MesoS2D:Mesospheric sub-seasonal to decadal predictability

MesoS2D：中层次季节到年代际的可预测性

• 批准号: NE/V01837X/1
• 负责人: Corwin Wright
• 金额: $ 47.09万
• 依托单位: University of Bath
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV01837X%2F1
• 关键词: MesoS2D; Mesospheric; sub; seasonal; decadal

In order to accurately predict impacts of space weather and climate variability on the whole atmosphere we need an accurate representation of the whole atmosphere. The mesosphere (~50-95 km altitude) is the most poorly understood region of the atmosphere, it is the critical boundary between two domains (the climate domain and the space weather domain) and this presents a problem when trying to model and prediction conditions in the whole atmosphere. Currently the level of prediction in the mesosphere is no better than climatology. Historically there have been few observations of this region to help us characterise it. However, in the past decade or so the number of observations has increased markedly, including multiple middle atmosphere observing satellite missions. We plan to take advantage of this golden age of middle atmosphere observations and together with one of the world most sophisticated whole atmosphere models to quantify the variability and drivers of the mesosphere. The mesosphere influences, and is influenced by, in-situ and external effects such as atmospheric waves and tides (upward) and space weather effects (downward). The mesosphere is strongly coupled to the lower edge of the ionosphere, as well as the other atmospheric regions, so changes in one part can impact on others. In order to make progress in modelling the whole atmosphere as a coupled system we need to have a sound scientific understanding of the drivers of variability. For climate models we have a good level of predictability for ~2 weeks and one the ~decades scale. However, critically we cannot do this in the mesosphere yet. We aim to focus our efforts on understanding variability on the sub-seasonal to decadal variations in the mesosphere as a pathway to improving model predictions. We will use the highly instrumented region of Scandinavia, in conjunction with satellite data, to determine the variability of the mesosphere/lower ionosphere and its drivers over a sub seasonal to decadal scale. We will be among the first to use a new, ~£50 million, high-resolution instrument (EISCAT 3D). This will be the world's most sophisticated ionospheric radar which will allow unprecedented small scale measurements of variations in the middle atmosphere. In conjunction with special high-resolution whole atmosphere model simulations, we will determine the drivers and variability of this atmospheric region and provide a first step along the road of improving predictability of the mesosphere at sub-seasonal to decadal timescales.

为了准确预测空间天气和气候变化对整个大气层的影响，我们需要对整个大气层进行准确的描述。中层(约50-95公里高度)是大气中最不了解的区域，它是两个区域(气候域和空间天气域)之间的关键边界，这给整个大气的模拟和预测带来了问题。目前，中间层的预报水平并不比气候学好多少。从历史上看，很少有人观察到这一地区，以帮助我们描述它的特征。然而，在过去十年左右的时间里，观测次数显著增加，包括多个中层大气观测卫星飞行任务。我们计划利用这个中层大气观测的黄金时代，并与世界上最复杂的全大气模式之一一起，量化中间层的可变性和驱动因素。中间层影响原地和外部效应，并受其影响，例如大气波和潮汐(向上)和空间天气效应(向下)。中间层与电离层下缘以及其他大气层区域强烈耦合，因此一个部分的变化可能会影响其他部分。为了在将整个大气模拟为一个耦合系统方面取得进展，我们需要对变化的驱动因素有一个科学的理解。对于气候模型，我们有很好的~2周和~数十年尺度的可预测性。然而，关键是我们还不能在中间层做到这一点。我们的目标是将我们的努力集中在理解中间层亚季节到年代际变化上的可变性，以此作为改进模式预测的途径。我们将利用高度仪器化的斯堪的纳维亚地区，结合卫星数据，确定中间层/低电离层及其驱动因素在亚季节到十年尺度上的可变性。我们将是首批使用新的5000万GB高分辨率仪器(EISCAT 3D)的公司之一。这将是世界上最先进的电离层雷达，它将允许对中间大气中的变化进行前所未有的小范围测量。结合特别的高分辨率全大气模式模拟，我们将确定这一大气区域的驱动因素和可变性，并在改善亚季节到十年时间尺度的中间层可预报性的道路上迈出第一步。

项目成果

Stratospheric gravity waves excited by Hurricane Joaquin in 2015: 3-D characteristics and the correlation with hurricane intensification

2015 年华金飓风激发的平流层重力波：3D 特征及其与飓风强度的相关性

• DOI: 10.5194/egusphere-2023-3008
• 发表时间: 2024
• 作者: Wu X

Using sub-limb observations to measure gravity waves excited by convection.

• DOI: 10.1038/s41526-023-00259-2
• 发表时间: 2023-02-08
• 期刊: NPJ MICROGRAVITY
• 影响因子: 5.1
• 作者: Wright, Corwin J.;Ungermann, Joern;Preusse, Peter;Polichtchouk, Inna
• 通讯作者: Polichtchouk, Inna

Aeolus wind lidar observations of the 2019/2020 Quasi-Biennial Oscillation disruption with comparison to radiosondes and reanalysis

风神激光雷达对 2019/2020 年准两年期振荡中断的观测与无线电探空仪的比较和再分析

• DOI: 10.5194/egusphere-2023-285
• 发表时间: 2023
• 作者: Banyard T

Atmospheric Gravity Waves: Processes and Parameterization

大气重力波：过程和参数化

• DOI: 10.1175/jas-d-23-0210.1
• 发表时间: 2023
• 期刊: Journal of the Atmospheric Sciences
• 影响因子: 3.1
• 作者: Achatz U

A statistical study of convective and dynamic instabilities in the polar upper mesosphere above Troms?

特罗姆瑟上方极地上层中间层对流和动力不稳定性的统计研究？

• DOI: 10.1186/s40623-023-01771-1
• 发表时间: 2023
• 期刊: Earth, Planets and Space
• 作者: Nozawa Satonori;Saito Norihito;Kawahara Takuya;Wada Satoshi;Tsuda Takuo T.;Maeda Sakiho;Takahashi Toru;Fujiwara Hitoshi;Narayanan Viswanathan Lakshmi;Kawabata Tetsuya;Johnsen Magnar G.
• 通讯作者: Johnsen Magnar G.