Human-induced Climate Change Research Articles

Teaching and learning in uncertain times: thinking with multiple crises

ABSTRACT Teachers are working in disturbing and challenging times, characterised by coterminous crises, the Covid-19 pandemic and human induced climate change; these are transforming our working conditions and the lives of students and teachers. In this research, we looked to our own pedagogical practices as teacher educators to collaboratively explore what it means to be teachers and learners in uncertain times of multiple crises. We use a collaborative autoethnographic methodology to better understand the kind of educator these times demand and consider the implications for teacher education. Through fictionalised, co-constructed vignettes that act as pedagogical encounters, we explore our collaborative experiences in relation to multiple crises: in the classroom, at climate strikes, and in conversations with teachers during the pandemic. We use these vignettes to think with and through teaching during the global pandemic and the climate catastrophe, and with young people’s climate activism. Thinking with these vignettes, we analyse the ways (young) people across the world were already creating and are continuing to create, prefiguratively, different possible futures through public and ‘everyday’ modes of political action for climate justice, and what this might mean for teacher education.

Arctic weather variability and connectivity

The Arctic’s rapid sea ice decline may influence global weather patterns, making the understanding of Arctic weather variability (WV) vital for accurate weather forecasting and analyzing extreme weather events. Quantifying this WV and its impacts under human-induced climate change remains a challenge. Here we develop a complexity-based approach and discover a strong statistical correlation between intraseasonal WV in the Arctic and the Arctic Oscillation. Our findings highlight an increased variability in daily Arctic sea ice, attributed to its decline accelerated by global warming. This weather instability can influence broader regional patterns via atmospheric teleconnections, elevating risks to human activities and weather forecast predictability. Our analyses reveal these teleconnections and a positive feedback loop between Arctic and global weather instabilities, offering insights into how Arctic changes affect global weather. This framework bridges complexity science, Arctic WV, and its widespread implications.

Climate change should drive mammal defaunation in tropical dry forests.

Human-induced climate change has intensified negative impacts on socioeconomic factors, the environment, and biodiversity, including changes in rainfall patterns and an increase in global average temperatures. Drylands are particularly at risk, with projections suggesting they will become hotter, drier, and less suitable for a significant portion of their species, potentially leading to mammal defaunation. We use ecological niche modelling and community ecology biodiversity metrics to examine potential geographical range shifts of non-volant mammal species in the largest Neotropical dryland, the Caatinga, and evaluate impacts of climate change on mammal assemblages. According to projections, 85% of the mammal species will lose suitable habitats, with one quarter of species projected to completely lose suitable habitats by 2060. This will result in a decrease in species richness for more than 90% of assemblages and an increase in compositional similarity to nearby assemblages (i.e., reduction in spatial beta diversity) for 70% of the assemblages. Small-sized mammals will be the most impacted and lose most of their suitable habitats, especially in highlands. The scenario is even worse in the eastern half of Caatinga where habitat destruction already prevails, compounding the threats faced by species there. While species-specific responses can vary with respect to dispersal, behavior, and energy requirements, our findings indicate that climate change can drive mammal assemblages to biotic homogenization and species loss, with drastic changes in assemblage trophic structure. For successful long-term socioenvironmental policy and conservation planning, it is critical that findings from biodiversity forecasts are considered.

Through-life stochastic carbon emission assessment and optimisation for critical assets

International governments and businesses are increasingly pledging more action to address human-induced climate change, including committing to the Paris Climate Agreement, which seeks to reduce global Greenhouse Gas Emissions (GHGE). Critical assets provide essential capabilities where failure could have catastrophic consequences. These assets have long service lives and are exposed to varying operational conditions and service requirements, which makes assessing through-life GHGE challenging. Current modelling techniques provide deterministic, single-point results, which provides a limited assessment of critical asset through-life GHGE where uncertainty can be significant. Furthermore, no modelling technique was identified that relates asset GHGE to Whole Life Cost (WLC) and operational effectiveness, which are both organisational priorities. This leaves decision-makers without robust information regarding the possible impacts of GHGE reduction strategies on the WLC and the operational effectiveness of their critical assets. This study develops a methodology framework to model critical asset GHGE with WLC and operational availability based on industry best practices and transferrable modelling techniques from other sectors. A model was created based on an in-service helicopter platform and was subjected to four test scenarios to demonstrate effects on WLC, GHGE and operational availability relative to baseline. Monte Carlo simulation was used to appropriately present modelling uncertainty.

