Biogeophysical impacts of land use on present-day climate: near-surface temperature change and radiative forcing

Changes in land cover affect climate through the surface energy and moisture budgets, but these biogeophysical impacts of land use have not yet been included in General Circulation Model (GCM) simulations of 20th century climate change. Here, the importance of these effects was assessed by comparing climate simulations performed with current and potential natural vegetation. The northern mid-latitude agricultural regions were simulated to be approximately 1–2 K cooler in winter and spring in comparison with their previously forested state, due to deforestation increasing the surface albedo by approximately 0.1 during periods of snow cover. Some other regions such as the Sahel and India experienced a small warming due to land use. Although the annual mean global temperature is only 0.02 K lower in the simulation with present-day land use, the more local temperature changes in some regions are of a similar magnitude to those observed since 1860. The global mean radiative forcing by anthropogenic surface albedo change relative to the natural state is simulated to be −0.2 Wm², which is comparable with the estimated forcings relative to pre-industrial times by changes in stratospheric and tropospheric ozone, N₂O, halocarbons, and the direct effect of anthropogenic aerosols. Since over half of global deforestation has occurred since 1860, simulations of climate since that date should include the biogeophysical effects of land use.     

Quantifying the contributions of anthropogenic and natural forcings to climate changes over arid-semiarid areas during 1946–2005

In this study, the contributions from changes in man-made greenhouse gases (GHG), anthropogenic aerosols (AA), and land use (LU), as well as natural solar and volcanic (NAT) forcing changes, to observed changes in surface air temperature (T) and precipitation (P) over global land, especially over arid-semiarid areas, during 1946–2005 are quantified using observations and climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Results show that the anthropogenic (ANT) forcings dominate the ubiquitous surface warming seen in observations and lead to slight increases in precipitation over most land areas, while the NAT forcing leads to small cooling over land. GHG increases are the primary factor responsible for the anthropogenic climate change, while the AA forcing offsets a large part of the GHG-induced warming and P changes. The LU forcing generally contributes little to the T and P changes from 1946 to 2005 over most land areas. Unlike the consistent temperature changes among most model simulations, precipitation changes display a large spread among the models and are incomparable with the observations in spatial distributions and magnitude, mainly due to its large internal variability that varies among individual model runs. Using an optimal fingerprinting method, we find that the observed warming over land during 1946–2005 can be largely attributed to the ANT forcings, and the combination of the ANT and NAT forcings can explain about 85~95% of the observed warming trend over global land as well as over most arid-semiarid regions such as Northern China. However, the anthropogenic influences on precipitation over the past 60 years are generally undetectable over most land areas, including most arid-semiarid regions. This indicates that internal variability is still larger than the forced change for land precipitation.     

Effects of Land Cover Conversion on Surface Climate

This study investigates the effects of large-scale human modification of land cover on regional and global climate. A general circulation model (Colorado State University GCM) coupled to a biophysically-based land surface model (SiB2) was used to run two 15-yr climate simulations. The control run used current vegetation distribution as observed by satellite for the year 1987 to derive the vegetation's physiological and morphological properties. The twin simulation used a realistic approximation of vegetation type distribution that would exist in the absence of human disturbance.In temperate latitudes, where anthropogenic modification of the landscape has converted large areas of forest and grassland to cropland, conversion cools canopy temperatures up to 0.7 ° C in summer and 1.1 ° C in winter. This cooling results from both (1) morphological changes in vegetation which increase albedo and (2) physiological changes in vegetation which increase latent heat flux of crops compared with undisturbed vegetation during the growing season. In the tropics and subtropics, conversion warms canopy temperature by about 0.8 ° C year round. The warming results from a combination of morphological changes in vegetation offset by physiological changes that reduce latent heat flux of existing compared with undisturbed vegetation. If water efficient, tropical C4 grasses replace C3 vegetation, latent heat flux is further reduced.The overall effect of land cover conversion is cooling in temperate latitudes and warming in the tropics. Because the effects are opposite in sign in tropics and middle latitudes, they cancel each other when averaged globally. Over land, the surface temperature increased by 0.2 C in winter and remained essentially unchanged in summer. The effects on land surface hydrology were also small when averaged globally. The results suggest that the effects of land use change of the observed magnitude do not have a strong impact on the globally averaged climate but their signature at regional scales is significant and vary according to the type of land cover conversion.     

