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Improved methods for estimating equilibrium climate sensitivity from transient warming simulations

机译:从瞬态变暖模拟估算均衡气候敏感性的改进方法

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Equilibrium climate sensitivity (ECS) refers to the total global warming caused by an instantaneous doubling of atmospheric CO2 from the pre-industrial level in a climate system. ECS is commonly used to measure how sensitive a climate system is to CO2 forcing; but it is difficult to estimate for the real world and for fully coupled climate models because of the long response time in such a system. Earlier studies used a slab ocean coupled to an atmospheric general circulation model to estimate ECS, but such a setup is not the same as the fully coupled system. More recent studies used a linear fit between changes in global-mean surface air temperature (Delta T) and top-of-atmosphere net radiation (Delta N) to estimate ECS from relatively short simulations. Here we analyze 1000 years of simulation with abrupt quadrupling (4 x CO2) and another 500-year simulation with doubling (2 x CO2) of pre-industrial CO2 using the CESM1 model, and three other multi-millennium (5000 year) abrupt 4 x CO2 simulations to show that the linear-fit method considerably underestimates ECS due to the flattening of the -dN/dT slope, as noticed previously. We develop and evaluate three other methods, and propose a new method that makes use of the realized warming near the end of the simulations and applies the -dN/dT slope calculated from a best fit of the Delta T and Delta N data series to a simple two-layer model to estimate the unrealized warming. Using synthetic data and the long model simulations, we show that the new method consistently outperforms the linear-fit method with small biases in the estimated ECS using 4 x CO2 simulations with at least 180 years of simulation. The new method was applied to 4 x CO2 experiments from 20 CMIP5 and 19 CMIP6 models, and the resulting ECS estimates are about 10% higher on average and up to 25% higher for models with medium-high ECS ( 3 K) than those reported in the IPCC AR5. Our new estimates suggest an ECS range of about 1.78-5.45 K with a mean of 3.61 K among the CMIP5 models and about 1.85-6.25 K with a mean of 3.60 K for the CMIP6 models. Furthermore, stable ECS estimates require at least 240 (180) years of simulation for using 2 x CO2 (4 x CO2) experiments, and using shorter simulations may underestimate the ECS substantially. Our results also suggest that it is the forced -dN/dT slope after year 40, not the internally-generated -dN/dT slope, that is crucial for an accurate estimate of the ECS, and this forced slope may be fairly stable.
机译:平衡气候敏感度(ECS)是指由气候系统中预工业水平的大气二氧化碳瞬时加倍引起的全球变暖。 ECS通常用于衡量气候系统对CO2强制敏感的敏感;但由于这种系统中的长响应时间,难以估计现实世界和完全耦合的气候模型。早期的研究使用平板海洋耦合到大气通用循环模型来估计ECS,但这种设置与完全耦合的系统不同。更新的研究使用了线性拟合在全球平均表面空气温度(Delta T)的变化和大气层净辐射(Delta N)之间的变化之间估计ECS的估计来自相对短的仿真。在这里,我们分析了1000多年的模拟,突然四倍化(4×CO2)和使用CESM1模型的预工业二氧化碳的双倍(2 x CO2)和另外500年模拟,以及三个其他多千年(5000年)突然4 X CO2模拟,表明线性拟合方法由于-DN / DT斜率的平坦而显着低估了ECS,如前所述。我们开发和评估其他三种方法,并提出了一种新的方法,利用仿真结束时实现的变暖,并将-dn / dt斜率应用于Δt和delta n数据系列的最佳拟合。简单的双层模型来估计未实现的变暖。使用合成数据和长型模拟,我们表明新方法始终如一地优于使用4×CO2模拟在估计的EC中具有小偏差的线性拟合方法,其中使用4 x CO2模拟,至少具有180年的模拟。将新方法应用于来自20cmip5和19个CMIP6型号的4×CO2实验,并且由于中高EC(> 3 k)的模型,所得到的ECS估计平均较高率高约10%,高达25%,而不是那些在IPCC AR5中报告。我们的新估计表明,CMIP5型号中的平均值为3.61 k的ECS范围为3.61 k,为CMIP6型号为3.60 k的平均值为1.85-6.25 k。此外,稳定的ECS估计需要使用2×CO2(4×CO2)实验的至少240(180)多年的模拟,并且使用较短的模拟可能基本上低估ECS。我们的结果还表明,在40年之后的强制-DN / DT斜率,而不是内部生成的-DN / DT斜率,这对于精确估计ECS至关重要,并且这种强制斜率可能相当稳定。

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