Synchronized slowdown of climate warming and carbon sink enhancement over deciduous broadleaf forests based on FLUXNET analysis

The temperate deciduous broadleaf forests (DBFs) are widely distributed in middle and high latitudes and play vital role in providing ecosystem services and mitigating human induced climate change, however, the responses of the carbon sink of DBFs to recent warming slowdown were not well known at regional scale. Here, we investigated the temporal pattern of carbon sink in DBFs and its drivers based on the eddy covariance carbon flux observations at 15 FLUXNET sites from 1997 to 2014. The annual mean net ecosystem production (NEP) was 272 ± 43 g C m−2 yr−1 during 1997–2005 and it increased to 445 ± 13 g C m−2 yr−1 during 2006–2014, as a result of boosted gross primary production (GPP) and weakened ecosystem respiration, respectively. We found slowdown in trends of temperature and carbon sink enhancement during 2006–2014. The NEP decreased at the rate of −11.9 g C m−2 yr−1 during the warming slowdown period (2006–2014, p < 0.05) compared to a prior strong increased trend during the warming period (1997–2005, 47.6 g C m−2 yr−1, p < 0.05). The mean annual temperature dominated the inter-annual variation of NEP (46.9 %), and it worked together with seasonal water availability to control the NEP changes. The slowdown of peak photosynthesis growth rate and carbon uptake period (CUP) extension may contribute to the NEP reversal during the later period. Our results demonstrated that the carbon uptake potential of temperate DBFs may highly depend on warming trends.

Assessing coastal bathymetry and climate change impacts on coastal ecosystems using Landsat 8 and Sentinel-2 satellite imagery

Coastal ecosystems are facing heightened risks due to human-induced climate change, including rising water levels and intensified storm events. Accurate bathymetry data is crucial for assessing the impacts of these threats. Traditional data collection methods can be cost-prohibitive. This study investigates the feasibility of using freely accessible Landsat and Sentinel satellite imagery to estimate bathymetry and its correlation with hydrographic chart soundings in Port Klang, Malaysia. Through analysis of the blue and green spectral bands from the Landsat 8 and Sentinel 2 datasets, a bathymetry map of Port Klang's seabed is generated. The precision of this derived bathymetry is evaluated using statistical metrics like Root Mean Square Error (RMSE) and the coefficient of determination. The results reveal a strong statistical connection (R2 = 0.9411) and correlation (R2 = 0.7958) between bathymetry data derived from hydrographic chart soundings and satellite imagery. This research not only advances our understanding of employing Landsat imagery for bathymetry assessment but also underscores the significance of such assessments in the context of climate change's impact on coastal ecosystems. The primary goal of this research is to contribute to the comprehension of Landsat imagery's utility in bathymetry evaluation, with the potential to enhance safety protocols in seaport terminals and provide valuable insights for decision-making concerning the management of coastal ecosystems amidst climate-related challenges. The findings of this research have practical implications for a wide range of stakeholders involved in coastal management, environmental protection, climate adaptation and disaster preparedness.

Distribution patterns of Quercus ilex from the last interglacial period to the future by ecological niche modeling.

The plants' geographic distribution is affected by natural or human-induced climate change. Numerous studies at both the global and regional levels currently focus on the potential changes in plant distribution areas. Ecological niche modeling can help predict the likely distribution of species according to environmental variables under different climate scenarios. In this study, we predicted the potential geographic distributions of Quercus ilex L. (holm oak), a keystone species of the Mediterranean ecosystem, for the Last Interglacial period (LIG: ~130 Ka), the Last Glacial Maximum (LGM: ~22 Ka), mid-Holocene (MH: ~6 Ka), and future climate scenarios (Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios) for 2050-2070 obtained from CCSM4 and MIROC-ESM global climate scenarios respectively. The models were produced with algorithms from the R-package "biomod2" and assessed by AUC of the receiver operating characteristic plot and true skill statistics. Aside from BIOCLIM (SRE), all model algorithms performed similarly and produced projections that are supported by good evaluation scores, although random forest (RF) slightly outperformed all the others. Additionally, distribution maps generated for the past period were validated through a comparison with pollen data acquired from the Neotoma Pollen Database. The results revealed that southern areas of the Mediterranean Basin, particularly coastal regions, served as long-term refugia for Q. ilex, which was supported by fossil pollen data. Furthermore, the models suggest long-term refugia role for Anatolia and we argue that Anatolia may have served as a founding population for the species. Future climate scenarios indicated that Q. ilex distribution varied by region, with some areas experiencing range contractions and others range expands. This study provides significant insights into the vulnerability of the Q. ilex to future climate change in the Mediterranean ecosystem and highlights the crucial role of Anatolia in the species' historical distribution.

