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The discrepancy between simulated and observed globally averaged monthly atmospheric concentrations of carbon dioxide could be attributed either to deficiencies in the observation network or to inadequacies in the global carbon cycle models. This paper shows that model results could be brought closer to observations by improving model components that describe the seasonal changes in the storage of quickly decaying fractions of litter. [ABSTRACT FROM AUTHOR]

The article focuses on the metrics used for comparing greenhouse gases with focus on the Integrated Temperature Change Potential (IGTP). It states that the IGTP and global warming potentials (GWP) are asymptotically equal is the time horizon reaches infinity. It says that the IGTP is equal to the Sustained Global Temperature change Potential (SGTP) under standard assumptions when calculating GWPs.

The article presents information on a study conducted on a 500 year model simulation of the mid-Pliocene Warm Period (mPWP) by using the Community Climate System Model, version 4 (CCSM4). Results from the CCSM4 mPWP simulation showed a 1.9 Degrees Centigrade increase in global mean annual temperature, along with a polar amplification of nearly three times the global warming.

In recent years, research on climate change and human security has received much attention among policy makers and academia alike. Communities in the Global South that rely on an intact resource base will especially be affected by predicted changes in temperature and precipitation. The objective of this article is to better understand under what conditions local communities can adapt to anticipated impacts of climate change and avoid conflict over the loss of resources. The empirical part of the paper answers the question to what extent local communities in the Chilwa Basin in Malawi have experienced climate change and how they are affected by it. Further, it assesses one of Malawi's adaptation projects designed to build resilience to a warmer and more variable climate, and points to some of its limitations. This research shows that not all adaptation strategies are suited to cope with a warmer and more variable climate. [ABSTRACT FROM AUTHOR]

The article discusses the interpretation and definition of quantities relating to climate sensitivity in the discussions paper "Climate sensitivity in the Anthropocene," by M. Previdi and colleagues. It states that the paper brought several errors and inconsistencies in the discussion of climate sensitivity. It says that definition of temperature which denoted surface temperature was inconsistent.

Given the potential for elements of the Earth system to undergo rapid, hard to reverse changes in state, there is a pressing need to establish robust methods to produce early warning signals of such events. Here we present a conceptual ecosystem model in which a diversity of stable states emerge, along with rapid changes, referred to as critical transitions, as a consequence of external driving and non-linear ecological dynamics. We are able to produce robust early warning signals that precede critical transitions. However, we show that there is no correlation between the magnitude of the signal and magnitude or reversibility of any individual critical transition. We discuss these findings in the context of ecosystem management prior to and post critical transitions. We argue that an understanding of the dynamics of the systems is necessary both for management prior and post critical transitions and the effective interpretation of any early warning signal that may be produced for that system. [ABSTRACT FROM AUTHOR]

Robust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. Currently, two such levels are discussed in the context of the international climate negotiations as long-term global temperature goals: a below 2 °C and a 1.5 °C limit in global-mean temperature rise above pre-industrial levels. Despite the prominence of these two temperature limits, a comprehensive assessment of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5 °C and 2 °C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between 1.5 °C and 2 °C. For heat-related extremes, the additional 0.5 °C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2 °C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature induced bleaching from 2050 onwards. This fraction is reduced to about 90 % in 2050 and projected to decline to 70 % by 2100 for a 1.5 °C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and several hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9 to 17 % between 1.5 °C and 2 °C, and the projected lengthening of regional dry spells increases from 7 % longer to 11 %. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and Northern South America are projected to face local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50 cm rise by 2100 relative to year 2000-levels under a 2 °C warming, which is about 10 cm lower for a 1.5 °C scenario. Our findings highlight the importance of regional differentiation to assess future climate risks as well as different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a solid foundation for future work on refining our understanding of warming-level dependent climate impacts. [ABSTRACT FROM AUTHOR]

We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation of the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various time scales is discussed. [ABSTRACT FROM AUTHOR]

The article discusses a study conducted to compare three types of data sets with the Coupled Model Intercomparison Project (CMIP5) climate model simulations to understand similarities or differences between temperature trends in CMIP5 simulations with those from the radiosonde observations, reanalyses and CMIP3 climate simulations. It is stated that data sets are compared between the stratosphere and troposphere as well as between the tropics, Arctic and Antarctic.

