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The role of air-sea interactions in sub-seasonal variability

海气相互作用在次季节变化中的作用

基本信息

批准号：
NE/L010976/1
负责人：
Nicholas Klingaman
金额：
$ 60.66万
依托单位：
University of Reading
依托单位国家：
英国
项目类别：
Fellowship
财政年份：
2015
资助国家：
英国
起止时间：
2015 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FL010976%2F1
关键词：
role air sea interactions sub

项目摘要

This fellowship aims to understand the mechanisms by which air-sea interactions control the development and intensification of high-impact weather extremes, and to improve the ability of numerical models to simulate those mechanisms.Daily-monthly regional variations in weather and climate influence lives and livelihoods by affecting agriculture, hydrology and infrastructure. These sub-seasonal variations are controlled by high-impact phenomena including tropical cyclones; "blocking" high-pressure systems that cause droughts and heatwaves; and broad, organised areas of enhanced or reduced tropical thunderstorm activity that cause active and suppressed periods of monsoon rainfall.Analysis of field and satellite observations has suggested that transfers of energy and moisture between the atmosphere and the sea surface influence the location and intensity of these phenomena. These transfers result in short-lived (1-2 weeks) changes to sea-surface temperatures (SSTs), which can influence the atmosphere; tropical thunderstorms tend to favour warmer waters, for example. It is not possible to distinguish forcing from response using observations alone, however, preventing understanding of how air-sea feedbacks influence sub-seasonal phenomena. Many short- and medium-range (1-14 days) forecasts use numerical models of only the atmosphere, neglecting potentially critical air-sea interactions. Atmosphere-ocean coupled models that represent these interactions are used for seasonal-to-decadal forecasts and climate-change projections, but often struggle to simulate sub-seasonal variability. These failings limit predictions of regional weather and extremes, create uncertainty in regional climate-change projections and prevent scientists from using these models to understand air-sea feedbacks.These failings will be addressed through a novel modelling framework of an atmospheric model coupled to a simplified ocean model, which improves simulated short-lived SST variations; minimises errors in the model's mean climate that inhibit the simulation of high-impact phenomena; and allows air-sea feedbacks to be simulated in only certain regions of the globe or at certain times of year, to aid understanding of how these feedbacks influence high-impact phenomena. The framework will used with models from the Met Office, the European Centre for Medium-range Weather Forecasts and the Center for Multiscale Modelling of Atmospheric Processes (U.S.). Using models that differ considerably in their simulated high-impact phenomena permits more thorough testing of hypotheses about the impacts of air-sea interactions.This framework allows the simulated effects of air-sea interactions on high-impact phenomena to be more cleanly separated from the effect of errors in the simulation of the mean climate. Previous studies have conflated these effects, creating uncertainty about the role of air-sea interactions in sub-seasonal variability. In this framework, variations among models in how high-impact phenomena respond to air-sea interactions will be caused only by variations in the formulations of the atmospheric models. This will inspire experiments to alter these formulations and investigate how the representation of key atmospheric processes, such as the relationship between atmospheric moisture and precipitation, affects the simulation of high-impact phenomena. Re-forecasts of past high-impact phenomena will allow close comparisons of simulations and observations and permit experiments that test the effects of individual processes. Experiments in which model errors in the simulated mean climate are introduced in particular regions, or times of year, will identify those errors that most inhibit sub-seasonal variability. This fellowship will improve understanding of air-sea interactions and their role in sub-seasonal variability, predictions of weekly-monthly variations in weather and climate, and regional projections of climate change.

