Microwave Satellite Remote Sensing of High -Latitude Atmospheric Water Vapour and Surface Properties

高纬度大气水汽及地表性质微波卫星遥感

• 批准号: RGPIN-2020-05580
• 负责人: Duck, Thomas
• 金额: $ 2.19万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717302
• 关键词: Microwave; Satellite; Remote; Sensing; Latitude

Climate change is proceeding two to three times faster in the Arctic than elsewhere, leading to a 13% per decade reduction in September Arctic sea ice extent. The changes are driven by anthropogenic carbon dioxide emissions, and are subject to feedback effects, especially from water vapour. Our understanding of water vapour at high latitudes is limited by accessibility difficulties on the ground and interference by clouds with most forms of satellite measurement. Microwave satellite measurements have strong potential for filling data gaps, and for helping to improve predictive capabilities. Twenty-eight years of passive microwave (183 GHz) measurements from a series of polar-orbiting instruments represents a significant, freely available, and under-utilized resource for remote sensing of the Arctic atmosphere and surface. An impediment to their use is the lack of well-developed algorithms needed to retrieve properties of geophysical interest including water vapour column, surface emissivity, and surface emitting layer temperature. Retrieved water vapour columns are systematically moister than modeled historical reanalyses, which decreases the utility of the measurements for geophysical research. I propose an ambitious plan to increase the quality of information obtained from microwave satellite measurements by developing innovative retrieval techniques, analyzing sources of error, and validating retrieved properties against other data sources. Should the observed water vapour bias hold up to further scrutiny, models of the Arctic environment would need to change, with consequences for climate and weather prediction. Full use of available satellite resources will require new theoretical approaches. We will use optimal estimation and machine learning, with an emphasis on artificial neural networks (ANNs), to create new retrievals. New software will be written to process satellite measurements and produce high-quality geophysical data products. The impact of errors induced by surface assumptions, clouds, and choice of radiative transfer model will be explored. Advanced error statistics will be obtained in conjunction with the assimilation system operated by Environment and Climate Change Canada (ECCC). The calculations will represent an important step toward the assimilation of surface-sensitive microwave radiances over land and sea ice that will help improve predictive capabilities. Measurement validation will include a wide range of surface station and aircraft data. Benefits to the research community will include advancements in microwave retrieval capabilities and publicly available validated online data sets for geophysical research. Contributions toward improved forecasts will benefit quality of life through better short-term (i.e., weather) and long-term (i.e., climate) predictions. Trainees and scientists ready for careers in Canada's environmental monitoring and space sciences communities will be developed.

北极地区的气候变化速度是其他地区的两到三倍，导致9月份北极海冰面积每十年减少13%。这些变化是由人为二氧化碳排放推动的，并受到反馈效应的影响，特别是来自水蒸气的反馈效应。我们对高纬度地区水蒸气的了解受到地面访问困难以及云层对大多数卫星测量形式的干扰的限制。微波卫星测量在填补数据空白和帮助提高预测能力方面具有很强的潜力。 一系列极地轨道仪器对被动微波(183 GHz)进行了28年的测量，这是对北极大气和地表进行遥感的重要、免费和未得到充分利用的资源。它们使用的一个障碍是缺乏所需的完善的算法来提取地球物理意义的属性，包括水蒸气柱、表面发射率和表面发射层温度。提取的水汽柱系统地比模拟的历史再分析更潮湿，这降低了测量在地球物理研究中的效用。 我提出了一项雄心勃勃的计划，通过开发创新的检索技术，分析误差来源，并对照其他数据源验证检索的属性，来提高从微波卫星测量获得的信息的质量。如果观测到的水蒸气偏差经得起进一步的审查，北极环境的模型将需要改变，从而对气候和天气预测产生影响。 充分利用现有卫星资源将需要新的理论方法。我们将使用最优估计和机器学习，重点是人工神经网络(ANN)，以创建新的检索。将编写新的软件来处理卫星测量并产生高质量的地球物理数据产品。 我们将探讨地面假设、云层和辐射传输模式的选择所引起的误差的影响。先进的误差统计数据将与加拿大环境和气候变化中心(环境和气候变化中心)运行的同化系统一起获得。这些计算将代表着朝着同化陆地和海冰上对表面敏感的微波辐射迈出的重要一步，这将有助于提高预测能力。测量验证将包括广泛的地面站和飞机数据。 对研究界的好处将包括微波检索能力的进步和用于地球物理研究的可公开获得的经验证的在线数据集。通过更好的短期(即天气)和长期(即气候)预测，对改进预测的贡献将有利于生活质量。将培养准备在加拿大环境监测界和空间科学界从事职业生涯的受训人员和科学家。