uantifying the sensitivity of shallow cumulus cloud fields to a broad range of environmental perturbations
量化浅积云场对各种环境扰动的敏感性
基本信息
- 批准号:2284965
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:英国
- 项目类别:Studentship
- 财政年份:2019
- 资助国家:英国
- 起止时间:2019 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Despite significant progress being made over previous decades of work, climate projections are still marred by large uncertainties, particularly in the Equilibrium Climate Sensitivity (ECS), a measure of the global equilibrium temperature response to a doubling of CO2. (Schneider et al., 2017)One of the key causes for this spread in predictions - for a given emissions scenario - emanates from the response of shallow, marine clouds to climate change, termed the `shallow cloud feedback`. These clouds are of particular importance for the earth's radiation budget as they have a net cooling influence due to their low, warm cloud tops and high albedo. (Bony et al., 2004; Bony and Dufresne, 2005; Spill et al., 2019)Recent work has shown that over half the variance of ECS between CMIP5 models can be explained by changes in the shortwave reflectance of tropical low clouds. (Brient et al., 2016) Additionally, early work has demonstrated that the single greatest source of uncertainty within the shallow cloud feedback is the sensitivity of warm, boundary layer clouds to changes in their environment. (Bony and Dufresne, 2005)Hence, it is critical to understand and quantify the sensitivity of warm, shallow cloud field properties to changes in their environment, so as to better constrain their uncertain behaviour in global climate models. (Schneider et al., 2017)this project proposes to extend the analysis of previous sensitivity studies in two ways:Firstly, we will conduct a suite of high-resolution simulations of transient, warm shallow cloud fields which explicitly consider the possible range of covariation between both environmental and microphysical perturbations. (Dagan et al., 2017, 2018; Spill et al., 2019) To do this we will use Latin Hypercube sampling to select the maximally informative simulations to conduct in order to adequately sample the uncertainty space of possible combinations of external perturbations. Possible parameters to perturb could include temperature, subsidence, CDNC, free-tropospheric relative humidity or windspeed. (McKay, Beckman and Conover, 1979; Lee et al., 2011) Secondly, using the space-filling, maximally informative set of simulations conducted, we will be able to train and verify a Gaussian process (GP) emulator which can be used to estimate the cloud response across the high-dimensional parameter space. This technique of combining Latin hypercube sampling with GP emulation has already been used to great effect in the quantification of uncertainty in global aerosol-climate models, and the approach is ripe for use in cloud feedback studies. (Lee et al., 2011, 2012) Once the emulator is constructed and verified, we will be able to easily sample a wide range of environmental perturbations, allowing us to identify the most sensitive parameters in the modelled response of shallow cumuli to changes in their environment. We will also be able to comprehensively explore to what extent the cloud response to a combination of external parameters is linear or non-linear, which has not been possible in previous studies. Finally, it is expected that the emulator approach will also enable a better understanding of how CDNC changes and the "precipitation governor" mechanism act as a control on cloud feedbacks.
尽管在过去几十年的工作中取得了重大进展,但气候预测仍然受到很大的不确定性的影响,特别是在平衡气候敏感性(ECS)方面,这是一种衡量全球平衡温度对二氧化碳加倍的反应的措施。(Schneider等人,2017)对于特定的排放情景而言,预测中出现这种差异的主要原因之一是浅层海洋云对气候变化的反应,称为“浅层云反馈”。这些云对地球的辐射收支特别重要,因为它们有一个净冷却的影响,由于其低,温暖的云顶和高的辐射。(Bony例如,2004; Bony和Dufresne,2005; Spill等人,2019)最近的研究表明,CMIP 5模式之间ECS的一半以上的变化可以用热带低云短波反射率的变化来解释。(Brient等人,此外,早期的工作已经证明,浅云反馈中最大的不确定性来源是温暖的边界层云对环境变化的敏感性。(Bony和Dufresne,2005)因此,了解和量化暖浅云场特性对环境变化的敏感性至关重要,以便更好地限制它们在全球气候模式中的不确定行为。(Schneider等人,2017)本计画建议以两种方式延伸先前敏感性研究的分析:第一,我们将进行一套高解析度的瞬变暖浅云场模拟,明确考虑环境与微物理扰动之间可能的共变范围。(Dagan等人,2017,2018; Spill等人,为了做到这一点,我们将使用拉丁超立方体采样来选择最大信息量的模拟进行,以便充分采样外部扰动的可能组合的不确定性空间。可能扰动的参数包括温度、沉降、CDNC、自由对流层相对湿度或风速。(McKay,Beckman和科诺菲尔,1979年; Lee等人,其次,使用空间填充,最大信息量的模拟集,我们将能够训练和验证高斯过程(GP)仿真器,该仿真器可用于估计高维参数空间中的云响应。这种拉丁超立方体采样与GP模拟相结合的技术已经在全球气溶胶-气候模式的不确定性量化中发挥了巨大作用,这种方法已经成熟,可以用于云反馈研究。(Lee例如,2011年,2012年)一旦模拟器的构建和验证,我们将能够轻松地采样范围广泛的环境扰动,使我们能够确定最敏感的参数,在模拟响应的浅积云在其环境的变化。我们还将能够全面探索云对外部参数组合的响应在多大程度上是线性或非线性的,这在以前的研究中是不可能的。最后,预计模拟器的方法也将使人们能够更好地了解CDNC的变化和“降水总督”机制作为一个控制云的反馈。
项目成果
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其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
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LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
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吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
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Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
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