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.     

A comparison of a GCM response to historical anthropogenic land cover change and model sensitivity to uncertainty in present-day land cover representations

This study assesses the sensitivity of the fully coupled NCAR-DOE PCM to three different representations of present-day land cover, based on IPCC SRES land cover information. We conclude that there is significant model sensitivity to current land cover characterization, with an observed average global temperature range of 0.21 K between the simulations. Much larger contrasts (up to 5 K) are found on the regional scale; however, these changes are largely offsetting on the global scale. These results show that significant biases can be introduced when outside data sources are used to conduct anthropogenic land cover change experiments in GCMs that have been calibrated to their own representation of present-day land cover. We conclude that hybrid systems that combine the natural vegetation from the native GCM datasets combined with human land cover information from other sources are best for simulating such impacts. We also performed a prehuman simulation, which had a 0.39 K ~higher average global temperature and, perhaps of greater importance, temperature changes regionally of about 2 K. In this study, the larger regional changes coincide with large-scale agricultural areas. The initial cooling from energy balance changes appear to create feedbacks that intensify mid-latitude circulation features and weaken the summer monsoon circulation over Asia, leading to further cooling. From these results, we conclude that land cover change plays a significant role in anthropogenically forced climate change. Because these changes coincide with regions of the highest human population this climate impact could have a disproportionate impact on human systems. Therefore, it is important that land cover change be included in past and future climate change simulations.     

Effects of Land Use on the Climate of the United States

Land use practices have replaced much of the natural needleleaf evergreen, broadleaf deciduous, and mixed forests of the Eastern United States with crops. To a lesser extent, the natural grasslands in the Central United States have also been replaced with crops. Simulations with a land surface process model coupled to an atmospheric general circulation model show that the climate of the United States with modern vegetation is significantly different from that with natural vegetation. Three important climate signals caused by modern vegetation are: (1) 1 °C cooling over the Eastern United States and 1 °C warming over the Western United States in spring; (2) summer cooling of up to 2 °C over a wide region of the Central United States; and (3) moistening of the near-surface atmosphere by 0.5 to 1.5 g kg^-1over much of the United States in spring and summer. Although individual months show large, statistically significant differences in precipitation due to land-use practices, these differences average out over the course of the 3-month seasons. These changes in surface temperature and moisture extend well into the atmosphere, up to 500 mb, and affect the boundary layer and atmospheric circulation. The altered climate is due to reduced surface roughness, reduced leaf and stem area index, reduced stomatal resistance, and increased surface albedo with modern vegetation compared to natural vegetation. The climate change caused by land use practices is comparable to other well known anthropogenic climate forcings. For example, it would take 100 to 175 years at the current, observed rate of summer warming over the United States to offset the cooling from deforestation. The summer sulfate aerosol forcing completely offsets the greenhouse forcing over the Eastern United States. Similarly, the climatic effect of North American deforestation, with extensive summer cooling, further offsets the greenhouse forcing.     

