Vegetation Effects on Rainfall in West Africa (VERA)

植被对西非降雨量的影响 (VERA)

基本信息

  • 批准号:
    NE/M004295/1
  • 负责人:
  • 金额:
    $ 34.58万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 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

项目摘要

Rainfall is the climatic parameter of greatest importance to the populations of the tropical continents. The arrival of monsoon rains drives a rapid transformation of the landscape, allowing crops to grow and river networks to refill. Yet predicting where and when rain will fall in the tropics is a notoriously difficult problem. Progress has been made in predicting how remote ocean conditions, such as El Nino, can affect rainfall in different parts of the tropics. However local factors such as vegetation also play a role. For example, when tropical forests are cut down for agriculture, we have evidence that this affects rainfall both locally, and across neighbouring countries. Indeed, climate scientists have to take into account future deforestation rates as well as greenhouse gas emissions when they assess how tropical climate will change in the 21st century.Vegetation affects rainfall through the process of transpiration. When plants absorb carbon dioxide for photosynthesis, they lose water from their leaves. Trees are able to extract this water from several metres below the surface using their deep roots, allowing them to continue photosynthesising for months without rainfall. Crops and grasses on the other hand start to run out of soil water during dry spells, which reduces transpiration. Instead the solar radiation absorbed by the plant canopy raises the air temperature. Replacing forests with crops and grasslands changes the rates of moistening and heating of the atmosphere, particularly when the shallow-rooted species start to run out of soil water. These changes in turn affect the development of winds, cloud and rain.The details of how the atmosphere responds to vegetation is an area of significant scientific debate. Firstly, there is evidence that clearing patches of forest may increase rainfall over the cleared area and reduce it over the remaining forest, depending on the particular weather patterns. On the other hand, new results have shown that as air masses cross the continent, they pick up additional moisture from forests, which then leads to more rain several hundred kilometres further downwind. Finally, by controlling the balance between heating and moistening of the atmosphere, the vegetation can affect the winds bringing moist air off the ocean, delaying or extending the rainy seasons which characterise tropical climate.Although these 3 vegetation effects are each known to affect rainfall, we rely on computer models of the vegetation and atmosphere to understand how they might work in combination. Capturing the essential physical processes within a model is very challenging. In particular, there are large and long-standing uncertainties in the description of cumulonimbus storms (thunderstorms, which dominate the rainfall of many tropical regions) within the models. However through recent advances in computing power, we are now able to run these models for entire seasons with sufficient spatial detail to properly capture storms.In this project we will use data from satellites and the latest weather and climate models to get to the heart of how vegetation affects rainfall. Focusing on West Africa, one of the most climatically sensitive regions of the world, we will examine cloud and vegetation observations from the last 30 years to detect where deforestation has changed rainfall, and how the rapid greening of the savannah each year affects the monsoon rains. We will perform new computer simulations, incorporating the detailed development of thousands of individual storms, and examine what happens when we artificially deforest a region in the model. These results will allow us to assess the performance of the somewhat cruder models used to forecast climate change globally. By focusing on specific processes in the climate system, our results will help to improve these models, and at the same time provide robust conclusions on deforestation to guide land managers.
降雨量是对热带大陆人口最重要的气候参数。季风雨的到来推动了景观的迅速转变,使作物生长和河流网络重新填充。然而,预测热带地区何时何地会下雨是一个众所周知的难题。在预测厄尔尼诺等遥远的海洋条件如何影响热带不同地区的降雨方面已经取得了进展。然而,植被等当地因素也发挥了作用。例如,当热带森林被砍伐用于农业时,我们有证据表明这会影响当地和邻国的降雨量。事实上,气候科学家在评估热带气候在21世纪世纪的变化时,必须考虑到未来的森林砍伐率和温室气体排放。当植物吸收二氧化碳进行光合作用时,它们会从叶子中失去水分。树木能够利用它们的深根从地表以下几米处提取这些水,使它们能够在没有降雨的情况下持续数月进行光合作用。另一方面,作物和草在干旱期间开始耗尽土壤水分,这减少了蒸腾作用。相反,植物冠层吸收的太阳辐射提高了空气温度。用农作物和草地代替森林改变了大气的增湿和升温速率,特别是当浅根物种开始耗尽土壤水分时。这些变化反过来影响风、云和雨的发展。大气如何对植被做出反应的细节是一个重要的科学争论领域。首先,有证据表明,清除森林斑块可能会增加已清除地区的降雨量,并减少剩余森林的降雨量,这取决于特定的天气模式。另一方面,新的研究结果表明,随着气团穿越非洲大陆,它们从森林中吸收了额外的水分,从而导致顺风数百公里处的降雨量增加。最后,通过控制大气加热和湿润之间的平衡,植被可以影响风,将潮湿的空气带离海洋,延迟或延长热带气候的雨季。尽管这三种植被效应都被认为会影响降雨,但我们依靠植被和大气的计算机模型来了解它们是如何结合在一起工作的。在模型中捕捉基本的物理过程是非常具有挑战性的。特别是,在模型中,积雨云风暴(雷暴,在许多热带地区降雨中占主导地位)的描述存在着长期的巨大不确定性。然而,通过最近的计算能力的进步,我们现在能够在整个季节运行这些模型,具有足够的空间细节,以正确捕捉风暴。在这个项目中,我们将使用来自卫星的数据和最新的天气和气候模型,以了解植被如何影响降雨的核心。西非是世界上气候最敏感的地区之一,我们将研究过去30年的云和植被观测,以发现森林砍伐改变了降雨量,以及每年萨凡纳的快速绿化如何影响季风降雨。我们将进行新的计算机模拟,结合数千个单独风暴的详细发展,并检查当我们人工砍伐模型中的一个区域时会发生什么。这些结果将使我们能够评估用于预测全球气候变化的较为粗糙的模型的性能。通过关注气候系统中的特定过程,我们的研究结果将有助于改进这些模型,同时提供有关森林砍伐的可靠结论,以指导土地管理者。

