The Peculiar Trajectory of Global Warming
The Peculiar Trajectory of Global Warming
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DOI：
10.1029/2020jd033629
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发表时间：
2021-02
期刊：
影响因子：
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通讯作者：
S. Fueglistaler;Levi G. Silvers
中科院分区：
文献类型：
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作者：
S. Fueglistaler;Levi G. Silvers
一般环流模式（GCM）在给定历史时期观测到的海表温度（SST）的模拟显示，系统的全球短波云辐射效应（SWCRE）变化与全球表面温度无关（称为“模式效应”）。在这里，我们表明，在使用CMIP6推荐的PCMDI/AMIPII海温模拟中，量化热带深对流区域与热带或全球平均海温差异的单个参数（Δconv）捕获了时变的“模式效应”。特别是，Δconv在20世纪80年代至90年代的一个大的正趋势解释了自20世纪70年代末以来强烈负的SWCRE反馈的符号变化。在这几十年里，深对流区比热带平均温度高50%左右。在强迫耦合的大气-海洋GCM模拟中很少观察到这种放大，其中放大的变暖通常约为+10%。在2000年之后的全球变暖中断期间Δconv变化不大，最近恢复的全球变暖时期太短，无法强有力地检测趋势。在规定的海温模拟中，Δconv是由温暖和寒冷地区的海温差异所强迫的。对6个重建的SST指数（SST#）进行了评估，结果显示卫星时代的趋势相似，但PCMDI/AMIPII重建的SST与卫星时代之前的差异要大得多。云反馈的量化主要取决于海温概率密度分布形状的微小变化。这些敏感性强调了高度准确、持久和稳定的全球气候记录对于确定云反馈是多么重要。
General Circulation Model (GCM) simulations with prescribed observed sea surface temperature (SST) over the historical period show systematic global shortwave cloud radiative effect (SWCRE) variations uncorrelated with global surface temperature (known as “pattern effect”). Here, we show that a single parameter that quantifies the difference in SSTs between regions of tropical deep convection and the tropical or global average (Δconv) captures the time‐varying “pattern effect” in the simulations using the PCMDI/AMIPII SST recommended for CMIP6. In particular, a large positive trend in the 1980s–1990s in Δconv explains the change of sign to a strongly negative SWCRE feedback since the late 1970s. In these decades, the regions of deep convection warm about +50% more than the tropical average. Such an amplification is rarely observed in forced coupled atmosphere‐ocean GCM simulations, where the amplified warming is typically about +10%. During the post 2000 global warming hiatus Δconv shows little change, and the more recent period of resumed global warming is too short to robustly detect trends. In the prescribed SST simulations, Δconv is forced by the SST difference between warmer and colder regions. An index thereof (SST#) evaluated for six SST reconstructions shows similar trends for the satellite era, but the difference between the pre‐ and the satellite era is substantially larger in the PCMDI/AMIPII SSTs than in the other reconstructions. Quantification of the cloud feedback depends critically on small changes in the shape of the SST probability density distribution. These sensitivities underscore how essential highly accurate, persistent, and stable global climate records are to determine the cloud feedback.