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Understanding Measurements of Climate Sensitivity

了解气候敏感性的测量

基本信息

批准号：
1661861
负责人：
Andrew Dessler
金额：
$ 42.77万
依托单位：
Texas A&M University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-04-01 至 2021-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1661861&HistoricalAwards=false
关键词：
Understanding Measurements Climate Sensitivity

项目摘要

The mean temperature of the earth is determined by the balance of incoming and outgoing radiant energy at the top of the atmosphere, and the outgoing energy generally increases and decreases with mean temperature. The temperature dependence of outgoing energy stabilizes earth's climate, as an increase in temperature produces an increase in outgoing energy which cools the planet, and a decrease in temperature has the opposite effect. The restoring effect of temperature on outgoing energy can be quantified by a climate feedback parameter which summarizes the net effect of a variety of mechanisms which together determine the global effect. For internally generated climate variability such as El Nino, which produces a temporary increase in global temperature, the feedback parameter determines how quickly the temperature will return to its long-term climatological value. For externally forced climate change, such as the warming produced by an increase in carbon dioxide (CO2), the feedback parameter determines the amount of warming that will ultimately occur as a result of the radiative effect of the CO2 increase.It is commonly assumed that the same feedback parameter applies very generally to global temperature changes produced by internal climate variability (like the temperature increase during El Nino events) and permanent climate change forced by increases in carbon dioxide (CO2) and other external factors. But preliminary work by the PI and others suggests a systematic difference between parameter values calculated from internal variability and forced change simulations in climate models, possibly due to differences in the spatial patterns of temperature anomalies associated with internal variability and forced change, and the fact that different feedback mechanisms are prominent in different regions. A difference in feedback strength between forced response and internal variability would complicate efforts to estimate the feedback parameter from observations, as the necessary observations include satellite measurements of the incoming and outgoing top-of-atmosphere radiative fluxes that are only available for a 15-year period. Changes in radiative fluxes over such a short period are dominated by internal variability, thus the feedback parameter value derived from them would only be representative of internal variability and should not be used to assess the sensitivity of climate to CO2 increases. A further issue identified by the PI is that the feedback parameter may have strong decade-to-decade variability, at least in long model simulations of climate under present-day conditions. Such variability, likely also related to the spatial patterns of temperature anomalies and their consequences for specific feedback mechanisms (for instance the albedo feedback associated with ice and snow which generally occur at higher latitudes), would also have to be taken into account when attempting to estimate climate sensitivity from observations.This project considers possible differences in feedback parameter between internal variability and forced change, as well as the possibility of decadal variability in the feedback parameter, using a combination of observations and model simulations. Much of the work focuses on an alternative feedback parameter based on the mean temperature at a mid-tropospheric level (500mb), as parameter values calculated at this level show greater agreement between observations and simulations than their counterparts based on surface temperature. This agreement motivates further examination of the processes contributing to differences in feedback parameter in model simulations, which have the advantage of very long periods of record and outputs which include detailed breakdowns of hard-to-observe quantities such as the longwave and shortwave radiative effects of clouds.The work has broader impacts due to the desirability of constraints on how much warming can result from increases in atmospheric CO2 and other greenhouse gases, particularly given the large uncertainty in estimates from model simulations. The project also supports two graduate students, thereby providing for the future workforce in this research area.

地球的平均温度由大气顶部传入和传出的辐射能的平衡决定，传出的能量通常随平均温度而增加和减少。输出能量对温度的依赖性稳定了地球的气候，因为温度升高会导致输出能量增加，从而使地球冷却，而温度下降则产生相反的效果。温度对输出能量的恢复作用可以通过气候反馈参数来量化，该参数总结了多种机制的净效应，这些机制共同决定了全球效应。对于内部产生的气候变化，例如厄尔尼诺现象，会导致全球温度暂时升高，反馈参数决定温度恢复到其长期气候值的速度。对于外部强迫的气候变化，例如二氧化碳 (CO2) 增加引起的变暖，反馈参数决定了由于二氧化碳增加的辐射效应而最终发生的变暖量。通常认为，相同的反馈参数非常普遍地适用于内部气候变率引起的全球温度变化（如厄尔尼诺事件期间的温度升高）和碳增加导致的永久性气候变化二氧化碳（CO2）和其他外部因素。但PI和其他人的初步工作表明，根据气候模型中的内部变率和强迫变化模拟计算出的参数值之间存在系统差异，这可能是由于与内部变率和强迫变化相关的温度异常的空间模式存在差异，以及不同地区存在不同的反馈机制这一事实。强迫响应和内部变异之间的反馈强度差异将使估计观测反馈参数的工作复杂化，因为必要的观测包括对传入和传出大气层顶部辐射通量的卫星测量，而这些测量仅在 15 年期间可用。如此短的时间内辐射通量的变化主要由内部变率决定，因此由此得出的反馈参数值只能代表内部变率，不应用于评估气候对二氧化碳增加的敏感性。 PI 发现的另一个问题是，反馈参数可能具有很强的十年到十年的变化，至少在当前条件下对气候的长期模型模拟中是这样。这种变化可能还与温度异常的空间模式及其对特定反馈机制的影响有关（例如，与冰和雪相关的反照率反馈通常发生在高纬度地区），在尝试根据观测估计气候敏感性时也必须考虑到这种变化。该项目考虑了内部变化和强迫变化之间反馈参数之间可能存在的差异，以及十年间变化的可能性。反馈参数，使用观察和模型模拟的组合。大部分工作都集中在基于对流层中层平均温度 (500mb) 的替代反馈参数上，因为在此级别计算的参数值显示，与基于表面温度的对应参数值相比，观测值和模拟值之间的一致性更高。该协议促使进一步研究导致模型模拟中反馈参数差异的过程，其优点是记录和输出周期很长，其中包括难以观测的量的详细分类，例如云的长波和短波辐射效应。由于需要限制大气中二氧化碳和其他温室气体的增加会导致多少变暖，特别是考虑到大范围的变暖，这项工作具有更广泛的影响。模型模拟估计的不确定性。该项目还支持两名研究生，从而为该研究领域的未来劳动力提供支持。