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Screening and Selecting Climate Change Impact Parameters as Potential Drivers of Migration - Focusing over the time period: 1975 to 2015

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The current report is focused on a technical screening and selecting exercise of climate/weather parameters and indices to be used in a bigger JRC Project on Climate Change Induced Migration (CLICIM). The main aim of the current exercise is to select among several tenths of variables and data sets, the ones that could be potentially influence directly or indirectly drivers of migration. Besides the mainstream climate change impact parameters such as temperature, wind, humidity, clouds and precipitation, we consider an extensive set of climate/weather extreme indices that could shed light on the possible relationships between environmental degradation parameters and induced migration.
In total we examine closely ninety five parameters and indices assessing their temporal and geographical coverage and relevance on the basis of the most recent climate change and migration literature before proceeding to the final selection of thirty seven meteorological parameters and extreme climate/weather indices. The report describes the data availability for each parameter and index, limitations and capabilities in terms of coverage and spatial and temporal detail and provides references on the use of the variable mainly in the context of migration studies. Such empirical evidence has been considered as the primary criterion for selecting parameters and indices potentially influencing drivers of migration. Other criteria guiding our selection have been the technical suitability in respect of the main population and net migration data already assembled during the initial phase of the CLICIM Project.
This report will be followed by a similar screening exercise focusing on agriculture and water scarcity indices. In the final steps of CLICIM, the full set of the indices documented in these two screening reports will be put in relation with population and net migration data at high spatial resolution and utilised in statistical models exploring potential links between climate change impacts and induced migration.