CAREER: The Mesoscale Climate Dynamics of Rocky Mountain Snowpack Depletion

职业：落基山积雪消耗的中尺度气候动力学

• 批准号: 1349990
• 负责人: Justin Minder
• 金额: $ 57.06万
• 依托单位: SUNY at Albany
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-03-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1349990&HistoricalAwards=false
• 关键词: CAREER; Mesoscale; Climate; Dynamics; Rocky

The surface-albedo feedback (SAF) from mountain snow cover is one of the dominant influences on the regional-scale response to large-scale climate variability and change in the mid-latitudes. At global scales, detailed analyses have illuminated the controls on the SAF and sources of spread in SAF magnitude between global climate models (GCMs). While regional climate model (RCM) simulations over complex terrain suggest substantial regional effects of the SAF, no detailed quantitative analysis of the regional SAF has been undertaken. This project will quantify and diagnose the SAF in high-resolution RCM simulations over the Rocky Mountains (and later the continental United States) using the WRF model. They include 8-year reanalysis-forced control simulations and 8-year pseudo-global-warming (PGW) simulations, wherein reanalysis boundary conditions are perturbed by monthly mean changes predicted by a GCM under greenhouseforcing. This framework allows for clean diagnosis of thermodynamic and mesoscale mechanisms of climate change in isolation from changes in large-scale circulations and storminess. Analysis will include: (i) Quantification of the SAF and its contributions from various physical processes: The SAF will be separated from other forcings and feedbacks via linear feedback analysis and via RCM simulations with a suppressed SAF. The mechanisms controlling the strength of the SAF will be diagnosed including: the relative roles of snow cover and snow metamorphism changes, the atmosphere masking of surface albedo changes, and the role of atmospheric advection. (ii) Evaluation of simulated snow cover and albedo: RCM output will be evaluated against high-resolution remote sensing provided by the MODIS instrument (including the new MODSCAG snow product) to critically test the realism of the simulated SAF and identify sources of bias. (iii) Examination of the interactions between the SAF and regional-scale circulations: This will include a determination of the role of advection in balancing radiative perturbations and the role of radiative perturbations in altering thermally driven mesoscale circulations. (iv) Comparison with other mountain ranges, forcing scenarios, and model parameterizations: Analysis of additional simulations with different model configurations will be used to understand how geographic setting modulates the SAF. It will also be used to examine differences in the SAF between simulations with and without changes in large-scale circulations or dust-on-snow forcing.Educational impacts at the graduate level will include mentoring and training of a student. At the undergraduate level, a course on the environmental science of mountainous regions will be enriched with RCM output from the project and field observations. At the high school level, annual classroom visits and weeklong summer camps on weather and climate for local students will be developed. These programs will serve urban districts with high populations of minorities underrepresented in the STEM fields. The camps will engage students through lectures, demonstrations, hands-on laboratory experiences, and an interactive field trip to a local mountaintop observatory. Students will be introduced to the university environment, career options, and a range of role models. This will serve to enable, excite, and recruit students for future study and employment in the atmospheric sciences specifically and STEM in general.

山区积雪的地表反射反馈（SAF）是中纬度地区对大尺度气候变率和变化的区域尺度响应的主要影响之一。在全球尺度上，详细的分析阐明了全球气候模式（GCM）之间SAF的控制因素和SAF幅度扩散的来源。虽然区域气候模式（RCM）模拟复杂的地形表明，大量的区域影响的SAF，没有详细的定量分析的区域SAF进行。该项目将使用WRF模式在落基山脉（以及后来的美国大陆）的高分辨率RCM模拟中量化和诊断SAF。它们包括8年再分析强迫控制模拟和8年伪全球变暖（PGW）模拟，其中再分析边界条件的扰动下温室效应下的GCM预测的月平均变化。这一框架允许对气候变化的热力学和中尺度机制进行清晰的诊断，而不受大尺度环流和风暴变化的影响。分析将包括：（i）SAF的量化及其来自各种物理过程的贡献：SAF将通过线性反馈分析和通过具有抑制SAF的RCM模拟与其他强迫和反馈分离。控制SAF强度的机制将被诊断为：积雪和雪变质变化的相对作用，大气掩盖地面温度变化，以及大气平流的作用。 (ii)模拟雪盖和积雪的评价：将对照中分辨率成像分光仪提供的高分辨率遥感（包括新的中分辨率成像分光比例尺积雪产品）对区域气候模型的输出进行评价，以严格检验模拟的SAF的真实性，并查明偏差的来源。 (iii)检查SAF和区域尺度环流之间的相互作用：这将包括确定平流在平衡辐射扰动中的作用以及辐射扰动在改变热驱动的中尺度环流中的作用。 (iv)与其他山脉，强迫情景和模型参数化的比较：将使用不同模型配置的额外模拟分析来了解地理环境如何调节SAF。 它也将被用来检查SAF之间的差异，在模拟和没有变化的大规模环流或灰尘对雪forcing.Educational影响在研究生水平将包括指导和培训的学生。 在大学一级，将利用该项目的区域协调机制产出和实地观察，充实关于山区环境科学的课程。 在高中一级，将为当地学生举办关于天气和气候的年度教室访问和为期一周的夏令营。 这些计划将服务于少数民族人口在STEM领域代表性不足的城市地区。 营地将通过讲座、演示、实验室实践体验以及当地山顶天文台的互动实地考察来吸引学生。 学生将被介绍到大学环境，职业选择，和一系列的榜样。 这将有助于使，激发和招收学生未来的学习和就业在大气科学特别是干一般。