Arctic evapotranspiration: A diagnostic synthesis and model assessment

北极蒸散量：诊断综合和模型评估

• 批准号: 1830131
• 负责人: John Walsh
• 金额: $ 19.13万
• 依托单位: University of Alaska Fairbanks Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-15 至 2022-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1830131&HistoricalAwards=false
• 关键词: Arctic; evapotranspiration; diagnostic; synthesis; model

In this study, the investigators will use available data and modeling tools to understand a key component of the water cycle in a changing Arctic terrestrial environment. Changes in the wetness of Arctic land surfaces can have consequences for vegetative stress, susceptibility to wildfires, and terrestrial release of greenhouse gases such as carbon dioxide and methane. Land surface wetness may also affect wildlife, as well as human activities such as subsistence hunting and fishing, overland travel, access to resources, and water availability. Global climate models are unanimous in projecting increases in Arctic precipitation and nearly so in projecting increases of runoff. Projections of net moisture flux, or the difference between precipitation and evapotranspiration, vary widely among models, especially during the warm season. Observational data point to recent decreases in soil moisture for at least some parts of the Arctic, consistent with increasing evapotranspiration in a warming climate, but increases in surface water in other areas. This study will synthesize different types of existing data to optimize model projections of anticipated changes to Arctic surface wetness. In addition to improved understanding of how a key Arctic process is represented in global models, the broader impacts of this project include training for a graduate student and dissemination of results to policy and stakeholder communities through the Scenarios Network for Alaska and Arctic Planning and Alaska Center for Climate Assessment and Policy programs. The investigators will synthesize three types of existing data on Arctic evapotranspiration (ET): in situ measurements from observing sites, remote-sensing-derived estimates of ET, and global climate model output. They will use these diverse data sources to: 1) clarify the drivers of ET variations over time in different vegetative types and 2) evaluate climate model simulations of terrestrial ET and its variability in the Arctic. The field sites will include various tundra and boreal vegetation types, both with and without permafrost, and observations will include incident radiation, humidity, and wind speed to assess the drivers of ET in the data and in climate models. Global climate model output will come primarily from the Coupled Model Intercomparison Project. Satellite remote-sensing-derived estimates will come from MODIS archives and will bridge the scale discrepancy between models and in situ measurements. Validation of model output against in situ and remote-sensing derived estimates will focus on variation in ET over timescales of days to years. Synthesis of the three types of information will assess key processes that climate models must capture to produce credible projections of Arctic terrestrial hydrology. Based on their ability to capture seasonal cycles and ET over various vegetation types, the investigators will identify the most realistic global models, along with their formulational and structural characteristics. Results will help set priorities for model improvement and model selection to enable more robust conclusions about the trajectory of Arctic terrestrial surface wetness.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在这项研究中，研究人员将利用现有的数据和建模工具来了解北极陆地环境变化中水循环的关键组成部分。北极陆地表面湿度的变化可能对植物压力、野火易感性以及二氧化碳和甲烷等温室气体的陆地释放产生影响。陆地表面湿度也可能影响野生动物，以及人类活动，如狩猎和捕鱼，陆上旅行，获得资源和水的可用性。全球气候模型在预测北极降水量增加方面是一致的，在预测径流量增加方面也是如此。预测的净水分通量，或降水和蒸散量之间的差异，有很大的不同模式，特别是在温暖的季节。观测数据表明，至少在北极某些地区，土壤湿度最近有所下降，这与气候变暖导致的蒸散量增加相一致，但在其他地区，地表水有所增加。这项研究将综合不同类型的现有数据，以优化北极地表湿度预期变化的模型预测。除了更好地了解关键的北极过程如何在全球模型中表现之外，该项目更广泛的影响还包括培训研究生，并通过阿拉斯加和北极规划情景网络以及阿拉斯加中心将结果传播给政策和利益相关者社区。气候评估和政策计划。 研究人员将综合三种类型的现有北极蒸散量（ET）数据：观测点的原位测量，ET的遥感估计和全球气候模型输出。他们将使用这些不同的数据源：1）澄清不同植被类型中ET随时间变化的驱动因素，2）评估北极陆地ET及其变化的气候模型模拟。现场将包括各种苔原和北方植被类型，包括有和没有永久冻土，观测将包括入射辐射，湿度和风速，以评估数据和气候模型中ET的驱动因素。全球气候模式输出将主要来自耦合模式相互比较项目。卫星遥感得出的估计数将来自中分辨率成像分光仪档案，并将弥补模型与现场测量之间的比例差异。验证模型输出对在现场和遥感派生的估计将集中在ET的变化在几天到几年的时间尺度。综合这三种信息将评估气候模型必须捕捉的关键过程，以便对北极陆地水文进行可靠的预测。 根据他们捕捉季节循环和各种植被类型的ET的能力，调查人员将确定最现实的全球模型，沿着他们的公式和结构特征。研究结果将有助于为模型改进和模型选择设定优先级，从而对北极陆地表面湿度的轨迹得出更可靠的结论。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

Future Changes of Snow in Alaska and the Arctic under Stabilized Global Warming Scenarios

• DOI: 10.3390/atmos13040541
• 发表时间: 2022-04-01
• 期刊: ATMOSPHERE
• 影响因子: 2.9
• 作者: Bigalke, Siiri;Walsh, John E.
• 通讯作者: Walsh, John E.

Extreme weather and climate events in northern areas: A review

• DOI: 10.1016/j.earscirev.2020.103324
• 发表时间: 2020-08
• 期刊: Earth-Science Reviews
• 影响因子: 12.1
• 作者: J. Walsh;T. Ballinger;E. Euskirchen;Edward Hanna;J. Mård;J. Overland;H. Tangen;T. Vihma;T. Vihma

Increasing contribution of peatlands to boreal evapotranspiration in a warming climate

• DOI: 10.1038/s41558-020-0763-7
• 发表时间: 2020-05-11
• 期刊: NATURE CLIMATE CHANGE
• 影响因子: 30.7
• 作者: Helbig, Manuel;Waddington, James Michael;Zyrianov, Vyacheslav
• 通讯作者: Zyrianov, Vyacheslav

Diagnosis of Atmospheric Drivers of High-Latitude Evapotranspiration Using Structural Equation Modeling

• DOI: 10.3390/atmos12101359
• 发表时间: 2021-10
• 期刊: Atmosphere
• 影响因子: 2.9
• 作者: Sarah M. Thunberg;E. Euskirchen;J. Walsh;Kyle M Redilla

Emerging Anthropogenic Influences on the Southcentral Alaska Temperature and Precipitation Extremes and Related Fires in 2019

2019 年新出现的人为因素对阿拉斯加中南部极端温度和降水以及相关火灾的影响

• DOI: 10.3390/land10010082
• 发表时间: 2021
• 期刊: Land
• 影响因子: 3.9
• 作者: Bhatt, Uma S.;Lader, Rick T.;Walsh, John E.;Bieniek, Peter A.;Thoman, Richard;Berman, Matthew;Borries-Strigle, Cecilia;Bulock, Kristi;Chriest, Jonathan;Hahn, Micah
• 通讯作者: Hahn, Micah