Detecting human influence on climate using neural networks based Granger causality

In this note we observe that a problem of linear approach to Granger causality testing between CO₂ and global temperature is that such tests can have low power. The probability to reject the null hypothesis of non-causality when it is false is low. Regarding non-linear Granger causality, based on multi-layer feed-forward neural network, the analysis provides evidence of significant unidirectional Granger causality from CO₂ to global temperature.     

Testing for linear Granger causality from?natural/anthropogenic forcings to global temperature anomalies

In this paper, we analyze the Granger causality from natural or anthropogenic forcings to global temperature anomalies. The lag-augmented Wald test is performed, and its robustness is also evaluated considering bootstrap method. The results show there is no-evidence of Granger causality from natural forcings to global temperature. On the contrary, a detectable Granger causality is found from anthropogenic forcings to global temperature confirming that greenhouse gases have an important role on recent global warming.     

气候检测与归因的格兰杰检验法

 为揭示气候变化并探索其可能原因,引入了格兰杰因果检验法。在叙述其基本原理的基础上,对影响中国气温变化的若干因子进行了检验。论证了通过检验的因子与中国气温变化的可能物理联系,着重说明了二氧化碳增加对中国气温变化的影响,解释了我国增温滞后于全球气温变化的原因。由此证实格兰杰因果检验法是气候变化检测与归因的一种有用的新方法。通过计算和分析,证实了格兰杰检验法的可用性。     

气候检测与归因的格兰杰检验法

为揭示气候变化并探索其可能原因,引入了格兰杰因果检验法。在叙述其基本原理的基础上,对影响中国气温变化的若干因子进行了检验。论证了通过检验的因子与中国气温变化的可能物理联系,着重说明了二氧化碳增加对中国气温变化的影响,解释了我国增温滞后于全球气温变化的原因。由此证实格兰杰因果检验法是气候变化检测与归因的一种有用的新方法。通过计算和分析,证实了格兰杰检验法的可用性。     

Exploring Granger causality between global average observed time series of carbon dioxide and temperature

Detection and attribution methodologies have been developed over the years to delineate anthropogenic from natural drivers of climate change and impacts. A majority of prior attribution studies, which have used climate model simulations and observations or reanalysis datasets, have found evidence for human-induced climate change. This papers tests the hypothesis that Granger causality can be extracted from the bivariate series of globally averaged land surface temperature (GT) observations and observed CO₂ in the atmosphere using a reverse cumulative Granger causality test. This proposed extension of the classic Granger causality test is better suited to handle the multisource nature of the data and provides further statistical rigor. The results from this modified test show evidence for Granger causality from a proxy of total radiative forcing (RC), which in this case is a transformation of atmospheric CO₂, to GT. Prior literature failed to extract these results via the standard Granger causality test. A forecasting test shows that a holdout set of GT can be better predicted with the addition of lagged RC as a predictor, lending further credibility to the Granger test results. However, since second-order-differenced RC is neither normally distributed nor variance stationary, caution should be exercised in the interpretation of our results.     

What is the link between temperature and carbon dioxide levels? A Granger causality analysis based on ice core data

We use statistical methods to analyze whether there exists long-term causality between temperature and carbon dioxide concentration. The analysis is based on a the Vostok Ice Core data from 400,000 to 6,000 years ago, extended by the EPICA Dome C data which go back to 800,000 years ago. At first, to make the data equidistant, we reconstruct it by linear interpolation. Then, using an approximation of a piecewise exponential function, we adjust for a deterministic trend. Finally, we employ the Granger causality test. We are able to strongly reject the null hypothesis that carbon dioxide concentration does not Granger cause temperature as well as the reverse hypothesis that temperature does not Granger cause carbon dioxide concentration.     

Is Granger causality analysis appropriate to investigate the relationship between atmospheric concentration of carbon dioxide and global surface air temperature?

Summary Many time series based studies use Granger causality analysis in order to investigate the connection between atmospheric carbon-dioxide concentrations and global mean temperature. This note re-examines the causal relationship between these variables and shows the inappropriateness of the Granger test to the problem under investigation.     