Winter is coming: Interactions of multiple stressors in winter and implications for the natural world.

Winter is a key driver of ecological processes in freshwater, marine and terrestrial ecosystems, particularly in higher latitudes. Species have evolved various adaptive strategies to cope with food limitations and the cold and dark wintertime. However, human-induced climate change and other anthropogenic stressors are impacting organisms in winter in unpredictable ways. In this paper, we show that global change experiments investigating multiple stressors have predominantly been conducted during summer months. However, effects of anthropogenic stressors sometimes differ between winter and other seasons, necessitating comprehensive investigations. Here, we outline a framework for understanding the different effects of anthropogenic stressors in winter compared to other seasons and discuss the primary mechanisms that will alter ecological responses of organisms (microbes, animals and plants). For instance, while the magnitude of some anthropogenic stressors can be greater in winter than in other seasons (e.g. some pollutants), others may alleviate natural winter stress (e.g. warmer temperatures). These changes can have immediate, delayed or carry-over effects on organisms during winter or later seasons. Interactions between stressors may also vary with season. We call for a renewed research direction focusing on multiple stressor effects on winter ecology and evolution to fully understand, and predict, how ecosystems will fare under changing winters. We also argue the importance of incorporating the interactions of anthropogenic stressors with winter into ecological risk assessments, management and conservation efforts.

Warmer and wetter: Outlining climate services for snow-dependent tourism in Norway – The case of Lofoten

Human-induced climate change potentially impacts nature-based activities in Lofoten and may limit the attractiveness of the destination for tourists seeking recreation and adventure in the mountains. As a climate service, we calculated climate indicators relevant to the tourism sector based on the representative concentration pathways RCP4.5 and RCP8.5 until 2060. We used high-resolution gridded climate data and projections to calculate indicators such as changes in the frequency and intensity of consecutive wet days, changes in precipitation type (snow, sleet, rain), changes in the number of skiing days on ungroomed, natural snow, and changes of the monthly 0 °C-isoline. We found a minor, but non-robust increase in the number of consecutive wet days with a precipitation intensity > 8 mm/day, and a clear change in the precipitation regime depending on altitude that leads to more precipitation falling as rain instead of snow. Also, a strong decrease in the number of skiing days is projected by the climate models as the monthly near-surface 0 °C-isoline increases. These are important findings for long-term planning and investments in the tourism sector in Lofoten, especially as tourism growth is considered an important tool for regional economic development. The analytical methods used in this study are transferable to analyses on a regional to national scale. National maps and data material for 11 regions were recently published on https://klimaservicesenter.no/kss/framskr/sno-sludd-regn.

The Impact of Climate Change on Environmental Sustainability and Human Mortality

Climate dictates the critical aspects of human environmental conditions. The frequency and intensity of extreme weather conditions due to human-induced climate change have alarmingly increased. Consequently, climate change directly affects environmental sustainability and human mortality in the short term and creates prolonged and complicated long-term indirect grave risks. This paper examines three-level environmental impact risks associated with climate change on human mortality. It proposes a conceptual framework for developing an empirical event-based human mortality database related to climate change and communication strategies to enhance global environmental adaptation, resilience, and sustainability.

