Investigating the impact of IR surface emissivity knowledge & uncertainties on climate & weather-forecasting timescales

研究红外表面发射率知识的影响

基本信息

批准号：
2119013
负责人：
金额：
--
依托单位：
Imperial College London
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2018
资助国家：
英国
起止时间：
2018 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2119013
关键词：
Investigating impact IR surface emissivity

项目摘要

The magnitude and pace of human-induced climate change is projected to be at its largest in high-latitude (polar) regions. The radiative interaction between the surface & atmosphere is key to understanding climate change, enhanced in Polar Regions by the interplay between the cryosphere & open ocean under an exceptionally transparent atmosphere in the mid- to far-IR. Surface reflection/emissivity has been studied extensively throughout the visible and NIR for many surface types across the globe. However, recent climate model simulations have highlighted that a hitherto unrecognised feedback process may significantly accelerate the rate of warming in arctic areas through IR interactions. Termed the 'ice-emissivity' feedback, the process is postulated to rely on differential surface emission of far infrared (FIR) radiation (wavelengths between ~ 15 and 100 microns) from snow covered and ocean surfaces (Feldman et al., 2014). In the FIR, theoretical estimates of surface emissivity suggest that the ocean is less emissive than overlying ice and snow layers, hence as snow/ice melts additional heat can be trapped within the upper ocean, accelerating ice melt and leading to further near surface and surface warming. Existing studies evidence a need for improvements in current estimates of the surface emissivity across the full infrared spectrum. These studies also indicate that snow and ice surfaces do indeed have an emissivity spectrum that is significantly different from that of a perfect, blackbody emitter (an assumption made in most current weather and climate prediction models). Very recent work within Imperial College's Space and Atmospheric Physics group has delivered the first ever in-situ estimates of FIR surface emissivity from airborne observations (Bellisario et al., 2017). We are also currently developing the capability to make measurements of surface emissivity extending across the infrared via a purpose designed portable ground-based system. Current modelling efforts have focused on the long-term response of the polar regions to infrared surface emissivity, but its unstudied impact on shorter 'weather' time-scales and the large source of uncertainty it adds to monthly-scale predictions should not be estimated. In this project you will thus: (1) Further exploit arctic flight campaign data to assess the robustness of our initial results and perform additional evaluation of theoretical snow/ice surface emissivity estimates.(2) Utilise our new ground-based interferometer system to obtain in-situ estimates of infrared emissivity spanning the mid- and far infrared for a range of different surfaces and conditions, focusing initially on snow/ice covered high latitudes.(3) Work with the co-supervisor institutions to assess the impact of new robust IR surface reflectance/emissivity measurements on EO cal/val, climate studies & numerical weather prediction application areas.

人类引起的气候变化的幅度和速度预计在高纬度（极）区域最大。表面和大气之间的辐射相互作用是理解气候变化的关键，在冰冻圈和开阔海洋之间的相互作用在极地到Far-IR的异常透明大气下增强了极地区域。在全球许多表面类型中，已经对表面反射/发射率进行了广泛的研究和NIR研究。但是，最近的气候模型模拟强调，迄今未认可的反馈过程可能会通过IR相互作用显着加速北极地区的变暖率。该过程被称为“冰出发性”反馈，据推测，该过程依赖于从覆盖的积雪和海洋表面中的远红外（FIR）辐射（〜15至100微米之间的波长）的差分表面发射（Feldman等，2014）。在FIR中，理论上的表面发射率估计表明，海洋比上覆冰和雪层的发射不那么发射，因此，随着雪/冰融化的额外热量可能会被困在上海中，加速冰融化，并在表面和表面附近进一步。变暖。现有研究证明，需要改善整个红外光谱中表面发射率的当前估计值。这些研究还表明，雪和冰面确实具有发射率的频谱，与完美的黑体发射极（在大多数当前天气和气候预测模型中做出的假设）明显不同。帝国学院的太空和大气物理小组中的最新工作已经提供了有史以来对空中观察结果的FIR表面发射率的第一次原位估计（Bellisario等，2017）。目前，我们还在开发通过专门设计的便携式地面系统进行跨红外延伸的表面发射率的测量能力。当前的建模工作集中在极性区域对红外表面发射率的长期反应上，但其对较短的“天气”时间尺度的影响不足，并且不应估计它为每月规模的预测增加的不确定性来源。在此项目中，您将：（1）进一步利用北极飞行运动数据来评估我们最初结果的鲁棒性，并对理论雪/冰面发射率估算进行额外评估。（2）利用我们的新基于地面的干涉仪系统获得在各种不同表面和条件下，红外发射率的现场估计值最初集中在雪/冰上覆盖的高纬度地区。 IR表面反射/发射率测量EO CAL/VAL，气候研究和数值天气预测应用领域。