北京气候变暖与主要极端气温指数的归因分析

在对资料进行均一化处理的基础上,分析了北京1960—2008 年气候变暖及主要极端气温指数的统计特征,并应用格兰杰检验法对其进行归因分析。结果表明:(1) 近49 a 来北京年平均气温增速约为0.39 ℃/(10 a),气候增暖具有明显的非对称性。(2) 霜冻指数和气温年较差呈下降趋势,降幅为3.9 d/(10 a)和0.8 ℃/(10 a)。生长季指数、暖夜指数及热浪指数则呈上升趋势,增幅平均达3.0 d/(10 a)、0.75%/(10 a)和1.5 d/(10 a)。(3) 北京年平均气温是霜冻指数、生长季指数及暖夜指数发生变化的格兰杰原因。虽然年平均气温与热浪指数在不同滞后期均具强相关性,但是检验表明它们之间并无显著的因果关系,很可能是由于某种原因导致的一种统计上的伪相关现象。      

Anthropogenic and natural causes of climate change

We test for causality between radiative forcing and temperature using multivariate time series models and Granger causality tests that are robust to the non-stationary (trending) nature of global climate data. We find that both natural and anthropogenic forcings cause temperature change and also that temperature causes greenhouse gas concentration changes. Although the effects of greenhouse gases and volcanic forcing are robust across model specifications, we cannot detect any effect of black carbon on temperature, the effect of changes in solar irradiance is weak, and the effect of anthropogenic sulfate aerosols may be only around half that usually attributed to them.     

Might electricity consumption cause urbanization instead? Evidence from heterogeneous panel long-run causality tests

The share of a population living in urban areas, or urbanization, is both an important demographic, socio-economic phenomenon and a popular explanatory variable in macro-level models of energy and electricity consumption and their resulting carbon emissions. Indeed, there is a substantial, growing subset of the global modeling literature that seeks to link urbanization with energy and electricity consumption, as well as with carbon emissions. This paper aims to inform both modelers and model consumers about the appropriateness of establishing such a link by examining the nature of long-run causality between electricity consumption and urbanization using heterogeneous panel methods and data from 105 countries spanning 1971–2009. In addition, the analysis of the time series properties of urbanization has implications both for modelers and for understanding the urbanization phenomenon. We consider total, industrial, and residential aggregations of electricity consumption per capita, three income-based panels, and three geography-based panels for non-OECD countries. The panel unit root, cointegration, and causality tests used account for cross-sectional dependence, nonstationarity, and heterogeneity – all of which are present in the data set. We cannot reject pervasively Granger causality in the urbanization to electricity consumption direction. However, the causality finding that is both the strongest and most similar across the various panels is that of long-run Granger causality from electricity consumption to urbanization. In other words, the employment and quality of life opportunities that access to electricity afford likely encourage migration to cities, and thus, cause urbanization. Also, nearly all countries’ urbanization series contained structural breaks, and the most recent post-break annual change rates suggested that nearly all countries’ rates of urbanization change were slowing. Lastly, future modeling work on energy consumption or carbon emissions should consider subnational scales of analysis, and focus on measures of urban density or urban form rather than national urbanization levels.     

世界排放大国CO2排放和GDP的格兰杰因果分析及其对国际气候治理的影响和意义

基于1990—2015年世界前20个排放大国碳排放量和国内生产总值（GDP）的时间序列数据,采用协整分析、格兰杰因果检验,对主要排放大国碳排放与经济增长之间的关系进行了实证分析。通过协整分析得出大多数国家的碳排放量与经济增长之间存在长期均衡关系;碳排放量和GDP的格兰杰检验结果显示,大多数世界排放大国碳排放与经济增长之间存在单向因果关系。发达国家主要表现为经济增长是碳排放的格兰杰原因,发展中国家则主要表现为碳排放是经济增长的格兰杰原因。研究结果反映了发达国家和发展中国家在碳减排问题上的阶段性特征,碳减排对发展中国家经济发展的负面影响明显大于发达国家。基于格兰杰因果分析结果,国际气候治理进程中关于要求发展中国家现阶段提出大幅减排目标的诉求不符合发展中国家发展阶段特征,可能影响发展中国家经济发展的正常秩序和规律。发达国家基于历史排放责任、发展阶段和能力,都应该带头开展减排行动,并帮助发展中国家实现转型、升级发展,降低经济发展对碳排放的依赖。国际气候治理需要根据并考虑不同国家的发展需求和特征,形成国际合作制度安排,实现社会经济发展与全球气候治理的协同。     

Contribution of Greenhouse Gas Radiative Forcing and Atlantic Multidecadal Oscillation to Surface Air Temperature Trends

The contributions of radiative forcing of greenhouse gases (GHG) and Atlantic Multidecadal Oscillation (AMO) to the trends in global surface air temperature (GST) and surface air temperature for different latitude bands are estimated. Instrumental observational data obtained since the middle of the 19th century and three-component autoregressive models are used. Characteristics of influences of both factors on GST (Wiener–Granger causality) are obtained. The contribution of AMO over the length intervals of 15–30 years appears comparable in absolute value to the contribution of GHG and sometimes even exceeds it, while its contribution over 60-year and longer periods is insignificant. During the recent decades, GHG contribute stronger to the trends of GST and tropical surface air temperature, while their contribution to the trends in surface air temperature in the middle and high latitudes is smaller.     