Terrestrial ecosystems of northern Eurasia are greening, yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness and forest fires contribute to the trend in Gross Primary Productivity (GPP) derived from satellite data across northern Eurasia. For the period 1982-2008 we find that GPP, estimated using ensemble satellite NDVI (Normalized Difference Vegetation Index) observations from GIMMS3g and VIP datasets, is most sensitive to temperature, precipitation and cloudiness during summer, the peak of the growing season. For regional median GPP, summer temperature explains 33.3% of the variation in GPP, while the other environmental variables explain from 2.2 to 11.8 %. Warming over the period analyzed, even without a sustained increase in precipitation, led to a significant GPP increase over 67.3% of the region. A significant decrease in GPP was found over 6.2% of the region, primarily the dryer grasslands in the south-western. For this area, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. Our results further advance the notion that air temperature is the dominant environmental control for the recent GPP increases across northern Eurasia. [ABSTRACT FROM AUTHOR]

Earth's climate exhibits internal modes of variability on various time scales. Here we investigate multi-decadal variability of the Atlantic meridional overturning circulation (AMOC) in the control runs of an ensemble of CMIP5 models. By decomposing global- mean-temperature (GMT) variance into contributions of the AMOC and Northern Hemisphere sea-ice extent using a graph-theoretical statistical approach, we find the AMOC to contribute 8% to GMT variability in the ensemble mean. Our results highlight the importance of AMOC sea-ice feedbacks that explain 5% of the GMT variance, while the contribution solely related to the AMOC is found to be about 3 %. As a consequence of multi-decadal AMOC variability, we report substantial variations in North Atlantic deepocean heat content with trends of up to 0.7×1022 J decade-1 that are of the order of observed changes over the last decade and consistent with the reduced GMT warming trend over this period. Although these temperature anomalies are largely density-compensated by salinity changes, we find a robust negative correlation between the AMOC and North Atlantic deep-ocean density with density lagging the AMOC by 5 to 11 yr in most models. While this would in principle allow for a self-sustained oscillatory behavior of the coupled AMOC-deep-ocean system, our results are inconclusive about the role of this feedback in the model ensemble. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is the largest store of organic carbon (C) in the biosphere, but still the turnover of SOM is incompletely understood and not well described in global C cycle models. Here we use the Community Land Model (CLM) and compare the out- put for soil organic C (SOC) to estimates from a global data set. We also modify the assumptions about SOM turnover in two ways: (1) we assume distinct temperature sensitivities of SOC pools with different turnover time and (2) we assume a priming effect, such that decomposition rate of native SOM increases in response to a supply of fresh organic matter. The standard model predicted the global distribution of SOM reasonably well in most areas, but it failed to predict the very high stocks of SOM at high latitudes. It also predicted somewhat too much SOC in areas with high plant productivity, such as tropical rain forests and some mid-latitude areas. Assuming that the temperature sensitivity of SOC decomposition is dependent on the turnover rate of component pools reduced total SOC at equilibrium by a relatively small amount (<1% globally). Including a priming effect reduced total global SOC more (6.6% globally) and tended to decrease SOC most in areas with high plant input (tropical and temperate forests), which were also the areas where the unmodified model overpredicted SOC (by about 40 %). The model was then run with climate change prediction for the standard and modified versions. Future simulations showed that differences between the standard and modified versions were maintained in a future with climate change (4-6 and 23-47 Pg difference in soil carbon between standard simulation and the modified with temperature sensitivity and priming respectively). [ABSTRACT FROM AUTHOR]

The article presents a study which focuses on the use of polar-focused approach to solar radiation management (SRM) to limit the pace of climatic changes in high latitudes. The study used the CAM3.1 atmospheric model coupled to a slab ocean from the National Center for Atmospheric Research. The study shows that green house gas emission is sufficient to limit the warming influence of greenhouse gas concentrations and polar reductions in solar radiation.

Phenology is experiencing dramatic changes over deciduous forests in the US. Estimates of trends in phenology on the continental scale are uncertain, however, with studies failing to agree on both the magnitude and spatial distribution of trends in spring and autumn. This is due to the sparsity of in situ records, uncertainties associated with remote sensing data, and the regional focus of many studies. It has been suggested that reported trends are a result of recent temperature changes, though multiple processes are thought to be involved and the nature of the temperature forcing remains unknown. To date, no study has directly attributed long-term phenological trends to individual forcings across the US through integrating observations with models. Here, we construct an extensive database of ground measurements of phenological events across the US, and use it to calibrate and evaluate a suite of phenology models. The models use variations of the accumulative temperature summation, with additional chilling requirements for spring phenology and photoperiod limitation for autumn. Including a chilling requirement or photoperiod limitation does not improve model performance, suggesting that temperature change, especially in spring and autumn, is the dominant driver of the observed trend during the past 3 decades. Our results show that phenological trends are not uniform over the contiguous US, with a significant advance of 0.34 day yr-1 for the spring budburst in the East, a delay of 0.15 day yr-1 for the autumn dormancy onset in the Northeast and West, but no evidence of change elsewhere. Relative to the 1980s, the growing season in the 2000s is extended by about 1 week (3-4%) in the East, New England, and the upper Rocky Mountains forests. These results help reconcile conflicting reports of phenological trends in the literature, and directly attribute observed trends to long-term changes in temperature. [ABSTRACT FROM AUTHOR]

The article presents a newly composed dataset of climate change scenario to pacify requirements for global assessments of climate change impacts. It is evident that global mean temperature change has become the yardstick to gauze impact of unavoidable climate change and requirement of adaptation. It is informed that the dataset helps in analyzing impact of climate change and implement climate model.