该奖学金旨在了解海气相互作用控制高影响极端天气发展和加剧的机制，并提高数值模式模拟这些机制的能力。天气和气候的逐月区域变化通过影响农业、水文和基础设施影响人们的生活和生计。这些分季节变化受包括热带气旋在内的高影响现象的控制；“阻断”导致干旱和热浪的高压系统；广泛而有组织的热带雷暴活动增强或减弱的区域，导致季风降雨的活跃期和抑制期。对实地和卫星观测的分析表明，大气和海面之间的能量和水分转移影响这些现象的位置和强度。这些转移导致海面温度（SSTs）的短期（1-2周）变化，这可以影响大气；例如，热带雷暴倾向于温暖的水域。然而，仅利用观测不可能区分强迫和响应，这妨碍了对海气反馈如何影响次季节现象的理解。许多中短期（1-14天）预报只使用大气的数值模式，忽略了潜在的关键海气相互作用。代表这些相互作用的大气-海洋耦合模式用于季节到十年的预报和气候变化预估，但往往难以模拟亚季节变率。这些缺陷限制了对区域天气和极端事件的预测，造成了区域气候变化预测的不确定性，并阻碍了科学家使用这些模型来理解海气反馈。这些缺陷将通过与简化的海洋模式相结合的大气模式的新模式框架来解决，该模式改善了模拟的短期海温变化；使模式平均气候中抑制高影响现象模拟的误差最小化；并允许在全球特定地区或一年中的特定时间模拟空气-海洋反馈，以帮助理解这些反馈如何影响高影响现象。该框架将与英国气象局、欧洲中期天气预报中心和美国大气过程多尺度模拟中心的模型一起使用。使用在模拟高影响现象方面差异很大的模型，可以更彻底地检验关于海气相互作用影响的假设。这一框架使模拟的海气相互作用对高影响现象的影响能够更清晰地与平均气候模拟中的误差影响区分开来。以前的研究将这些影响合并在一起，造成了海气相互作用在亚季节变化中的不确定性。在这一框架下，模式之间关于高影响现象对海气相互作用的反应的差异将仅由大气模式的公式变化引起。这将激发实验来改变这些公式，并研究关键大气过程的表示，如大气湿度和降水之间的关系，如何影响高影响现象的模拟。对过去高影响现象的重新预报将使模拟和观测结果进行密切比较，并允许进行试验，以测试个别过程的影响。将模拟平均气候的模式误差引入特定地区或一年中的特定时间的实验，将确定那些最能抑制亚季节变率的误差。这一奖学金将增进对海气相互作用及其在次季节变化、天气和气候周-月变化预测以及气候变化区域预测中的作用的了解。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Contribution of Tropical Cyclones to Atmospheric Moisture Transport and Rainfall over East Asia

DOI：
10.1175/jcli-d-16-0308.1
发表时间：
2017-05
期刊：
Journal of Climate
影响因子：
4.9
作者：
Liang Guo;N. Klingaman;P. Vidale;A. Turner;M. Demory;A. Cobb
通讯作者：
Liang Guo;N. Klingaman;P. Vidale;A. Turner;M. Demory;A. Cobb

Projected Changes in the East Asian Hydrological Cycle for Different Levels of Future Global Warming

DOI：
10.3390/atmos13030405
发表时间：
2022-03
期刊：
Atmosphere
影响因子：
2.9
作者：
A. Chevuturi;N. Klingaman;A. Turner;Liang Guo;P. Vidale
通讯作者：
A. Chevuturi;N. Klingaman;A. Turner;Liang Guo;P. Vidale

Evaluation of climate simulations produced with the Brazilian global atmospheric model version 1.2

DOI：
10.1007/s00382-020-05508-8
发表时间：
2020-10
期刊：
Climate Dynamics
影响因子：
4.6
作者：
Caio A. S. Coelho;D. C. de Souza;P. Kubota;S. S. Costa-S.;Layrson Menezes;B. S. Guimarães;S. Figueroa;J. P. Bonatti;I. F. Cavalcanti;G. Sampaio;N. Klingaman;J. Baker
通讯作者：
Caio A. S. Coelho;D. C. de Souza;P. Kubota;S. S. Costa-S.;Layrson Menezes;B. S. Guimarães;S. Figueroa;J. P. Bonatti;I. F. Cavalcanti;G. Sampaio;N. Klingaman;J. Baker

The Convection Connection: How Ocean Feedbacks Affect Tropical Mean Moisture and MJO Propagation