Sensitivity of climate change signals deduced from multi-model Monte Carlo experiments
Sensitivity of climate change signals deduced from multi-model Monte Carlo experiments
复制标题
多模型蒙特卡罗实验推导出的气候变化信号的敏感性
DOI：
--
复制
发表时间：
2002
期刊：
影响因子：
--
通讯作者：
A. Hense
中科院分区：
文献类型：
--
作者：
H. Paeth;A. Hense
近地表气温和降水经常被认为是人为气候变化的指标，在这项研究中，他们相互比较的模拟信噪比。特别强调的是温度和降雨信号的特征时间尺度。通过方差分析，基于4个温室气体（GHG）诱导的长期耦合气候模式试验，定量分析了内部噪声和外部GHG强迫对总变率的贡献。外部解释的方差部分是衡量气象变量可预测性的一个有价值的尺度。此外，不同的气候模式的敏感性进行了评估，基于多模式集成。在温度方面，温室气体强迫在热带地区占总方差的90%以上，在热带以外地区占50 - 70%，表明地球仪有变暖的趋势。另一方面，降水在很大程度上是由内部变率引起的。温室气体情景最多占降雨量方差的30%。相应的趋势模式更加分化，预测亚热带地区的干燥条件和其他地方的降水量增加。温度信号，从1970年起，是明显的30年或更长的时间尺度。对于降水，有一个弱的，但统计上显着的低频信号在区域尺度上，这是明显的60年的时间片，但不是在较短的时间尺度。目前，与温度相比，降水量是一个不利的温室气体引起的气候变化的检测变量。超集合的方法表明，模式间的变化贡献的主要部分，在高纬度地区的总变率，而温室气体对温度的影响在热带地区仍然很明显。在海冰边缘、山脉和南极洲上空，模型的不确定性很大。
Near-surface air temperature and precipitation are frequently presumed to be indicators of anthropogenic climate change; in this study, they are compared with each other in terms of their simulated signal-to-noise ratio. Special emphasis is given to the characteristic time scales of temperature and rainfall signals. By means of analysis of variance, based on an ensemble of 4 greenhousegas (GHG) induced, long-term, coupled climate model experiments, the contributions of internal noise and external GHG forcing to total variability are quantified. The part of the variance accounted for externally is a valuable measure for the predictability of a meteorological variable. Further, the sensitivity to different climate models is evaluated, based on multi-model ensembles. With regard to temperature, the GHG forcing accounts for more than 90% of the total variance in the tropics and 50 to 70% in the extra-tropics, implicating a warming trend all over the globe. On the other hand, precipitation is largely induced by internal variability. The GHG scenario accounts for at best 30% of the variance in rainfall. The corresponding trend pattern is more differentiated, predicting dryer conditions in the subtropical regions and rising precipitation elsewhere. The temperature signal, arising from 1970 onward, is evident on time scales of 30 yr and longer. For precipitation, there is a weak but statistically significant low-frequency signal on a regional scale, which is apparent for 60 yr time slices but not at shorter time scales. At present, precipitation, in contrast to temperature, represents an unfavourable detection variable for GHG-induced climate change. The super-ensemble approach reveals that intermodel variations contribute the major part to total variability in high latitudes, whereas the GHG impact on temperature is still evident in the tropics. Large model uncertainties occur in the regions of sea ice margins, mountains and over Antarctica.