我国留学生人数的预测及其对居民消费的影响

采用1985-2012年数据,利用时间序列分析方法,建立了刻画我国出国留学人数变动的模型ARIMA（2,2,2）,得到较好的预测效果.同时研究了出国留学人数与我国城镇居民人均消费性支出之间的关系,建立了相应的模型,并进行了Granger 因果关系检验.结果表明：出国留学生数的对数每增加1%,城镇居民人均消费性支出的对数将增加近0.06%.     

Intense coastal rainfall in the Netherlands in response to high sea surface temperatures: analysis of the event of August 2006 from the perspective of a changing climate

August 2006 was an exceptionally wet month in the Netherlands, in particular near the coast where rainfall amounts exceeded 300% of the climatological mean. August 2006 was preceded by an extremely warm July with a monthly mean temperature of almost 1°C higher than recorded in any other summer month in the period 1901–2006. This had resulted in very high sea surface temperatures (SSTs) in the North Sea at the end of July. In this paper the contribution of high SSTs to the high rainfall amounts is investigated. In the first part of this study, this is done by analyzing short-term integrations with a regional climate model (RACMO2) operated at 6 km resolution, which are different in the prescribed values of the SSTs. In the second part of the paper the influence of SSTs on rainfall is analyzed statistically on the basis of daily observations in the Netherlands during the period 1958–2006. The results from both the statistical analysis as well as the model integrations show a significant influence of SSTs on precipitation. This influence is particularly strong in the coastal area, that is, less than 30–50 km from the coastline. With favorable atmospheric flow conditions, the analyzed dependency is about +15% increase per degree temperature rise, thereby exceeding the Clausius–Clapeyron relation—which is often used as a temperature related constraint on changes in extreme precipitation—by approximately a factor of two. It is shown that the coastal area has consistently become wetter compared to the inland area since the 1950s. This finding is in agreement with the rather strong observed trend in SST over the same period and the dependencies of rainfall on SST reported in this study.     

温度变化对南京城市电力负荷的影响

应用计量经济学中格兰杰因果关系检验方法,分析了温度变化对中国南京城市用电量和电力负荷的影响,认为南京日平均温度与日最大电力负荷、日用电量之间存在着较显著的相关性.气温变化对日最大电力负荷和日用电量具有不同的季节性和周期性影响,气温对用电量的短期影响最显著,对电力负荷的影响更具明显的季节性特征.通过不同月份电力负荷对气温变化敏感性的分析,进一步揭示了南京市气温变化与电力消费之间的季节变动特征,有利于气象与能源部门共同应对未来气候变化带来的城市能源问题.     

The coupling of optimal economic growth and climate dynamics

In this paper, we study optimal economic growth programs coupled with climate change dynamics. The study is based on models derived from MERGE, a well established integrated assessment model (IAM). We discuss first the introduction in MERGE of a set of “tolerable window” constraints which limit both the temperature change and the rate of temperature change. These constraints, obtained from ensemble simulations performed with the Bern 2.5-D climate model, allow us to identity a domain intended to preserve the Atlantic thermohaline circulation. Next, we report on experiments where a two-way coupling is realized between the economic module of MERGE and an intermediate complexity “3-D-” climate model (C-GOLDSTEIN) which computes the changes in climate and mean temperature. The coupling is achieved through the implementation of an advanced “oracle based optimization technique” which permits the integration of information coming from the climate model during the search for the optimal economic growth path. Both cost-effectiveness and cost-benefit analysis modes are explored with this combined “meta-model” which we refer to as GOLDMERGE. Some perspectives on future implementations of these approaches in the context of “collaborative” or “community” integrated assessment modules are derived from the comparison of the different approaches.     

