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Structural changes in long-term trends of the dynamics of the upper atmosphere

高层大气动态长期趋势的结构变化

基本信息

批准号：
36432611
负责人：
Professor Dr. Christoph Jacobi
金额：
--
依托单位：
Institut für Meteorologie
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2007
资助国家：
德国
起止时间：
2006-12-31 至 2010-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/36432611?language=en
关键词：
Structural changes long term trends

项目摘要

Experimental evidence has shown that, differing from the behaviour of middle atmosphere temperature, mesosphere/lower thermosphere (MLT) winds do not exhibit a clear long-term trend pattern, which is probably due to the interplay of lower and middle atmospheric sources of MLT dynamical variations. To clarify the role of different sources in MLT variations, time series of middle atmosphere winds will be investigated with respect to structural changes in long-term trends recently observed. Taking into account the relatively short data series and inhomogeneous time series available, sophisticated statistical tools will be used to assess the time when possible middle atmosphere trends change their structure and the type of these changes. These analyses will be complemented by comparison with variations and trends of troposphere-stratosphere parameters related to dynamics, ozone behaviour, lower ionospheric parameters, and external influence as solar flux, geomagnetic field and cosmic ray flux variations to obtain information on possible sources of middle atmosphere wind trends and their changes. Numerical modelling of the middle atmosphere response to lower atmosphere changes will be performed using state-of-the-art circulation models of the middle atmosphere. Time slice runs based upon reanalysis data will be used to clarify the influence of the lower atmosphere on middle atmosphere trends.

实验证据表明，与中层大气温度行为不同，中层/低热层(MLT)风没有明显的长期趋势模式，这可能是由于MLT动力变化的中、低大气源相互作用所致。为了阐明不同来源在MLT变化中的作用，将根据最近观测到的长期趋势的结构变化来研究中层大气风的时间序列。考虑到现有的数据序列相对较短和时间序列不均匀，将使用复杂的统计工具来评估可能的中层大气趋势改变其结构的时间和这些改变的类型。这些分析将与与动力学、臭氧行为、低电离层参数以及太阳通量、地球磁场和宇宙射线通量变化等外部影响有关的对流层-平流层参数的变化和趋势进行比较，以获得关于中大气风趋势及其变化的可能来源的信息。将使用最先进的中层大气环流模式对中层大气对低层大气变化的响应进行数值模拟。基于再分析数据的时间切片运行将用于阐明低层大气对中层大气趋势的影响。