The article discusses a research study which evaluates a climate simulation through the Global Environmental and Ecological Simulation of Interactive Systems and Modular Ocean Model version 2 (GENMOM). Findings reveal that the said model developed a global temperature bias of 0.6 degree-Celsius. It indicates the development of a split intertropical convergence zone (ITCZ) and weaker-than-observed overturning circulation as the two main weaknesses depicted in the simulations.

Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedback to elevated atmospheric carbon dioxide (CO2) in the warmer future world. We examined seven biome models with climate projections forced by four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify uncertainty in global SOC stock projections from global and regional perspectives. Our simulations showed that SOC stocks among the biome models varied from 1090 to 2650 PgC even in historical periods (ca. 2000). In a higher forcing scenario (RCP8.5), inconsistent estimates of impact on the total SOC (2099-2000) were obtained from different model simulations, ranging from a net sink of 347 PgC to a net source of 122 PgC. In all models, the elevated atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 PgC by the end of the 21st century. Using time-series data of total global SOC estimated by biome biome model, we statistically analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (▵ T and ▵ P respectively) in each biome model using a state-space model. This analysis suggests that ▵ T explained global SOC stock changes in most models with a resolution of 1-2° C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 PgCyr-1 to 3.53 PgCyr-1 among the biome models. On the other hand, ▵ P had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the changes in SOC estimated by the biome models, especially in boreal to arctic regions. Our study revealed considerable climate change impact uncertainty in SOC decomposition among biome models. Further research is required to improve our understanding and ability to estimate biospheric feedback through SOC-relevant processes as well as vegetation processes. [ABSTRACT FROM AUTHOR]

The article presents a study which compares the changes in global mean temperature obtained from emission driven Global Climate Model (GCM) in response to various future scenarios. It states GCM simulations models uncertainties in atmospheric feedbacks, ocean physics, and land carbon cycle and aerosol sulphur cycles. It suggests that uncertainty sampling from the emission leads to a wide range of atmospheric concentrations and results of changes in temperature.

Several studies have connected emissions of greenhouse gases to economic and trade data to quantify the causal chain from consumption to emissions and climate change. These studies usually combine data and models originating from different sources, making it difficult to estimate uncertainties in the end results. We estimate uncertainties in economic data, multi-pollutant emission statistics and metric parameters, and use Monte Carlo analysis to quantify contributions to uncertainty and to determine how uncertainty propagates to estimates of global temperature change from regional and sectoral territorial- and consumption-based emissions for the year 2007. We find that the uncertainties are sensitive to the emission allocations, mix of pollutants included, the metric and its time horizon, and the level of aggregation of the results. Uncertainties in the final results are largely dominated by the climate sensitivity and the parameters associated with the warming effects of CO2. The economic data have a relatively small impact on uncertainty at the global and national level, while much higher uncertainties are found at the sectoral level. Our results suggest that consumption-based national emissions are not significantly more uncertain than the corresponding production based emissions, since the largest uncertainties are due to metric and emissions which affect both perspectives equally. The two perspectives exhibit different sectoral uncertainties, due to changes of pollutant compositions. We find global sectoral consumption uncertainties in the range of ±9-±27% using the global temperature potential with a 50 year time horizon, with metric uncertainties dominating. National level uncertainties are similar in both perspectives due to the dominance of CO2 over other pollutants. The consumption emissions of the top 10 emitting regions have a broad uncertainty range of ±9-±25 %, with metric and emissions uncertainties contributing similarly. The Absolute global temperature potential with a 50 year time horizon has much higher uncertainties, with considerable uncertainty overlap for regions and sectors, indicating that the ranking of countries is uncertain. [ABSTRACT FROM AUTHOR]

The article discusses a study on geologic constraints on Earth system sensitivity (ESS) to carbon dioxide during the Cretaceous and early Paleogene periods. It mentions that the sensitivity has climate policy implications due to anticipated decline of global temperature despite of decrease in anthropogenic greenhouse-gas emissions. It also notes its estimates of 3° Celsius on both periods based on paleo-reconstructions of the gas and temperature.