Detection of anthropogenic climate change using an atmospheric GCM

 Atmosphere-only general circulation models are shown to be a useful tool for detecting an anthropogenic effect on climate and understanding recent climate change. Ensembles of atmospheric runs are all forced with the same observed changes in sea surface temperatures and sea-ice extents but differ in terms of the combinations of anthropogenic effects included. Therefore, our approach aims to detect the `immediate' anthropogenic impact on the atmosphere as opposed to that which has arisen via oceanic feedbacks. We have adapted two well-used detection techniques, pattern correlations and fingerprints, and both show that near-decadal changes in the patterns of zonal mean upper air temperature are well simulated, and that it is highly unlikely that the observed changes could be accounted for by sea surface temperature variations and internal variability alone. Furthermore, we show that for zonally averaged upper air temperature, internal `noise' in the atmospheric model is small enough that a signal emerges from the data even on interannual time scales; this would not be possible in a coupled ocean-atmosphere general circulation model. Finally, although anthropogenic forcings have had a significant impact on global mean land surface temperature, we find that their influence on the pattern of local deviations about this mean is so far undetectable. In order to achieve this in the future, as the signal grows, it will also be important that the response of the Northern Hemisphere mid-latitude westerly flow to changing sea surface temperatures is well simulated in climate model detection studies. Received: 3 December 1999 / Accepted: 30 October 2000     

The impact of land cover change on the atmospheric circulation

 The NCAR Community Climate Model (version 3), coupled to the Biosphere Atmosphere Transfer scheme and a mixed layer ocean model is used to investigate the impact on the climate of a conservative change from natural to present land cover. Natural vegetation cover was obtained from an ecophysiologically constrained biome model. The current vegetation cover was obtained by perturbing the natural cover from forest to grass over areas where land cover has been observed to change. Simulations were performed for 17 years for each case (results from the last 15 years are presented here). We find that land cover changes, largely constrained to the tropics, SE Asia, North America and Europe, cause statistically significant changes in regional temperature and precipitation but cause no impact on the globally averaged temperature or precipitation. The perturbation in land cover in the tropics and SE Asia teleconnect to higher latitudes by changing the position and strength of key elements of the general circulation (the Hadley and Walker circulations). Many of the areas where statistically significant changes occur are remote from the location of land cover change. Historical land cover change is not typically included in transitory climate simulations, and it may be that the simulation of the patterns of temperature change over the twentieth century by climate models will be further improved by taking it into account. Received: 27 May 1999 / Accepted: July 2000     

The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

Summary A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO₂ is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO₂ was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO₂ contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO₂ and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.     

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

土地利用变化对气候影响的研究进展

为满足人类对食物、纤维、水和居住地的需求,全球土地利用格局发生了巨大的变化,IPCC 第四次评估报告（IPCC,2007）指出土地利用变化是人类影响气候的重要强迫之一。土地利用变化对气候的影响分为生物地球物理作用和生物地球化学作用。分别对有关生物地球物理作用和生物地球化学作用的研究进展以及研究热点进行了综述;并从定量评估两者对气候影响的相对贡献以及两者共同效应的角度,回顾了辐射强迫计算和耦合模式数值模拟两种方法的研究进展,及其在森林恢复、人工造林以及碳封存等气候变化应对措施可行性评估中的应用。最后分析和展望了当前土地利用变化对气候影响相关研究中的不确定性以及未来发展方向。     

Climate simulations for 1880–2003 with GISS modelE

We carry out climate simulations for 1880–2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880–2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The role of land surface dynamics in glacial inception: a study with the UVic Earth System Model

The first results of the UVic Earth System Model coupled to a land surface scheme and a dynamic global vegetation model are presented in this study. In the first part the present day climate simulation is discussed and compared to observations. We then compare a simulation of an ice age inception (forced with 116 ka BP orbital parameters and an atmospheric CO₂ concentration of 240 ppm) with a preindustrial run (present day orbital parameters, atmospheric [CO₂] = 280 ppm). Emphasis is placed on the vegetations response to the combined changes in solar radiation and atmospheric CO₂ level. A southward shift of the northern treeline as well as a global decrease in vegetation carbon is observed in the ice age inception run. In tropical regions, up to 88% of broadleaf trees are replaced by shrubs and C₄ grasses. These changes in vegetation cover have a remarkable effect on the global climate: land related feedbacks double the atmospheric cooling during the ice age inception as well as the reduction of the meridional overturning in the North Atlantic. The introduction of vegetation related feedbacks also increases the surface area with perennial snow significantly.     

