Global warming projections derived from an observation-based minimal model

被引:12
|
作者
Rypdal, K. [1 ]
机构
[1] UiT Arctic Univ Norway, Dept Math & Stat, Tromso, Norway
关键词
EARTHS TEMPERATURE; CLIMATE; MEMORY;
D O I
10.5194/esd-7-51-2016
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A simple conceptual model for the global mean surface temperature (GMST) response to CO2 emissions is presented and analysed. It consists of linear long-memory models for the GMST anomaly response Delta T to radiative forcing and the atmospheric CO2-concentration response Delta C to emission rate. The responses are connected by the standard logarithmic relation between CO2 concentration and its radiative forcing. The model depends on two sensitivity parameters, alpha(T) and alpha(C), and two "inertia parameters," the memory exponents beta(T) and beta(C). Based on observation data, and constrained by results from the Climate Model Intercomparison Project Phase 5 (CMIP5), the likely values and range of these parameters are estimated, and projections of future warming for the parameters in this range are computed for various idealised, but instructive, emission scenarios. It is concluded that delays in the initiation of an effective global emission reduction regime is the single most important factor that influences the magnitude of global warming over the next 2 centuries. The most important aspect of this study is the simplicity and transparency of the conceptual model, which makes it a useful tool for communicating the issue to non-climatologists, students, policy makers, and the general public.
引用
收藏
页码:51 / 70
页数:20
相关论文
共 50 条
  • [1] An observation-based scaling model for climate sensitivity estimates and global projections to 2100
    Raphaël Hébert
    Shaun Lovejoy
    Bruno Tremblay
    Climate Dynamics, 2021, 56 : 1105 - 1129
  • [2] An observation-based scaling model for climate sensitivity estimates and global projections to 2100
    Hebert, Raphael
    Lovejoy, Shaun
    Tremblay, Bruno
    CLIMATE DYNAMICS, 2021, 56 (3-4) : 1105 - 1129
  • [3] An observation-based constraint on permafrost loss as a function of global warming
    Chadburn, S. E.
    Burke, E. J.
    Cox, P. M.
    Friedlingstein, P.
    Hugelius, G.
    Westermann, S.
    NATURE CLIMATE CHANGE, 2017, 7 (05) : 340 - +
  • [4] An observation-based constraint on permafrost loss as a function of global warming
    Chadburn S.E.
    Burke E.J.
    Cox P.M.
    Friedlingstein P.
    Hugelius G.
    Westermann S.
    Nature Climate Change, 2017, 7 (5) : 340 - 344
  • [5] Observation-based blended projections from ensembles of regional climate models
    Esther Salazar
    Dorit Hammerling
    Xia Wang
    Bruno Sansó
    Andrew O. Finley
    Linda O. Mearns
    Climatic Change, 2016, 138 : 55 - 69
  • [6] Observation-based blended projections from ensembles of regional climate models
    Salazar, Esther
    Hammerling, Dorit
    Wang, Xia
    Sanso, Bruno
    Finley, Andrew O.
    Mearns, Linda O.
    CLIMATIC CHANGE, 2016, 138 (1-2) : 55 - 69
  • [7] GRUN: an observation-based global gridded runoff dataset from 1902 to 2014
    Ghiggi, Gionata
    Humphrey, Vincent
    Seneviratne, Sonia I.
    Gudmundsson, Lukas
    EARTH SYSTEM SCIENCE DATA, 2019, 11 (04) : 1655 - 1674
  • [8] Observation-Based Longwave Cloud Radiative Kernels Derived from the A-Train
    Yue, Qing
    Kahn, Brian H.
    Fetzer, Eric J.
    Schreier, Mathias
    Wong, Sun
    Chen, Xiuhong
    Huang, Xianglei
    JOURNAL OF CLIMATE, 2016, 29 (06) : 2023 - 2040
  • [9] An Observation-Based Model for Secondary Inorganic Aerosols
    Xue, Jian
    Yuan, Zibing
    Yu, Jian Zhen
    Lau, Alexis K. H.
    AEROSOL AND AIR QUALITY RESEARCH, 2014, 14 (03) : 862 - U882
  • [10] A framework for observation-based modelling in model-based testing
    Kanstrén, Teemu
    VTT Publications, 2010, (727): : 1 - 211