{"title":"从新生代到现代气候中温度-二氧化碳因果关系的随机评估。","authors":"Demetris Koutsoyiannis","doi":"10.3934/mbe.2024287","DOIUrl":null,"url":null,"abstract":"<p><p>As a result of recent research, a new stochastic methodology of assessing causality was developed. Its application to instrumental measurements of temperature (<i>T</i>) and atmospheric carbon dioxide concentration ([CO<sub>2</sub>]) over the last seven decades provided evidence for a unidirectional, potentially causal link between <i>T</i> as the cause and [CO<sub>2</sub>] as the effect. Here, I refine and extend this methodology and apply it to both paleoclimatic proxy data and instrumental data of <i>T</i> and [CO<sub>2</sub>]. Several proxy series, extending over the Phanerozoic or parts of it, gradually improving in accuracy and temporal resolution up to the modern period of accurate records, are compiled, paired, and analyzed. The extensive analyses made converge to the single inference that change in temperature leads, and that in carbon dioxide concentration lags. This conclusion is valid for both proxy and instrumental data in all time scales and time spans. The time scales examined begin from annual and decadal for the modern period (instrumental data) and the last two millennia (proxy data), and reach one million years for the most sparse time series for the Phanerozoic. The type of causality appears to be unidirectional, <i>T</i>→[CO<sub>2</sub>], as in earlier studies. The time lags found depend on the time span and time scale and are of the same order of magnitude as the latter. These results contradict the conventional wisdom, according to which the temperature rise is caused by [CO<sub>2</sub>] increase.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stochastic assessment of temperature-CO2 causal relationship in climate from the Phanerozoic through modern times.\",\"authors\":\"Demetris Koutsoyiannis\",\"doi\":\"10.3934/mbe.2024287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>As a result of recent research, a new stochastic methodology of assessing causality was developed. Its application to instrumental measurements of temperature (<i>T</i>) and atmospheric carbon dioxide concentration ([CO<sub>2</sub>]) over the last seven decades provided evidence for a unidirectional, potentially causal link between <i>T</i> as the cause and [CO<sub>2</sub>] as the effect. Here, I refine and extend this methodology and apply it to both paleoclimatic proxy data and instrumental data of <i>T</i> and [CO<sub>2</sub>]. Several proxy series, extending over the Phanerozoic or parts of it, gradually improving in accuracy and temporal resolution up to the modern period of accurate records, are compiled, paired, and analyzed. The extensive analyses made converge to the single inference that change in temperature leads, and that in carbon dioxide concentration lags. This conclusion is valid for both proxy and instrumental data in all time scales and time spans. The time scales examined begin from annual and decadal for the modern period (instrumental data) and the last two millennia (proxy data), and reach one million years for the most sparse time series for the Phanerozoic. The type of causality appears to be unidirectional, <i>T</i>→[CO<sub>2</sub>], as in earlier studies. The time lags found depend on the time span and time scale and are of the same order of magnitude as the latter. These results contradict the conventional wisdom, according to which the temperature rise is caused by [CO<sub>2</sub>] increase.</p>\",\"PeriodicalId\":49870,\"journal\":{\"name\":\"Mathematical Biosciences and Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematical Biosciences and Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.3934/mbe.2024287\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biosciences and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3934/mbe.2024287","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
摘要
最近的一项研究成果是开发了一种新的随机因果关系评估方法。将该方法应用于过去 70 年的温度(T)和大气二氧化碳浓度([CO2])的仪器测量,证明了温度是因,[CO2]是果,两者之间存在单向的、潜在的因果联系。在此,我对这一方法进行了完善和扩展,并将其应用于古气候代用数据以及 T 和 [CO2] 的仪器数据。我汇编、配对和分析了几个代用系列,它们跨越新生代或新生代的部分时期,在精确度和时间分辨率方面逐渐提高,直至现代的精确记录时期。通过广泛的分析,得出了一个单一的推论,即温度变化领先,而二氧化碳浓度变化滞后。这一结论适用于所有时间尺度和时间跨度的代用数据和仪器数据。所研究的时间尺度从现代(仪器数据)和过去两千年(代用数据)的年度和十年度开始,到新生代最稀少的时间序列的一百万年。与之前的研究一样,因果关系的类型似乎是单向的,即 T→[CO2]。发现的时间滞后取决于时间跨度和时间尺度,其数量级与后者相同。这些结果与[CO2]增加导致气温上升的传统观点相矛盾。
Stochastic assessment of temperature-CO2 causal relationship in climate from the Phanerozoic through modern times.
As a result of recent research, a new stochastic methodology of assessing causality was developed. Its application to instrumental measurements of temperature (T) and atmospheric carbon dioxide concentration ([CO2]) over the last seven decades provided evidence for a unidirectional, potentially causal link between T as the cause and [CO2] as the effect. Here, I refine and extend this methodology and apply it to both paleoclimatic proxy data and instrumental data of T and [CO2]. Several proxy series, extending over the Phanerozoic or parts of it, gradually improving in accuracy and temporal resolution up to the modern period of accurate records, are compiled, paired, and analyzed. The extensive analyses made converge to the single inference that change in temperature leads, and that in carbon dioxide concentration lags. This conclusion is valid for both proxy and instrumental data in all time scales and time spans. The time scales examined begin from annual and decadal for the modern period (instrumental data) and the last two millennia (proxy data), and reach one million years for the most sparse time series for the Phanerozoic. The type of causality appears to be unidirectional, T→[CO2], as in earlier studies. The time lags found depend on the time span and time scale and are of the same order of magnitude as the latter. These results contradict the conventional wisdom, according to which the temperature rise is caused by [CO2] increase.
期刊介绍:
Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing.
MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).