AMMA Further Analysis: Convective life-cycles over African continental surfaces

AMMA 进一步分析：非洲大陆表面的对流生命周期

基本信息

批准号：
NE/G018499/1
负责人：
Douglas Parker
金额：
$ 47.79万
依托单位：
University of Leeds
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%2FG018499%2F1
关键词：
AMMA Further Analysis Convective life

项目摘要

The population of West Africa rely on rainfall for their survival, since rainfall in most areas is the most important limit on agricultural production. Rainfall is also important in the availability of water for human consumption and for hydroelectric power generation, while the seasonal rainfall influences certain diseases such as malaria. Currently, our ability to predict rainfall in this region is extremely poor. This project aims to improve our understanding of the rain-bringing storms of West Africa, and improve our ability to forecast them. Through a knowledge-exchange programme with weather forecasters from the UK and West Africa, we will feed the new scientific understanding into daily and longer-term predictions. In the Sahel region during the monsoon season, most of the rain is delivered by large thunderstorm clouds, known as cumulonimbus, which can extend 20 kilometres upwards into the atmosphere. These cumulonimbus clouds band together into large, organised storms, several hundred km in extent, that produce intense rain, leading to patches of very wet soil. Often, after a storm, patches of wet soil lie adjacent to soil which remains extremely dry. In turn, the soil moisture patterns lie on top of a mixed distribution of vegetation, from forest to agriculture, savanna and desert. We know that such patterns in the land surface can interact with storms on the following days, and it is important to understand these processes for accurate weather forecasting. In the past, a major problem in quantifying this interaction between the land surface and cloud has been a lack of useful measurements from this remote region. Following the successful NERC-funded AMMA (African Monsoon Multidisciplinary Analysis) study, we now have unprecedented observational data for this region of the continental tropics. Using this dataset, we will analyse cases in which storms interact with the land surface, and therefore improve weather prediction models. The West African Monsoon is an airflow which brings humid air from the Atlantic Ocean into the continent: this humidity feeds the rain-bringing storms. However, moisture is also transported out of the low level, humid monsoon layer by smaller clouds, known as cumulus congestus. The rate at which moisture is mixed upwards by congestus clouds influences the water budget of the entire West African region, so we need to assess their effects if we are to get the forecast right. We will make use of chemical tracers measured during AMMA, to understand and evaluate the rates of congestus mixing, in reality and in models. We will use the UK Met Office weather and climate prediction model - the 'Unified Model' (UM). The UM is excellent for this kind of study because it can be used to describe a wide range of phenomena in the atmosphere, from small clouds a kilometre or so across, or the whole global atmosphere. Advances made in a sister project (Cascade) mean that now we have a version of the UM which can resolve clouds right across the continent, and assess the interactions between these clouds. Such interactions are just as important as the land surface state in setting off new storms -a big thunderstorm sets of patterns of waves in the atmosphere which move thousands of km across the continent and may commonly set off a new storm at a remote location. By resolving these processes in the Cascade version of the UM, we aim to understand what is needed to get them right in a weather prediction version of the UM. The UM is also used as a climate prediction model: currently, climate predictions for West Africa disagree on projections of future rainfall, which hinders effective mitigation strategies that could help in planning for local and international governments. The knowledge gained from this project will help not only in the day-to-day prediction of storm events but also in prediction of future rainfall trends.

西非的人口依靠降雨来生存，因为大多数地区的降雨是农业生产的最重要限制。降雨对于人类消费和水力发电发电的可用性也很重要，而季节性降雨会影响某些疾病，例如疟疾。目前，我们预测该地区降雨的能力极为差。该项目旨在提高我们对西非雨水风暴的理解，并提高我们预测它们的能力。通过来自英国和西非的天气预报员的知识交换计划，我们将向日常和长期预测提供新的科学理解。在季风季节，在萨赫勒地区，大部分雨水都是由大雷暴云（称为库隆布斯）传递的，可以将20公里向上延伸到大气中。这些云母云云将大的有组织的风暴融为一体，范围几百公里，会产生强烈的降雨，从而导致非常潮湿的土壤。通常，在暴风雨过后，湿土的斑块位于土壤附近，这些土壤仍然非常干燥。反过来，土壤水分模式位于植被分布的顶部，从森林到农业，稀树草原和沙漠。我们知道，在接下来的几天，陆地表面中的这种模式可以与风暴相互作用，重要的是要了解这些过程以进行准确的天气预测。过去，量化土地表面与云之间的这种相互作用的一个主要问题是缺乏该远程区域的有用测量。经过成功获得NERC资助的AMMA（非洲季风多学科分析）研究，我们现在已经为大陆热带地区的这一地区提供了前所未有的观察数据。使用此数据集，我们将分析风暴与土地表面相互作用的案例，从而改善天气预测模型。西非季风是一种气流，它将大西洋的潮湿空气带入大陆：这种潮湿的造成了雨水的风暴。然而，水分也被较小的云（称为Colecus concestus）从低水平的潮湿季风层输送出来。充血云将水分向上混合的速度会影响整个西非地区的水预算，因此，如果要正确进行预测，我们需要评估它们的影响。我们将利用在AMMA期间测量的化学示踪剂，以理解和评估过多的混合速率，实际上和模型。我们将使用英国大都会办公室的天气和气候预测模型 - “统一模型”（UM）。对于此类研究，UM非常出色，因为它可以用来描述大气中的广泛现象，从一公里左右的小云或整个全球气氛中。姊妹项目（Cascade）的进步意味着，现在我们有了UM版本，可以在整个非洲大陆上解决云，并评估这些云之间的相互作用。这种相互作用与陆地表面状态一样重要，这是一个新风暴 - 大气中的一系列波浪模式集合，这些模式在整个非洲大陆上移动了数千公里，并且通常会在偏远地区引发新的风暴。通过在UM的级联版本中解决这些过程，我们旨在了解在UM的天气预测版本中需要什么才能使它们正确。 UM也被用作气候预测模型：目前，西非对未来降雨的预测不同意的气候预测，这阻碍了有效的缓解策略，可以帮助计划地方和国际政府。从该项目中获得的知识不仅可以在暴风雨事件的日常预测中有助于预测未来的降雨趋势。