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)
The Global Monsoon System - Research and Forecast
全球季风系统 - 研究与预测
  • DOI:
    10.1142/9789813200913_0004
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Lafore J
  • 通讯作者:
    Lafore J
Analytical solution to a thermodynamic model for the sensitivity of afternoon deep convective initiation to the surface Bowen ratio
The First Forecasters' Handbook for West Africa
What Drives the Intensification of Mesoscale Convective Systems over the West African Sahel under Climate Change?
  • DOI:
    10.1175/jcli-d-19-0380.1
  • 发表时间:
    2020-04-01
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    Fitzpatrick, Rory G. J.;Parker, Douglas J.;Tucker, Simon
  • 通讯作者:
    Tucker, Simon
Simulation of vegetation feedbacks on local and regional scale precipitation in West Africa
  • DOI:
    10.1016/j.agrformet.2016.03.001
  • 发表时间:
    2016-05-28
  • 期刊:
  • 影响因子:
    6.2
  • 作者:
    Hartley, Andrew J.;Parker, Douglas J.;Webster, Stuart
  • 通讯作者:
    Webster, Stuart
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Christopher Taylor其他文献

The Development of an Experimental Model of Contaminated Muscle Injury in Rabbits
兔污染性肌肉损伤实验模型的建立
Assessment of antimicrobial peptide LL-37 as a post-exposure therapy to protect against respiratory tularemia in mice
抗菌肽 LL-37 作为暴露后治疗预防小鼠呼吸道兔热病的评估
  • DOI:
    10.1016/j.peptides.2013.02.024
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    3
  • 作者:
    H. Flick;M. Fox;K. Hamblin;Mark I. Richards;D. Jenner;T. Laws;A. Phelps;Christopher Taylor;Sarah V. Harding;D. Ulaeto;H. Atkins
  • 通讯作者:
    H. Atkins
Experimental respiratory Marburg virus haemorrhagic fever infection in the common marmoset (Callithrix jacchus)
普通狨猴(Callithrix jacchus)实验性呼吸道马尔堡病毒出血热感染
  • DOI:
    10.1111/iep.12018
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    3
  • 作者:
    S. Smither;M. Nelson;L. Eastaugh;T. Laws;Christopher Taylor;Simon A. Smith;F. Salguero;M. Lever
  • 通讯作者:
    M. Lever
Transgenic Neuroscience Research
转基因神经科学研究
  • DOI:
    10.17226/25362
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    3
  • 作者:
    S. Smither;M. Nelson;L. Eastaugh;T. Laws;Christopher Taylor;Simon A. Smith;F. Salguero;M. Lever
  • 通讯作者:
    M. Lever
Economics at the FTC: Multi-level Marketing and a Coal Joint Venture
  • DOI:
    10.1007/s11151-021-09845-8
  • 发表时间:
    2021-11-02
  • 期刊:
  • 影响因子:
    0.700
  • 作者:
    Marta Wosińska;David Givens;Yan Lau;Doug S. Smith;Christopher Taylor;Benjamin Wallace
  • 通讯作者:
    Benjamin Wallace