Attribution of 2022 early-spring heatwave in India and Pakistan to climate change: lessons in assessing vulnerability and preparedness in reducing impacts

In March 2022, large parts over the north Indian plains including the breadbasket region, and southern Pakistan began experiencing prolonged heat, which continued into May. The event was exacerbated due to prevailing dry conditions in the region, resulting in devastating consequences for public health and agriculture. Using event attribution methods, we analyse the role of human-induced climate change in altering the chances of such an event. To capture the extent of the impacts, we choose March–April average of daily maximum temperature over the most affected region in India and Pakistan as the variable. In observations, the 2022 event has a return period of ∼1-in-100 years. For each of the climate models, we then calculate the change in probability and intensity of a 1-in-100 year event between the actual and counterfactual worlds for quantifying the role of climate change. We estimate that human-caused climate change made this heatwave about 1 °C hotter and 30 times more likely in the current, 2022 climate, as compared to the 1.2 °C cooler, pre-industrial climate. Under a future global warming of 2 °C above pre-industrial levels, heatwaves like this are expected to become even more common (2–20 times more likely) and hotter (by 0 °C–1.5 °C) compared to now. Stronger and frequent heat waves in the future will impact vulnerable groups as conditions in some regions exceed limits for human survivability. Therefore, mitigation is essential for avoiding loss of lives and livelihood. Heat Action Plans have proved effective to help reduce heat-related mortality in both countries.

The many paths for an open, participatory, and inclusive science

Watch VIDEO. Societies are facing unprecedented challenges due to human-induced climate change. In order to understand, cope with and halt global warming, we need to understand the science behind its causes and impacts and to identify reliable sources of information. Science and scientists play a crucial role in this process and are called to the forefront of new relational practices for engaging the public and helping citizens develop scientific competences to participate in contemporary societies. Empowering individuals with sustainable-oriented knowledge, skills and values is vital for an active citizenship towards sustainability. Moreover, promoting dialogic channels between science and society encourages a more critical view of current challenges and science-oriented attitudes. Participatory methodologies can play an essential role in this context as they entail the inclusion of citizens in research and/or knowledge production and a closer contact with local and global realities. I will discuss different paths taken in national and international research projects to promote the inclusion of citizens in science. I will focus on two examples. One related to how citizen science can be used in educational contexts to reconfigure schools as collaborative ecosystems, part of a network that connects teachers, students, and scientists, who share the responsibility to identify problems, think about possible solutions, reflect on existing knowledge, collect new evidence, and integrate different perspectives. Results show positive impacts on a personal and academic level, with participants declaring higher self-esteem and a deeper understanding of the scientific process and social and environmental issues. A second example concerns dialogical and arts-based strategies to include academic, political, and activist stakeholders in the public debate on the opportunities and challenges of biotechnology. These strategies are framed within a concept of engaged citizen social science, considering that engagement with science should be bidirectional, where both scientists and the public are committed to establishing an effective dialogue between different forms of knowledge to co-create new meanings and impacts for project outcomes. It is also rooted in interdisciplinary dialogues through interaction between the disciplinary fields of the partners and the individuals involved in the social dialogue to create a shared vocabulary and contribute to a transformative impact of the project on social realities. The planned art-based approaches to science will help facilitate participation through more dynamic, creative, and meaningful engagement and greater understanding of different worldviews, thoughts, and understandings. Preliminary results suggest a greater awareness of the different dimensions related to the development and (unanticipated) impacts of new technology by the scientists and the artists involved in this co-creation process.

The effect of short-term exposure to high temperatures on male courtship behaviour and mating success in the fruit fly Drosophila virilis

Human-induced climate change is leading to higher average global temperatures and increasingly extreme weather events. High temperatures can have obvious effects on animal survival, particularly in ectotherms. However, the temperature at which organisms become sterile may be significantly lower than the temperature at which other biological functions are impaired. In the fruit fly Drosophila virilis, males are sterilized at temperatures above 34 °C, but are still active and able to mate normally. We investigated the male behavioural changes associated with high-temperature fertility loss. We exposed males to a warming treatment of 34.4 °C or 36.6 °C for 4 h, and then recorded their mating behaviour after being allowed to recover for 24 h. Previous work in this species suggests that males exposed to 34.4 °C lose the ability to produce new sperm, but can utilize mature sperm produced before the heat shock. We therefore predicted that these males would increases their courtship rate, and reduce their choosiness, in order to try to ensure a mating before their remaining mature sperm die. In contrast, over two-thirds of males exposed to 36.6 °C are completely sterile. In standard mating trials, earlier exposure to 34.4 °C or 36.6 °C did not affect male courtship behaviour when compared to control males kept at 23 °C. Exposure to high temperatures also did not alter the extent to which males directed courtship toward females of the same species. However, males exposed to 36.6 °C were significantly slower to mate, and had a reduced likelihood of mating, when compared to control males. Overall, exposure to high temperatures did not alter male courtship behaviour, but did lower their likelihood of mating. This suggests that females can distinguish between normal and heat-sterilized males before mating, and that female mate choice may at least partly mitigate the population-level consequences of high-temperature induced male sterility in this species.