This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea ice, and land. Due to its high equilibrium climate sensitivity (ECS of 5.3 K), E3SMv1.0 is one of the Coupled Model Intercomparison Project phase 6 (CMIP6) models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated with the global temperature change, while the spatial pattern of the change in runoff is consistent with the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The annual mean Atlantic meridional overturning circulation (AMOC) is overly weak with a slower change from ∼11 to ∼6 Sv (Sverdrup) relative to other CMIP6 models. The sea ice, especially in the Northern Hemisphere, decreases rapidly with large seasonal variability. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes transient accelerated warming in the all-forcing experiment in the first half of the 21st century. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions, e.g., southern North America, southern Africa, central Africa, and eastern Asia. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period. [ABSTRACT FROM AUTHOR]

Theory indicates that tropical cyclone (TC) intensity should respond to environmental temperature changes near the surface and in the TC outflow layer. While the sensitivity of TC intensity to sea surface temperature is well understood, less is known about the role of upper-level stratification. In this paper, we combine historical data analysis and idealised modelling to explore the extent to which historical low-level warming and upper-level stratification can explain observed trends in the TC intensity distribution. Observations and modelling agree that historical global environmental temperature changes coincide with higher lifetime maximum intensities. Observations suggest the response depends on the TC intensity itself. Hurricane-strength storms have intensified at twice the rate of weaker storms per unit surface and upper-tropospheric warming, and we find faster warming of low-level temperatures in hurricane environments than the tropical mean. Idealised simulations respond in the expected sense to various imposed changes in the near-surface temperature and upper-level stratification representing present-day and end-of-century thermal profiles and agree with TCs operating as heat engines. Removing upper-tropospheric warming or stratospheric cooling from end-of-century experiments results in much smaller changes in potential intensity or realised intensity than between present day and the end of the century. A larger proportional change in thermodynamic disequilibrium compared to thermodynamic efficiency in our simulations suggests that disequilibrium, not efficiency, is responsible for much of the intensity increase from present day to the end of the century. The limited change in efficiency is attributable to nearly constant outflow temperature in the simulated TCs among the experiments. Observed sensitivities are generally larger than modelled sensitivities, suggesting that observed TC intensity change responds to a combination of the temperature change and other environmental factors. [ABSTRACT FROM AUTHOR]

Extreme maximum temperatures during Australian spring can have deleterious impacts on a range of sectors from health to wine grapes to planning for wildfires but are studied relatively little compared to spring rainfall. Spring maximum temperatures in Australia have been rising over recent decades, and it is important to understand how Australian spring maximum temperatures develop in the present and warming climate. Australia's climate is influenced by variability in the tropics and extratropics, but some of this influence impacts Australia differently from winter to summer and, consequently, may have different impacts on Australia as spring evolves. Using linear regression analysis, this paper explores the atmospheric dynamics and remote drivers of high maximum temperatures over the individual months of spring. We find that the drivers of early spring maximum temperatures in Australia are more closely related to low-level wind changes, which in turn are more related to the Southern Annular Mode than variability in the tropics. By late spring, Australia's maximum temperatures are proportionally more related to warming through subsidence than low-level wind changes and more closely related to tropical variability. This increased relationship with the tropical variability is linked with the breakdown of the subtropical jet through spring and an associated change in tropically forced Rossby wave teleconnections. An improved understanding of how the extratropics and tropics project onto the mechanisms that drive high maximum temperatures through spring may lead to improved sub-seasonal prediction of high temperatures in the future. [ABSTRACT FROM AUTHOR]

The article presents comments on the article "Joint Effect of the Western and Eastern Pacific Warm Pools on El Nino-Southern Oscillation (ENSO) Cycle." It notes that the authors have used a very long datasets and have made a number of points about the changes in climatology over the period, however, the sources of data failed to discuss the changes on temperatures. It also observes that the data has assumed the value of the expansion and contraction of the warm pools and has confused the correlation between the cause and effect.

In this paper, we show that the projected global temperature change from CMIP5 models is remarkably similar to that obtained using simple regression models relating the global temperature to the atmospheric concentrations of CO2. This result is strengthened when we consider the projections obtained using the CMIP6 models. [ABSTRACT FROM AUTHOR]

The use of different primary energy sources in human society has led to two major polluting emissions in the environment: energy (mostly heat), and chemical substances (mostly carbon dioxide). In this paper, a new approach, based on the similarity between sensible heat and CO2 transfer properties, was used to determine the effect of anthropogenic heat release on the global air temperature. The total global anthropogenic emissions of sensible heat were divided into two separate streams: directly transferred to: (1) water and land, and (2) to the atmosphere. The direct emissions of heat to the atmosphere during the industrial era (years 1850-2018) were determined and their effect on the change of global atmospheric temperature was calculated. The global atmospheric temperature increase caused by anthropogenic heat emissions was estimated. The resulting calculations showed that at least half of the actual atmospheric temperature rise recorded during the last 170-year period, was due to the anthropogenic heat release. These results suggest that the temperature change of the atmosphere (global warming) is strongly affected by anthropogenic heat emissions. [ABSTRACT FROM AUTHOR]

