Climate Model Uncertainty and Trend Detection in Regional Sea Level Projections: A Review

被引:0
|
作者
Mark Carson
Kewei Lyu
Kristin Richter
Mélanie Becker
Catia M. Domingues
Weiqing Han
Laure Zanna
机构
[1] Universität Hamburg,Centrum für Erdsystemforschung und Nachhaltigkeit
[2] CSIRO Oceans and Atmosphere,Centre for Southern Hemisphere Oceans Research (CSHOR)
[3] University of Innsbruck,Institute for Atmospheric and Cryospheric Sciences
[4] Littoral,IMAS
[5] Environment and Societies (LIENSs) - UMR 7266, ACE CRC
[6] CNRS, CLEX
[7] University of Tasmania,Department of Atmospheric and Oceanic Sciences
[8] University of Colorado,Department of Physics, Atmospheric Ocean and Planetary Physics
[9] University of Oxford,undefined
来源
Surveys in Geophysics | 2019年 / 40卷
关键词
Sea level; Climate projections; Regional sea level; Uncertainty; Trends; Trend detection; Time of emergence; Climate model;
D O I
暂无
中图分类号
学科分类号
摘要
Projections of future sterodynamic sea level change from global climate models are associated with different sources of uncertainty. From a scientific, societal and policy-making perspective, it is relevant to both understand and reduce uncertainty in projections of climate change. Here, we review recent findings which describe, and shed light on, climate model uncertainty focusing particularly on two types of model uncertainty that contribute to the currently large spread in dynamical sea level patterns (i.e., regional sea level relative to the global mean). These uncertainties are: (1) intermodel uncertainty due to differences in models’ responses in a warming climate and (2) internal model variability due to an individual model’s own climate variability. On timescales longer than about 50 years from now, anthropogenic sterodynamic (dynamic plus global mean) sea level trends from middle- and high-end forcing scenarios will be larger than internal model variability. By 2100, these anthropogenic trends will also be larger than intermodel uncertainty when global mean thermosteric sea level rise and/or melting contributions from land ice are considered along with dynamic sea level changes. Furthermore, we discuss projections of future coastal sea level from the perspective of global climate models as well as from downscaled efforts based on regional climate models. Much knowledge and understanding has been achieved in the last decade from intermodel experiments and studies of sea level process-based model; here, the prospects for improving coastal sea level and reducing sea level uncertainty are discussed.
引用
收藏
页码:1631 / 1653
页数:22
相关论文
共 50 条
  • [21] The potential to reduce uncertainty in regional runoff projections from climate models
    Lehner, Flavio
    Wood, Andrew W.
    Vano, Julie A.
    Lawrence, David M.
    Clark, Martyn P.
    Mankin, Justin S.
    NATURE CLIMATE CHANGE, 2019, 9 (12) : 926 - +
  • [22] Quantifying uncertainty in future sea level projections downscaled from CMIP5 global climate models
    Sithara, S.
    Pramada, S. K.
    Thampi, Santosh G.
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2024, 38 (05) : 2065 - 2079
  • [23] Quantifying uncertainty in future sea level projections downscaled from CMIP5 global climate models
    S. Sithara
    S. K. Pramada
    Santosh G. Thampi
    Stochastic Environmental Research and Risk Assessment, 2024, 38 : 2065 - 2079
  • [24] Constraining Climate Model Projections of Regional Precipitation Change
    Zhang, Bosong
    Soden, Brian J.
    GEOPHYSICAL RESEARCH LETTERS, 2019, 46 (17-18) : 10522 - 10531
  • [25] Climate change projections for Greek viticulture as simulated by a regional climate model
    Georgia Lazoglou
    Christina Anagnostopoulou
    Stefanos Koundouras
    Theoretical and Applied Climatology, 2018, 133 : 551 - 567
  • [26] Climate change projections for Greek viticulture as simulated by a regional climate model
    Lazoglou, Georgia
    Anagnostopoulou, Christina
    Koundouras, Stefanos
    THEORETICAL AND APPLIED CLIMATOLOGY, 2018, 133 (1-2) : 551 - 567
  • [27] A Comparison of Climate Signal Trend Detection Uncertainty Analysis Methods
    Phojanamongkolkij, Nipa
    Kato, Seiji
    Wielicki, Bruce A.
    Taylor, Patrick C.
    Mlynczak, Martin G.
    JOURNAL OF CLIMATE, 2014, 27 (09) : 3363 - 3376
  • [28] Uncertainty quantification for regional climate model experiments
    Sain, Stephan R.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2011, 242
  • [29] Atmospheric regional climate projections for the Baltic Sea region until 2100
    Christensen, Ole Bossing
    Kjellstrom, Erik
    Dieterich, Christian
    Groeger, Matthias
    Meier, Hans Eberhard Markus
    EARTH SYSTEM DYNAMICS, 2022, 13 (01) : 133 - 157
  • [30] Certain Uncertainty: The Role of Internal Climate Variability in Projections of Regional Climate Change and Risk Management
    Deser, Clara
    EARTHS FUTURE, 2020, 8 (12)