temperature change in climate models;Andrews, T.,2015

2. Time-varying climate sensitivity from regional feedbacks;Armour, K. C.,2013

3. The effective number of spatial degrees of freedom of a time-varying field;Bretherton, C. S.,1999

4. Greater future global warming inferred from Earth’s recent energy budget;Brown, P. T.,2017

5. Amplified warming of extreme temperatures over tropical land;Byrne, M. P.,2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3