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Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes

异质景观上的雪-植被-大气相互作用

基本信息

批准号：
NE/H008187/1
负责人：
Richard Essery
金额：
$ 41.31万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2010
资助国家：
英国
起止时间：
2010 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FH008187%2F1
关键词：
Snow Vegetation Atmosphere Interactions over

项目摘要

By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. Computer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients. The aim of this project is to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions. We will gather information on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites have been chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. Using 28 radiometers, and moving them several times during the course of each experiment, will allow us to measure the highly variable patterns of radiation at the snow surface in forests. Information from the field experiments will be used in developing and testing a range of models. To reach the scales of interest, we will begin with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective is a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. We will work in close consultation with project partners at climate modelling and forecasting centres to ensure that our activities are directed towards outcomes that will meet their requirements.

明亮的雪和黑暗的森林通过改变地表吸收的太阳辐射量，对天气和气候产生强烈的影响;无论是雪覆盖的减少还是森林覆盖的增加，都会使下面的雪变暗，增加辐射的吸收，使上面的空气变暖。因此，天气预报和气候预测的计算机模型必须通过计算地面积雪量的变化以及辐射与森林冠层的相互作用来考虑这些影响。这些模型的分辨率一般都很粗糙，从几公里到几百公里不等。不能指望森林覆盖在如此长的距离上是连续的;相反，北方的景观是万年青和落叶林、空地、沼泽和湖泊的马赛克。雪可以被风从空旷地区带走，被周围的植被遮蔽，或者从森林树冠升华而不会到达地面，这些影响积雪模式的过程取决于开口的大小，植被的结构和天气条件。雪本身通过提供水分，使植物和土壤免受冬季寒冷的温度和储存养分来影响植被覆盖的模式。该项目的目的是开发更好的方法，在模型中表示雪，植被和大气之间的相互作用，对于实际应用，不能解决这些相互作用模式的重要尺度。我们将在北极地区的两个实地实验中收集关于雪、植被和辐射分布的信息：一个在瑞典，另一个在芬兰。之所以选择这些地点，是因为它们有长期的天气和降雪条件记录，交通方便，卫星和飞机提供的植被覆盖图很好，景观范围从稀疏的落叶林到茂密的针叶林，这是大得多的地区的典型特征。使用28个辐射计，并在每次实验过程中多次移动它们，将使我们能够测量森林雪表面高度可变的辐射模式。从实地实验中获得的信息将用于开发和测试一系列模型。为了达到感兴趣的尺度，我们将开始使用一个模型，该模型显式地解析各个树，并逐步通过具有更粗糙分辨率的模型进行工作，在每个阶段对模型进行相互测试，并与观察结果进行比较。最终目标是建立一个能够更好地利用地貌信息来预测地表辐射吸收以及积雪的积累和融化的模型。我们将与气候建模和预报中心的项目伙伴密切协商，以确保我们的活动旨在取得满足其要求的成果。