This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea-ice, and land. Due to its high climate sensitivity, E3SMv1.0 is one of the CMIP6 models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated to the global temperature change, while the spatial pattern of the change in runoff responds to the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The sea ice, especially in the Northern Hemisphere, rapidly decreases with large seasonal variability. The annual mean AMOC is overly weak with a slower change relative to other CMIP6 models. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes accelerated warming in SSP5-8.5 all-forcing experiment. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period. [ABSTRACT FROM AUTHOR]

The Great Plains of North America host a stark climatic gradient, separating the humid and well-watered eastern US from the semi-arid and arid western US, and this gradient shapes the region's water availability, its ecosystems, and its economies. This climatic boundary is largely set by the influence of two competing atmospheric circulation systems that meet over the Great Plains – the wintertime westerlies bring dominantly dry air that gives way to moist, southerly air transported by the Great Plains low-level jet in the warmer months. Climate model simulations suggest that, as CO 2 rises, this low-level jet will strengthen, leading to greater precipitation in the spring but less in the summer and, thus, no change in mean annual precipitation. Combined with rising temperatures that will increase potential evapotranspiration, semi-arid conditions will shift eastward, with potentially large consequences for the ecosystems and inhabitants of the Great Plains. We examine how hydroclimate in the Great Plains varied in the past in response to warmer global climate by studying the paleoclimate record within the Ogallala Formation, which underlies nearly the entire Great Plains and provides a spatially resolved record of hydroclimate during the globally warmer late Miocene. We use the stable isotopes of oxygen (δ18 O) as preserved in authigenic carbonates hosted within the abundant paleosol and fluvial successions that comprise the Ogallala Formation as a record of past hydroclimate. Today, and coincident with the modern aridity gradient, there is a sharp meteoric water δ18 O gradient with high (-6 ‰ to 0 ‰) δ18 O in the southern Great Plains and low (-12 ‰ to -18 ‰) δ18 O in the northern plains. We find that the spatial pattern of reconstructed late Miocene precipitation δ18 O is indistinguishable from the spatial pattern of modern meteoric water δ18 O. We use a recently developed vapor transport model to demonstrate that this δ18 O spatial pattern requires air mass mixing over the Great Plains between dry westerly and moist southerly air masses in the late Miocene – consistent with today. Our results suggest that the spatial extents of these two atmospheric circulation systems have been largely unchanged since the late Miocene and any strengthening of the Great Plains low-level jet in response to warming has been isotopically masked by proportional increases in westerly moisture delivery. Our results hold implications for the sensitivity of Great Plains climate to changes in global temperature and CO 2 and also for our understanding of the processes that drove Ogallala Formation deposition in the late Miocene. [ABSTRACT FROM AUTHOR]

The Fennoscandian boreal and mountain regions harbour a wide range of vegetation types, from boreal forest to high alpine tundra and barren soils. The area is facing a rise in air temperature above the global average and changes in temperature and precipitation patterns. This is expected to alter the Fennoscandian vegetation composition and change the conditions for areal land use such as forestry, tourism and reindeer husbandry. In this study we used a unique high-resolution (3 km) climate scenario with considerable warming resulting from strongly increasing carbon dioxide emissions to investigate how climate change can alter the vegetation composition, biodiversity and availability of suitable reindeer forage. Using a dynamical vegetation model, including a new implementation of potential reindeer grazing, resulted in simulated vegetation maps of unprecedented high resolution for such a long time period and spatial extent. The results were evaluated at the local scale using vegetation inventories and for the whole area against satellite-based vegetation maps. A deeper analysis of vegetation shifts related to statistics of threatened species was performed in six "hotspot" areas containing records of rare and threatened species. In this high-emission scenario, the simulations show dramatic shifts in the vegetation composition, accelerating at the end of the century. Alarmingly, the results suggest the southern mountain alpine region in Sweden will be completely covered by forests at the end of the 21st century, making preservation of many rare and threatened species impossible. In the northern alpine regions, most vegetation types will persist but shift to higher elevations with reduced areal extent, endangering vulnerable species. Simulated potential for reindeer grazing indicates latitudinal differences, with higher potential in the south in the current climate. In the future these differences will diminish, as the potentials will increase in the north, especially for the summer grazing grounds. These combined results suggest significant shifts in vegetation composition over the present century for this scenario, with large implications for nature conservation, reindeer husbandry and forestry. [ABSTRACT FROM AUTHOR]

Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability. [ABSTRACT FROM AUTHOR]