Potential effects of climate change on a semi-permanent prairie wetland

We assessed the potential effects of a greenhouse gas-induced global climate change on the hydrology and vegetation of a semi-permanent prairie wetland using a spatially-defined, rule-based simulation model. An 11-yr simulation was run using current versus enhanced greenhouse gas climates. Projections of climatic change were from the Goddard Institute for Space Studies (GISS) general circulation model. Simulations were also run using a range of temperature (+2 and +4 °C) and precipitation change values (–20, –10, 0, +10, +20%) to determine the responsiveness of wetland vegetation and hydrology to a variety of climate scenarios.Maximum water depths were significantly less under the enhanced greenhouse gas scenario than under the current climate. The wetland dried in most years with increased temperature and changes in precipitation. Simulations also revealed a significant change in the vegetation, from a nearly balanced emergent cover to open water ratio to a completely closed basin with no open water areas. Simulations over a range of climate change scenarios showed that precipitation changes (particularly increases) had a greater impact on water levels and cover ratios when the temperature increase was moderate (+2 °C).These potential changes in wetland hydrology and vegetation could result in a dramatic decline in the quality of habitat for breeding birds, particularly waterfowl. Continued research on climate and wetland modeling is needed.     

Climate change under aggressive mitigation: the ENSEMBLES multi-model experiment

We present results from multiple comprehensive models used to simulate an aggressive mitigation scenario based on detailed results of an Integrated Assessment Model. The experiment employs ten global climate and Earth System models (GCMs and ESMs) and pioneers elements of the long-term experimental design for the forthcoming 5th Intergovernmental Panel on Climate Change assessment. Atmospheric carbon-dioxide concentrations pathways rather than carbon emissions are specified in all models, including five ESMs that contain interactive carbon cycles. Specified forcings also include minor greenhouse gas concentration pathways, ozone concentration, aerosols (via concentrations or precursor emissions) and land use change (in five models). The new aggressive mitigation scenario (E1), constructed using an integrated assessment model (IMAGE?2.4) with reduced fossil fuel use for energy production aimed at stabilizing global warming below 2?K, is studied alongside the medium-high non-mitigation scenario SRES A1B. Resulting twenty-first century global mean warming and precipitation changes for A1B are broadly consistent with previous studies. In E1 twenty-first century global warming remains below 2?K in most models, but global mean precipitation changes are higher than in A1B up to 2065 and consistently higher per degree of warming. The spread in global temperature and precipitation responses is partly attributable to inter-model variations in aerosol loading and representations of aerosol-related radiative forcing effects. Our study illustrates that the benefits of mitigation will not be realised in temperature terms until several decades after emissions reductions begin, and may vary considerably between regions. A subset of the models containing integrated carbon cycles agree that land and ocean sinks remove roughly half of present day anthropogenic carbon emissions from the atmosphere, and that anthropogenic carbon emissions must decrease by at least 50% by 2050 relative to 1990, with further large reductions needed beyond that to achieve the E1 concentrations pathway. Negative allowable anthropogenic carbon emissions at and beyond 2100 cannot be ruled out for the E1 scenario. There is self-consistency between the multi-model ensemble of allowable anthropogenic carbon emissions and the E1 scenario emissions from IMAGE?2.4.     

Process, Forcing, and Signal Analysis of Global Mean TemperatureVariations by Means of a Three-Box Energy Balance Model

An analytic solution of an energy balance model (EBM) is presented which can beused as a recursive filter for time series analysis. It is shown that the EBM can reproduce the solution of a coupled atmosphere-ocean general circulation model (AOGCM) experiment. Contrary to the AOGCM, the EBM easily allows for variations in climate sensitivity to satisfy the full range of uncertainty concerned with this parameter. The recursive filter is applied to two natural and two anthropogenic forcing mechanisms which are expressed in terms of heating rate anomaly time series: volcanism, solar activity, greenhouse gases (GHG), and anthropogenic tropospheric aerosols. Thus, we obtain modelled global mean temperature variations as a response to the different forcings and with respect to the uncertainty in the forcing approximations and climate sensitivity. In addition, it is shown that the observed (ENSO-corrected) global mean temperature time series within the period from 1866 to 1997 can be explained by the external forcings which have been considered and an additional white noise forcing. In this way we are able to separate different signals and compare them. As a result, global anthropogenic climate change due to GHG forcing can be detected at a high level of significance without considering spatial patterns of climate change but including natural forcing, which is usually not done. Furthermore, it is shown that solar forcing alone does not lead to significantclimate change, whereas solar and volcanic forcing together lead to a significant natural climate change signal. Anthropogenic climate change due to GHG forcing may partly be masked by anthropogenic aerosol cooling.     