Labour Law and the ‘Capitalocene’: Law, Work and Nature in the Ecological Long Durée

The concept of the ‘Capitalocene’ draws attention to the origins of the climate crisis in capitalist dynamics, and specifically to the need for natural resources to be reproduced for less than their true cost if firms are to remain profitable. This insight suggests that the environmental crisis, manifested by extreme climate events, and the crisis in labour law, manifested by wage suppression and rising inequality, have the same root cause. Bringing production and reproduction back into balance will require changes of a structural kind to the global economy, and a rethinking of the law-nature nexus. Labour Law, Extreme Climate Events, Human-Induced Climate Change, Anthropocene, Capitalocene, Rising Inequality, Law-Nature Nexus

Assessing the Impact of Human-Induced and Climate Change-Driven Streamflow Alterations on Freshwater Ecosystems

Streamflow is critical and master variable for maintaining healthy and restorative processes in freshwater ecosystems. However, human-induced dam construction and climate change have significantly altered the flow regime and disrupted hydrological conditions. Consequently, protecting river ecosystems has become a crucial goal, necessitating environmental streamflow assessments. This study evaluates the impact of dam construction and climate change on the flow regime and environmental flow in the Gamcheon Basin, Korea. It focuses on two fish species, the dominant Zacco platypus and endangered Squalidus gracilis majimae, using an ecosystem function model to determine the appropriate environmental flow. GIS analysis was also employed to quantify the habitat connectivity within the assessed environmental streamflow. The study provides key insights into preserving streamflow and revitalizing river ecosystems, highlighting the need for a broader multi-species analysis for environmental flow determination and conservation. By determining the appropriate environmental flow and analyzing habitat connectivity, effective strategies can be developed for protecting and maintaining healthy freshwater ecosystems in a changing climate.

Multi-temporal downscaling of daily to sub-daily streamflow for flash flood watersheds at ungauged stations using a hybrid framework

Unprecedented flash floods (FFs) in urban regions have been rising due to the increasing intensity and magnitude of heavy rainfall resulting from human-induced climate and land-use changes. Modelling of FF along different spatiotemporal scales is extremely complex since FF models require multi-resolution forcing and observed information. In the absence of sub-daily, and multi-site streamflow data, multi-temporal downscaling (MTD) plays a crucial role for FF modeling. While a wide range of methods are available for the spatio-temporal downscaling of climate data, the applicability of the MTD strategy for streamflow has not been investigated yet. The current study proposed a MTD methodology for yielding the daily to sub-daily streamflow of gauged and ungauged stations using adaptive emulator modelling concepts. The proposed MTD framework for ungauged stations is a hybrid model that draws on conceptual and machine learning-based approaches to analyze catchment behavior. The study selected the Peachtree Creek watershed (United States) since it frequently experiences FFs. Results suggest that model-derived sub-daily streamflow had minimal uncertainty in capturing hydrological signatures and nearly 95% accuracy in predicting flow attributes over ungauged stations. The proposed framework can be useful for planning, mitigation, and management, where the fine resolution data is required.

Attributing Human Traits to Other Species as Alignment Work

Against the backdrop of human-induced climate change and severe biodiversity loss, feminist technoscience scholars stress the need for movements towards less anthropocentric knowledge production processes. The present paper delves into the alignment work involved in striving to coordinate and align human-centred epistemic cultures and epistemic cultures centring other species. In an early childhood education site, children, teachers, materials, imagination and the attribution of human traits to snails are elaborated on as key actors. In a literary fiction site, also referred to as environmental imagination, texts, choices of literary style, scientific facts and the attribution of human traits to eels, are featured as actors accomplishing alignment work. The paper argues that adding the concept of the terrestrial to the analysis of the alignment work, as proposed by feminist technoscience scholar Donna Haraway, makes other aspects and versions of non-anthropocentric or less anthropocentric knowledge production processes visible. The paper adds to STS-discussions on alignment work through highlighting alignment work processes as political, power-producing processes, which privilege certain interests while downplaying others.

