Using satellite data to understand the influence of marine biogenic activity on high latitude clouds and climate
Using satellite data to understand the influence of marine biogenic activity on high latitude clouds and climate
批准号:
2442794
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
该项目旨在利用卫星数据提高我们对生物成因海洋活动如何影响偏远高纬度地区的云和气候的理解。作为形成云滴和冰的种子的气溶胶粒子的影响是我们对未来气候变化预测的最大不确定性。对于被用作确定人为气溶胶影响的基线的前工业化时期来说,情况尤其如此。在前工业化时期,自然气溶胶来源占主导地位,因此非常需要了解它们,以便做出准确的气候预测。有很好的证据表明,海洋中的浮游植物强烈影响偏远地区的气溶胶和云滴数浓度(CDNC),这反过来又影响太阳云反射回太空的能量的多少。然而,所涉进程的许多细节需要澄清。最近的卫星研究表明,最新的地球系统气候模型(用于即将进行的CMIP6气候评估)严重低估了高纬度的CDNC,指出了可能与海冰的存在和/或融化有关的外来生物气溶胶来源。我们对决定高纬度云中冰形成的因素的了解甚至更加不确定,但对云的反射率和气候模型预测也有重要的影响。我们缺乏知识的部分原因是无法到达南极洲、南大洋和北极等偏远地区。因此,卫星仪器是研究这些地区的理想方法。该项目的目标如下:-1)利用野外活动数据验证对CDNC和云冰川的最新反演:目前利用太阳反射光的CDNC和冰浓度反演存在不确定性,需要确定卫星观测到的南极洲周围的CDNC值高是否是由于反演偏差所致。2)利用卫星数据确定导致南极洲和其他高纬度地区CDNC值高的因素,并确定高纬度云冰化的程度和潜在原因:卫星反演CDNC、冰浓度、云相(液体或冰)和其他云特性,此外,还将使用海冰覆盖率和浮游植物活动标记的反演。3)利用卫星数据测试和改进最新气象局地球系统气候模式(UKESM1)中的高纬度气溶胶、CDNC、冰过程和云的表现:模式评估将涉及对UKESM1模式的数百万个变种的分析,这些模式对不确定的参数组合进行抽样。其目的是利用卫星数据来确定可信的模型变体,并减少生物气溶胶形成机制中的不确定性。这将需要使用超级计算设施和处理“大数据”的技术。英国南极调查局是这项工作的一个项目合作伙伴,将在收集和分析高纬度数据方面带来丰富的经验,并将提供使用过去和即将进行的实地活动的数据的机会,并可能有机会参加即将到来的南极活动。MET Office合作伙伴将提供最新的尖端UKESM1地球系统模型和超级计算设施,并有机会帮助开发下一代气候模型。
英文摘要
This project aims to use satellite data to advance our understanding of how biogenic marine activity affects clouds and climate in remote high latitude regions.The influence of aerosol particles that act as seeds to form cloud droplets and ice represents the largest uncertainty in our predictions of future climate change. This is particularly true for the pre-industrial period that is used as a baseline for determining the influence of anthropogenic aerosol. In the pre-industrial period natural aerosol sources dominated and so there is a great need to understand them in order to make accurate climate predictions.There is good evidence that phytoplankton in the oceans strongly influence aerosols and cloud drop number concentrations (CDNC) in remote regions, which in turn affects how much of the Sun's energy clouds reflect back to space. However, many of the details of the processes involved need to be clarified. Recent satellite studies suggest that the latest Earth System climate models (as used for the upcoming CMIP6 climate assessment) severely underestimate CDNC at high latitudes pointing towards exotic sources of biogenic aerosol potentially related to the presence and/or the melt of sea-ice. Our knowledge of what determines ice formation in high-latitude clouds is even more uncertain, but yet also has important implications for cloud reflectivity and climate model predictions. Our lack of knowledge partly stems from the inaccessibility of remote locations such as Antarctica, the Southern Ocean and the Arctic. Satellite instruments thus represent an ideal way to study these regions. The aims of the project are as follows :-1) Validate the latest retrievals of CDNC and cloud glaciation using field campaign data: There is uncertainty in current CDNC and ice concentration retrievals that use reflected light from the Sun and a need to determine whether the high CDNC values around Antarctica observed by satellite are due to retrieval biases.2) Use satellite data to determine the factors that lead to high CDNC values near Antarctica and other high latitude regions, and to determine the degree and potentially the causes of glaciation of high latitude clouds: Satellite retrievals of CDNC, ice concentrations, cloud phase (liquid or ice) and other cloud properties, as well as retrievals of sea-ice coverage and markers of phytoplankton activity, will be used. This will require the analysis of vast amounts of data with the opportunity to use machine learning techniques to determine correlations between CDNC/cloud glaciation and potential causative factors.3) Use the satellite data to test and improve the representation of high latitude aerosols, CDNC, ice processes and clouds in the latest Met Office Earth system climate model (the UKESM1) : The model evaluation will involve the analysis of millions of variants of the UKESM1 model that sample uncertain parameter combinations. The aim is to use the satellite data to identify plausible model variants and reduce uncertainty in biogenic aerosol formation mechanisms. This will require the use of supercomputing facilities and processing techniques for "big data".The British Antarctic Survey is one project partner for this work and will bring great experience in collecting and analysing high latitude data, and will provide the opportunity to work with data from past and upcoming field campaigns, and potentially the chance to take part in an upcoming Antarctic campaign. Met Office partners will provide access to the latest cutting edge UKESM1 earth system model and supercomputing facilities with the opportunity to help develop the next generation of climate models.
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