A key issue of climate change is to identify the forcings and their relative contributions. The solar-climate relationship is currently the matter of a fierce debate. We address here the need for high quality observations and an adequate statistical approach. A recent work by Le Mouël et al. (2010) and its companion paper by Kossobokov et al. (2010) show spectacular correlations between solar activity and temperature series from three European weather stations over the last two centuries. We question both the data and the method used in these works. We stress (1) that correlation with solar forcing alone is meaningless unless other forcings are properly accounted for and that sunspot counting is a poor indicator of solar irradiance, (2) that long temperature series require homogenization to remove historical artefacts that affect long term variability, (3) that incorrect application of statistical tests leads to interpret as significant a signal which arises from pure random fluctuations. As a consequence, we reject the results and the conclusions of Le Mouël et al. (2010) and Kossobokov et al. (2010). We believe that our contribution bears some general interest in removing confusion from the scientific debate. [ABSTRACT FROM AUTHOR]

Since the upper ocean takes up much of the heat added to the earth system by anthropogenic global warming, one would expect that global warming would lead to an increase in stratification and a decrease in the ventilation of the ocean interior. However, multiple simulations in global coupled climate models using an ideal age tracer which is set to zero in the mixed layer and ages at 1 yr/yr outside this layer show that the intermediate depths in the low latitudes become younger under global warming. This paper reconciles these apparently contradictory trends, showing that a decrease in upwelling of old water from below is responsible for the change. Implications for global biological cycling are considered. [ABSTRACT FROM AUTHOR]

This paper summarizes the formulation of the ocean component to the Geophysical Fluid Dynamics Laboratory's (GFDL) coupled climate model used for the 4th IPCC Assessment (AR4) of global climate change. In particular, it reviews elements of ocean climate models and how they are pieced together for use in a state-of-the-art coupled model. Novel issues are also highlighted, with particular attention given to sensitivity of the coupled simulation to physical parameterizations and numerical methods. Features of the model described here include the following: (1) tripolar grid to resolve the Arctic Ocean without polar filtering, (2) partial bottom step representation of topography to better represent topographically influenced advective and wave processes, (3) more accurate equation of state, (4) three-dimensional flux limited tracer advection to reduce overshoots and undershoots, (5) incorporation of regional climatological variability in shortwave penetration, (6) neutral physics parameterization for representation of the pathways of tracer transport, (7) staggered time stepping for tracer conservation and numerical efficiency, (8) anisotropic horizontal viscosities for representation of equatorial currents, (9) parameterization of exchange with marginal seas, (10) incorporation of a free surface that accomodates a dynamic ice model and wave propagation, (11) transport of water across the ocean free surface to eliminate unphysical "virtual tracer flux" methods, (12) parameterization of tidal mixing on continental shelves. [ABSTRACT FROM AUTHOR]

The regional climate impacts of hypothetical future emissions scenarios can be estimated by combining Earth system model simulations with a linear pattern scaling model such as MESMER (Modular Earth System Model Emulator with spatially Resolved output), which uses estimated patterns of the local response per degree of global temperature change. Here we use the mean trend component of MESMER to emulate the regional pattern of the surface temperature response based on historical single-forcer and future Shared Socioeconomic Pathway (SSP) CMIP6 (Coupled Model Intercomparison Project Phase 6) simulations. Errors in the emulations for selected target scenarios (SSP1–1.9, SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) are decomposed into two components, namely (1) the differences in scaling patterns between scenarios as a consequence of varying combinations of external forcings and (2) the intrinsic time series differences between the local and global responses in the target scenario. The time series error is relatively small for high-emissions scenarios, contributing around 20 % of the total error, but is similar in magnitude to the pattern error for lower-emissions scenarios. This irreducible time series error limits the efficacy of linear pattern scaling for emulating strong mitigation pathways and reduces the dependence on the predictor pattern used. The results help guide the choice of predictor scenarios for simple climate models and where to target for the introduction of other dependent variables beyond global surface temperature into pattern scaling models. [ABSTRACT FROM AUTHOR]