Christopher Taylor的其他文献

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{{ truncateString('Christopher Taylor', 18)}}的其他基金

Nowcasting with Artificial Intelligence for African Rainfall: NAIAR
利用人工智能预测非洲降雨量:NAIAR
  • 批准号:
    NE/Y000420/1
  • 财政年份:
    2024
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant
Humid heat extremes in the Global (sub)Tropics (H2X)
全球(亚)热带地区的极端湿热(H2X)
  • 批准号:
    NE/X013596/1
  • 财政年份:
    2023
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant
Manufacturing the Future with Supercritical CO2 and Minimum Quantity Lubrication
用超临界二氧化碳和微量润滑制造未来
  • 批准号:
    EP/W002175/1
  • 财政年份:
    2022
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant
Land Impacts on Mesoscale Convective Systems
土地对中尺度对流系统的影响
  • 批准号:
    NE/W001888/1
  • 财政年份:
    2022
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant
CC* Compute: Compute Cluster for Computational Sciences at Louisiana State University Health Sciences Center – New Orleans (LSUHSC-NO)
CC* 计算:路易斯安那州立大学健康科学中心 — 新奥尔良 (LSUHSC-NO) 的计算科学计算集群
  • 批准号:
    2018936
  • 财政年份:
    2020
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Standard Grant
AMMA-2050 NEC05274
AMMA-2050 NEC05274
  • 批准号:
    NE/M020428/2
  • 财政年份:
    2019
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant
CSBR: Natural History Collections: Integrating the Orphaned Southern Illinois University Fluid Vertebrate Collections into the Illinois Natural History Survey Collections
CSBR:自然历史收藏:将南伊利诺伊大学孤儿流体脊椎动物收藏整合到伊利诺伊州自然历史调查收藏中
  • 批准号:
    1916255
  • 财政年份:
    2019
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Standard Grant
Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)
对流组织与季风降水、大气、地表和海洋的相互作用 (INCOMPASS)
  • 批准号:
    NE/L013819/1
  • 财政年份:
    2015
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant
RAPID: Transferring the Southern Illinois University Fluid Vertebrate Collections to the Illinois Natural History Survey
RAPID:将南伊利诺伊大学流体脊椎动物收藏转移至伊利诺伊州自然历史调查
  • 批准号:
    1529366
  • 财政年份:
    2015
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Standard Grant
IMPALA: Improving Model Processes for African cLimAte
IMPALA:改进非洲气候模型流程
  • 批准号:
    NE/M017230/1
  • 财政年份:
    2015
  • 资助金额:
    $ 34.58万
  • 项目类别:
    Research Grant

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Dynamic Credit Rating with Feedback Effects
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CAREER: Transformative Understanding of Rainfall-Triggered Landslides with Vegetation Effects from a Climate Change Perspective: Initiation and Consequences
职业:从气候变化的角度对降雨引发的山体滑坡及其植被影响进行变革性的理解:起因和后果
  • 批准号:
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研究阐明当地风系变化和沿海海面温度波动对关东平原夏季气温和局地强降雨的影响
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Vegetation Effects on Rainfall in West Africa (VERA)
植被对西非降雨量的影响 (VERA)
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