Detecting patterns of climate change in long-term forecasts of marine environmental parameters
在海洋的环境参数的长期的预报检测气候变化的模式作者机构：Istituto di Scienza e Tecnologie dell’Informazione“A.Faedo”–CNRPisaItaly b Food and Agriculture Organization of the United Nations(FAO)RomeItaly
出 版 物：《International Journal of Digital Earth》 (国际数字地球学报（英文）)
年 卷 期：2020年第13卷第5期
页 面：567-585页
核心收录：
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
主 题：Climate change environmental parameters forecasting environmental parameters time series ecological modelling species distribution modelling AquaMaps NASA Earth Exchange
摘 要：Forecasting environmental parameters in the distant future requires complex modelling and large computational *** to the sensitivity and complexity of forecast models,long-term parameter forecasts(*** to 2100)are uncommon and only produced by a few organisations,in heterogeneous formats and based on different assumptions of greenhouse gases ***,data mining techniques can be used to coerce the data to a uniform time and spatial representation,which facilitates their use in many *** this paper,streams of big data coming from AquaMaps and NASA collections of 126 long-term forecasts of nine types of environmental parameters are processed through a cloud computing platform in order to(i)standardise and harmonise the data representations,(ii)produce intermediate scenarios and new informative parameters,and(iii)align all sets on a common time and spatial *** series crosscorrelation applied to these aligned datasets reveals patterns of climate change and similarities between parameter trends in 10 marine *** results highlight that(i)the Mediterranean Sea may have a standalone‘response’to climate change with respect to other areas,(ii)the Poles are most representative of global forecasted change,and(iii)the trends are generally alarming for most oceans.
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