The Great Plains of North America host a stark climatic gradient, separating the humid and well-watered eastern US from the semi-arid and arid western US. First studied in detail by John Wesley Powell, this gradient shapes the region's ecosystems, economies, and the availability of water across the landscape. This gradient is largely set by the influence of two competing atmospheric circulation systems that meet over the Great Plains – the wintertime westerlies bring dominantly dry air that gives way to moist, southerly air transported by the Great Plains Low-Level Jet in the warmer months. Climate model simulations suggest that, as CO 2 rises, this low-level jet will strengthen, leading to greater precipitation in the spring, but less in the summer and, thus, no change in mean annual precipitation. Combined with rising temperatures that will increase potential evapotranspiration, semi-arid conditions will shift eastward, with potentially large consequences for the ecosystems and inhabitants of the Great Plains. We examine how hydroclimate in the Great Plains varied in the past in response to warmer global climate by studying the paleoclimate record within the Ogallala Formation, which underlies nearly the entire Great Plains and provides a spatially resolved record of hydroclimate during the globally warmer late Miocene. We use the stable isotopes of oxygen (δ18 O) as preserved in authigenic carbonates hosted within the abundant paleosol and fluvial successions that comprise the Ogallala Formation as a record of past hydroclimate. Today, and coincident with the modern aridity gradient, there is a sharp meteoric water δ18 O gradient with high (−6 to 0 ‰) δ18 O in the southern Great Plains and low (−12 to −18 ‰) δ18 O in the northern Plains. We find that the spatial pattern of reconstructed late Miocene precipitation δ18 O is indistinguishable from the spatial pattern of modern meteoric water δ18 O. We use a recently developed vapor transport model to demonstrate that this δ18O spatial pattern requires air mass mixing over the Great Plains between dry westerly and moist southerly air masses in the late Miocene – consistent with today. Our results suggest that the spatial extent of these two atmospheric circulation systems have been largely unchanged since the late Miocene and any strengthening of the Great Plains Low-Level Jet in response to warming has been isotopically masked by proportional increases in westerly moisture delivery. Our results hold implications for the sensitivity of Great Plains climate to changes in global temperature and CO 2 and also for our understanding of the processes that drove Ogallala Formation deposition in the late Miocene. [ABSTRACT FROM AUTHOR]

It is widely held that global temperature variations on time scales of a decade or less are primarily caused by internal climate variability, with smaller contributions from changes in external climate forcing such as solar irradiance. This paper shows that observed variations in global mean surface temperature, TGS, and ocean heat content (OHC) during the last 1-2 decades imply major changes in climate forcing during this period. In a first step, two independent methods are used to evaluate global temperature corrected for ocean-atmosphere heat exchange. El Niño/Southern Oscillation (ENSO) corrected TGS (written as TGS) is shown to agree closely with a novel temperature metric θ that combines uncorrected TGS with scaled OHC. This agreement rules out a substantial 21st-century contribution to TGS from ocean-atmosphere heat exchange. In contrast to TGS, the time series TGS (t) provides a clear fingerprint of transient global cooling associated with major volcanic eruptions, enabling a more accurate empirical estimate of the climate response of the global mean surface. This allows more accurate estimation of the net climate forcing by stratospheric aerosols and solar irradiance, which is then subtracted from TGS (t) to determine the underlying signal of anthropogenic global warming. Key features of this signal are a slowdown from the late 1990s to 2011 - corresponding to the well known climate hiatus - and a subsequent sharp upturn indicating a steep increase in anthropogenic climate forcing. It is argued that the only plausible cause for this increase is a large fractional decrease in tropospheric aerosol cooling. This attribution is supported by satellite-based observations of a > 50% decrease in SO2 emissions from large sources during the last six years. It suggests that current clean-air policies and replacement of coal by natural gas are driving a significant human made climatic event, 2-4 times faster than greenhouse driven warming alone. If confirmed, this implies a considerably shortened timescale to meet the IPCC 1.5°C objective, with major implications for near-term carbon emission policies. [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) are the gold standard for producing future projections of climate change, but running them is difficult and costly, and thus researchers are generally limited to a small selection of scenarios. This paper presents a technique for detailed emulation of Earth System Model (ESM) temperature output, based on constructing a deterministic model for the mean response to global temperature. The residuals between the mean response and the observed temperature fields are used to construct variability fields that are added to the mean response to produce the final product. The method produces grid-level output with spatially and temporally coherent variability. Output fields include random components, so the system may be run as many times as necessary to produce large ensembles of fields for uncertainty studies and similar uses. We describe the method, show example outputs, and present statistical verification that it reproduces the ESM properties it is intended to capture. This method, available as an open-source R package, should have utility in the study of climate uncertainty and variability, extreme events, and climate change mitigation. [ABSTRACT FROM AUTHOR]

The Indian Ocean exhibits multiple modes of interannual climate variability, whose future behaviour is uncertain. Recent analysis of glacial climates has uncovered an additional El Niño-like equatorial mode in the Indian Ocean, which could also emerge in future warm states. Here we explore changes in the tropical Indian Ocean simulated by the Paleoclimate Model Intercomparison Project (PMIP4). These simulations are performed by an ensemble of models contributing to the Coupled Model Intercomparison Project 6 and over four coordinated experiments: three past periods – the mid-Holocene (6000 years ago), the Last Glacial Maximum (21 000 years ago), the last interglacial (127 000 years ago) – and an idealized forcing scenario to examine the impact of greenhouse forcing. The two interglacial experiments are used to characterize the role of orbital variations in the seasonal cycle, whilst the other pair focus on responses to large changes in global temperature. The Indian Ocean Basin Mode (IOBM) is damped in both the mid-Holocene and last interglacial, with the amount related to the damping of the El Niño–Southern Oscillation in the Pacific. No coherent changes in the strength of the IOBM are seen with global temperature changes; neither are changes in the Indian Ocean Dipole (IOD) nor the Niño-like mode. Under orbital forcing, the IOD robustly weakens during the mid-Holocene experiment, with only minor reductions in amplitude during the last interglacial. Orbital changes do impact the SST pattern of the Indian Ocean Dipole, with the cold pole reaching up to the Equator and extending along it. Induced changes in the regional seasonality are hypothesized to be an important control on changes in the Indian Ocean variability. [ABSTRACT FROM AUTHOR]