Developing climate change scenarios for Tamil Nadu, India using MAGICC/SCENGEN

This paper describes the projection of climate change scenarios under increased greenhouse gas emissions, using the results of atmospheric-ocean general circulation models in the Coupled Model Intercomparison Project phase 3 dataset. A score is given to every model based on global and regional performance. Four out of 20 general circulation models (GCMs) were selected based on skill in predicting observed annual temperature and precipitation conditions. The ensemble of these four models shows superiority over the individual model scores. These models were subjected to increases in future anthropogenic radiative forcings for constructing climate change scenarios. Future climate scenarios for Tamil Nadu were developed with MAGICC/SCENGEN software. Model results show both temperature and precipitation increases under increased greenhouse gas scenarios. Northeast and northwest parts of Tamil Nadu show a greater increase in temperature and precipitation. Seasonally, the maximum rise in temperature occurred during the MAM season, followed by DJF, JJA, and SON. Decreasing trends of precipitation were observed during DJF and MAM.     

Biogeophysical effects of historical land cover changes simulated by six Earth system models of intermediate complexity

Six Earth system models of intermediate complexity that are able to simulate interaction between atmosphere, ocean, and land surface, were forced with a scenario of land cover changes during the last millennium. In response to historical deforestation of about 18 million sq km, the models simulate a decrease in global mean annual temperature in the range of 0.13–0.25°C. The rate of this cooling accelerated during the 19th century, reached a maximum in the first half of the 20th century, and declined at the end of the 20th century. This trend is explained by temporal and spatial dynamics of land cover changes, as the effect of deforestation on temperature is less pronounced for tropical than for temperate regions, and reforestation in the northern temperate areas during the second part of the 20th century partly offset the cooling trend. In most of the models, land cover changes lead to a decline in annual land evapotranspiration, while seasonal changes are rather equivocal because of spatial shifts in convergence zones. In the future, reforestation might be chosen as an option for the enhancement of terrestrial carbon sequestration. Our study indicates that biogeophysical mechanisms need to be accounted for in the assessment of land management options for climate change mitigation.     

CO2 threshold for millennial-scale oscillations in the climate system: implications for global warming scenarios

We present several equilibrium runs under varying atmospheric CO₂ concentrations using the University of Victoria Earth System Climate Model (UVic ESCM). The model shows two very different responses: for CO₂ concentrations of 400 ppm or lower, the system evolves into an equilibrium state. For CO₂ concentrations of 440 ppm or higher, the system starts oscillating between a state with vigorous deep water formation in the Southern Ocean and a state with no deep water formation in the Southern Ocean. The flushing events result in a rapid increase in atmospheric temperatures, degassing of CO₂ and therefore an increase in atmospheric CO₂ concentrations, and a reduction of sea ice cover in the Southern Ocean. They also cool the deep ocean worldwide. After the flush, the deep ocean warms slowly again and CO₂ is taken up by the ocean until the stratification becomes unstable again at high latitudes thousands of years later. The existence of a threshold in CO₂ concentration which places the UVic ESCM in either an oscillating or non-oscillating state makes our results intriguing. If the UVic ESCM captures a mechanism that is present and important in the real climate system, the consequences would comprise a rapid increase in atmospheric carbon dioxide concentrations of several tens of ppm, an increase in global surface temperature of the order of 1–2°C, local temperature changes of the order of 6°C and a profound change in ocean stratification, deep water temperature and sea ice cover.