Lconnect R package: A versatile tool for evaluating landscape connectivity and prioritizing habitat patches in conservation research

Biodiversity conservation faces significant challenges due to human-induced climate and habitat change. Understanding these threats’ effects and interactions is crucial for effective conservation planning. Here, we present the lconnect R package, a user-friendly tool for assessing landscape connectivity and prioritizing habitat patches. The package allows researchers to analyze and quantify structural connectivity metrics and prioritize patches based on their contribution to overall landscape connectivity. By facilitating the evaluation of landscape connectivity and patch prioritization, lconnect supports informed decision-making in landscape ecology and conservation biology. The package's advantages, relative to other available tools, are discussed, and an example of its application is presented. Overall, the lconnect R package presents a valuable addition to the toolbox of landscape ecologists, empowering them to better understand and address the challenges of habitat fragmentation and loss in biodiversity conservation.

Long-term preconditioning of the coral Pocillopora acuta does not restore performance in future ocean conditions

There is overwhelming evidence that tropical coral reefs are severely impacted by human induced climate change. Assessing the capability of reef-building corals to expand their tolerance limits to survive projected climate trajectories is critical for their protection and management. Acclimation mechanisms such as developmental plasticity may provide one means by which corals could cope with projected ocean warming and acidification. To assess the potential of preconditioning to enhance thermal tolerance in the coral Pocillopora acuta, colonies were kept under three different scenarios from settlement to 17 months old: present day (0.9 °C-weeks (Degree Heating Weeks), + 0.75 °C annual, 400 ppm pCO2) mid-century (2.5 °C-weeks, + 1.5 °C annual, 685 ppm pCO2) and end of century (5 °C-weeks, + 2 °C annual, 900 ppm pCO2) conditions. Colonies from the present-day scenario were subsequently introduced to the mid-century and end of century conditions for six weeks during summer thermal maxima to examine if preconditioned colonies (reared under these elevated conditions) had a higher physiological performance compared to naive individuals. Symbiodiniaceae density and chlorophyll a concentrations were significantly lower in mid-century and end of century preconditioned groups, and declines in symbiont density were observed over the six-week accumulated heat stress in all treatments. Maximum photosynthetic rate was significantly suppressed in mid-century and end of century preconditioned groups, while minimum saturating irradiances were highest for 2050 pre-exposed individuals with parents originating from specific populations. The results of this study indicate preconditioning to elevated temperature and pCO2 for 17 months did not enhance the physiological performance in P. acuta. However, variations in trait responses and effects on tolerance found among treatment groups provides evidence for differential capacity for phenotypic plasticity among populations which could have valuable applications for future restoration efforts.

More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models

Adapting to human-induced climate change is becoming an increasingly important aspect of sustainable development. To be able to do this effectively, it is important to know how much human influence has contributed to observed climate trends. Climate detection and attribution (D&amp;A) studies achieve this by estimating scaling factors usually obtained by performing a least squares regression of the observed trending climate variable on the equivalent variable simulated by a climate model. This study proposed instead to estimate scaling factors by using the econometric approach of dynamically modelling the time series as a cointegrating Vector Auto-Regressive (VAR) time series process. It is shown that a 2nd-order cointegrating VAR(2) model is theoretically justified if the observed and simulated variables can be represented as a one-box AR(1) response to a common integrated forcing. The VAR(2) model can be expressed as a Vector Error-Correction Model (VECM) and then fitted to the data to obtain the cointegration relationship, the stationary linear combination of the two variables, from which the scaling factor is then easily obtained. Estimates of the scaling factor from the VAR(2) model are critically compared to those from Ordinary Least Squares (OLS) and Total Least Squares (TLS) for annual Global Mean Surface Temperature (GMST) data simulated by a simple stochastic model of the carbon–climate system and for historical simulations from 16 climate models in the Coupled Model Intercomparison Project 5 (CMIP5) experiment. Results from the toy model simulations show that the slope estimates from OLS are negatively biased, TLS estimates are less biased but have high variance, and the VAR(2) estimates are unbiased and have lower variance and provide the most accurate estimates with smallest mean squared error. Similar behaviour is noted in the CMIP5 data. Hypothesis tests on the VAR(2) fits found strong evidence of a cointegrating relationship with the observations for all the CMIP5 simulations.