TAMSAT rainfall climatology and time series for East Africa workshop

东非研讨会 TAMSAT 降雨气候学和时间序列

• 批准号: NE/I008594/1
• 负责人: David Grimes
• 金额: $ 7.2万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI008594%2F1
• 关键词: TAMSAT; rainfall; climatology; time; series

Current predictions of rainfall climate change in Africa are vague and uncertain. This is in part due to the fact that African rainfall climate is poorly monitored. If we are not sure of the current climate, how can we provide reliable forecasts of what will happen in the future? There is therefore a need for an improved data set of African rainfall which has good spatial coverage and spans a sufficiently long time period to detect long term trends and estimate variability. In order to quantify trends and variability, the data set must also be temporally homogeneous, which is to say it must be based on a consistent set of data inputs and use the same algorithm for the whole time period. Such a data set would be invaluable for analysing past climate variability as well as facilitating improvements in seasonal rainfall forecasts and climate change predictions. These improvements are urgently needed for more reliable warnings of drought, more timely response of humanitarian organisations when necessary, and for better long term economic planning for Africa in general. Currently available rainfall data from gauges are too sparse and intermittent to provide the required data set. Satellite methods offer good spatial coverage but generally lack temporal homogeneity because they use a mixture of different inputs which vary in time. The only satellite approach which provides reliable estimates, full spatial coverage for Africa, long time series and temporal homogeneity is the TAMSAT algorithm, developed at the University of Reading. A time series for Africa based on retrospective use of the full Meteosat thermal infra red archive dating back to 1982 is now being processed at Reading and should be completed by October, 2010. The overall aim is to transfer the time series and methodology to end users via a series of workshops in Africa. Running workshops in Africa minimises costs, allows participation of more African scientists and provides the opportunity to improve the rainfall estimates by augmenting the calibration with additional raingauge data only available within the national meteorological services. A pilot workshop funded by Google has already been run for the Ethiopian National Meteorological Agency and was very successful. Building on this experience, within the proposed project we seek to run a second workshop in Uganda in January 2011 for several countries in the East African region. The workshop will provide participating countries with the full time series for their region augmented by local calibration, plus software to carry on adding to the archive. In the spirit of the 'Knowledge Exchange' programme, the improvements in time series made as a result of the locally available gauge data will be fed back to the climate research community. As well as Uganda, the participants will include 2 representatives from each of the Sudanese and Rwandan meteorological services and 2 representatives from SWALIM (Somali Walter and Land Information Management). Outputs from the workshop are particularly important for Somalia and Rwanda because of the lack of historic raingauge data due to political turbulence in these countries. To support this and future workshops, we are also requesting funding to upgrade and simplify existing software tools so as to provide a user-friendly software package which will be used within the workshops for raingauge quality control, satellite estimate calibration and time series generation. In the longer term, we aim to continue to collaborate with the scientists involved in further analysis and application of the rainfall data set. Opportunities will be sought for funding to run similar workshops in other regions.

目前对非洲降雨气候变化的预测是模糊和不确定的。部分原因是非洲的降雨气候监测不足。如果我们不确定当前的气候，我们如何能提供可靠的预测未来会发生什么？因此，有必要改进非洲降雨量数据集，使其具有良好的空间覆盖面，并涵盖足够长的时间，以发现长期趋势和估计变异性。为了量化趋势和变异性，数据集还必须是时间上均匀的，也就是说，它必须基于一组一致的数据输入，并在整个时间段内使用相同的算法。这样一套数据对于分析过去的气候变异性以及促进改进季节性降雨预报和气候变化预测将是非常宝贵的。这些改进是迫切需要的，以便更可靠地发出干旱警报，在必要时人道主义组织作出更及时的反应，并为整个非洲制定更好的长期经济规划。目前从雨量计获得的降雨量数据过于稀少和断断续续，无法提供所需的数据集。卫星方法提供了良好的空间覆盖，但一般缺乏时间均匀性，因为它们混合使用随时间变化的不同输入。阅读大学开发的TAMSAT算法是唯一一种卫星方法，它提供可靠的估计、对非洲的全面空间覆盖、长时间序列和时间均匀性。阅读目前正在处理非洲的时间序列，该时间序列是在追溯使用气象卫星热红外线档案的基础上编制的，可追溯到1982年，应于2010年10月完成。总体目标是通过在非洲举办一系列讲习班，向最终用户转让时间序列和方法。在非洲举办讲习班可以最大限度地降低成本，使更多的非洲科学家能够参与，并提供机会，通过使用只有国家气象部门才能提供的额外雨量计数据来加强校准，从而改进降雨量估计。由谷歌资助的一个试点讲习班已经为埃塞俄比亚国家气象局举办，并且非常成功。在这一经验的基础上，我们在拟议的项目范围内寻求于2011年1月在乌干达为东非地区的几个国家举办第二次讲习班。讲习班将向参加国提供其区域的完整时间序列，并通过当地校准加以扩充，加上软件，以便继续增加档案。本着“知识交流”方案的精神，由于当地现有的测量数据而对时间序列作出的改进将反馈给气候研究界。除乌干达外，与会者还将包括苏丹和卢旺达气象部门的2名代表以及SWALIM（索马里沃尔特和土地信息管理）的2名代表。研讨会的成果对索马里和卢旺达特别重要，因为这两个国家的政治动荡导致历史雨量数据缺乏。为了支持这次和今后的讲习班，我们还要求提供资金，以更新和简化现有的软件工具，以便提供一个方便用户的软件包，在讲习班内用于雨量计质量控制、卫星估计校准和时间序列生成。从长远来看，我们的目标是继续与参与进一步分析和应用降雨数据集的科学家合作。将寻找机会筹集资金，在其他区域举办类似的讲习班。