Air temperature trend and the impact on winter wheat phenology in Romania

Air temperature variability and trends in Romania were analysed using monthly, seasonal, and annual datasets. Temperature data of winter wheat season were also analysed. The Mann-Kendall test, Sen’s slope estimate, the sequential version of the Mann-Kendall test, the Pettitt test and spatial and temporal hierarchical cluster analyses were used. First, the datasets were checked for changing points. The 106-year period was divided into two long periods of 100 years each to verify the importance of a very short interval in changing of general trends; after that it was divided into three shorter periods of 35–36 years each. The main conclusions are as follows: the 6 years making up the difference between the two long periods are very important in the context of the recent global warming; the three shorter periods analysis indicate some fluctuations rather than continuous warming. The latest short period is the most relevant for global warming. Spatial hierarchical cluster analysis indicated the existence of two distinctive groups. One of them, which includes stations in the south-east part of the country, seems to be influenced by the Black Sea surface temperature. Temporal hierarchical cluster analysis reveals that annual data series have the closest relation with the summer data series. Further, the impact of temperature changes on winter wheat phenology was determined using a phenology simulation performed with the model from the Decision Support System for Agrotechnology Transfer v. 4.0.2.0 platform. Earlier occurrences of anthesis and maturity were noticed for several regions in the country.     

A global ocean temperature and altimeter data assimilation system for studies of climate variability

 An ocean data assimilation (ODA) system which can assimilate both temperature and altimeter observations has been applied to the global ocean and tested between January 1993–October 1996. A statistical method has been used to convert sea surface height (SSH) anomalies observations from TOPEX/POSEIDON into synthetic temperature profiles. The innovative aspect of this method is the introduction of time dependency in the correlations used to transform the altimeter observations into temperature corrections. The assimilation system is based on a univariate variational optimal interpolation scheme applied to assimilate both in situ and synthetic temperature profiles. In addition, a longer global analysis for the upper-ocean temperature starting from January 1979 and ending November 1997, has been produced to examine the skill of sea temperature assimilation with a rather simple and practical method. The temperature analysis shows encouraging improvement over a corresponding ocean simulation when compared to independent (not assimilated) temperature data both at seasonal and interannual time scales. However, the univariate data assimilation of hydrographic data does not result in an improvement of the velocity field. In fact the assimilation of sparse in situ data can introduce unrealistic spatial variability in the temperature field which affects the velocity field in a negative way. This deficiency is partially overcome when we also assimilate altimeter observations since the coverage is complete and uniform for this data. In particular, our study shows that temperature corrections due to the altimeter signal have a positive impact on the current system in the tropical Pacific. Received: 28 May 2000 / Accepted: 6 November 2000     

IPCC第五次评估报告第一工作组主要结论对《联合国气候变化框架公约》进程的影响分析

IPCC评估报告对国际气候变化谈判进程有重要影响,目前正在陆续发布的第五次评估报告已明确作为气候变化新协议谈判的重要信息来源,对讨论2020年后应对气候变化国际合作机制的影响不容忽视。最先发布的第一工作组评估报告基于新的科学观测事实、更为完善的归因分析和气候系统模式模拟结果,进一步确认了气候变暖的事实,发现了人类活动与全球温升之间因果关系的新证据,以及温室气体累积排放与温升响应之间的定量联系。本文通过分析其中一些关键结论可能的政策含义,探讨了这些关键结论对目前国际气候变化谈判进程和新协议等相关问题的可能影响,探讨了科学信息在气候变化决策过程中的作用,以及如何更为科学地理解和利用这些重要结论。     

Estimating the annual mean screen temperature empirically

Summary We have examined station data from around the world to study the separate effects of the latitude (between 60° N–40° S), elevation and distance inland, on the annual-mean screen temperature. In the first 200–400 km from some west coasts, screen temperatures (after adjustment for elevation) rise inland, reaching a maximum called the ‘thermal-ridge temperature’ Tr. The rise of temperature within this littoral fringe (of width F) depends mainly on the difference between the sea-surface temperature off the west coast and the zonal mean. Further inland than such a fringe, adjusted temperatures generally decline eastwards, approximately linearly, at a rate C. The rate is related to hemisphere and latitude. Empirical relationships between latitude and the observed coastal sea-surface temperature, the near-shore screen temperature, Tr, C and F for each continent are used to estimate annual mean temperatures on land. Independent estimates of this kind for 48 places, using a look-up table, differ overall by only 0.7 K from the actual long-term average annual mean temperatures. This is less than half the error resulting from an assumption of zonal-mean temperatures. Basing estimates on coastal sea-surface temperatures, instead of the look-up table, results in an average error of 1.0 K for the 48 places. The errors are comparable with the standard deviation of annual mean temperatures during 30 years or so. Received March 6, 2001 Revised July 30, 2001