Near-term projections of climate change are subject to substantial uncertainty from internal climate variability. Here we present an approach to reduce this uncertainty by sub-selecting those ensemble members that more closely resemble observed patterns of ocean temperature variability immediately prior to a certain start date. This constraint aligns the observed and simulated variability phases and is conceptually similar to initialization in seasonal to decadal climate predictions. We apply this variability constraint to large multi-model projection ensembles from the Coupled Model Intercomparison Project phase 6 (CMIP6), consisting of more than 200 ensemble members, and evaluate the skill of the constrained ensemble in predicting the observed near-surface temperature, sea-level pressure, and precipitation on decadal to multi-decadal timescales. We find that the constrained projections show significant skill in predicting the climate of the following 10 to 20 years, and added value over the ensemble of unconstrained projections. For the first decade after applying the constraint, the global patterns of skill are very similar and can even outperform those of the multi-model ensemble mean of initialized decadal hindcasts from the CMIP6 Decadal Climate Prediction Project (DCPP). In particular for temperature, larger areas show added skill in the constrained projections compared to DCPP, mainly in the Pacific and some neighboring land regions. Temperature and sea-level pressure in several regions are predictable multiple decades ahead, and show significant added value over the unconstrained projections for forecasting the first 2 decades and the 20-year averages. We further demonstrate the suitability of regional constraints to attribute predictability to certain ocean regions. On the example of global average temperature changes, we confirm the role of Pacific variability in modulating the reduced rate of global warming in the early 2000s, and demonstrate the predictability of reduced global warming rates over the following 15 years based on the climate conditions leading up to 1998. Our results illustrate that constraining internal variability can significantly improve the accuracy of near-term climate change estimates for the next few decades. [ABSTRACT FROM AUTHOR]

Major mass extinctions in the Phanerozoic Eon occurred during abrupt global climate changes accompanied by environmental destruction driven by large volcanic eruptions and projectile impacts. Relationships between land temperature anomalies and terrestrial animal extinctions, as well as the difference in response between marine and terrestrial animals to abrupt climate changes in the Phanerozoic, have not been quantitatively evaluated. My analyses show that the magnitude of major extinctions in marine invertebrates and that of terrestrial tetrapods correlate well with the coincidental anomaly of global and habitat surface temperatures during biotic crises, respectively, regardless of the difference between warming and cooling (correlation coefficient R=0.92 –0.95). The loss of more than 35 % of marine genera and 60 % of marine species corresponding to the so-called "big five" major mass extinctions correlates with a >7 ∘ C global cooling and a 7–9 ∘ C global warming for marine animals and a >7 ∘ C global cooling and a >∼7 ∘ C global warming for terrestrial tetrapods, accompanied by ±1 ∘ C error in the temperature anomalies as the global average, although the amount of terrestrial data is small. These relationships indicate that (i) abrupt changes in climate and environment associated with high-energy input by volcanism and impact relate to the magnitude of mass extinctions and (ii) the future anthropogenic extinction magnitude will not reach the major mass extinction magnitude when the extinction magnitude parallelly changes with the global surface temperature anomaly. In the linear relationship, I found lower tolerance in terrestrial tetrapods than in marine animals for the same global warming events and a higher sensitivity of marine animals to the same habitat temperature change than terrestrial animals. These phenomena fit with the ongoing extinctions. [ABSTRACT FROM AUTHOR]

It is now well established that the Arctic is warming at a faster rate than the global average. This warming, which has been accompanied by a dramatic decline in sea ice, has been linked to cooling over the Eurasian subcontinent over recent decades, most dramatically during the period 1998–2012. This is a counterintuitive impact under global warming given that land regions should warm more than ocean (and the global average). Some studies have proposed a causal teleconnection from Arctic sea ice retreat to Eurasian wintertime cooling; other studies argue that Eurasian cooling is mainly driven by internal variability and the relationship to sea ice is coincidental. Overall, there is an impression of strong disagreement between those holding the "ice-driven" versus "internal variability" viewpoints. Here, we offer an alternative framing showing that the sea ice and internal variability views can be compatible. Key to this is viewing Eurasian cooling through the lens of dynamics (linked primarily to internal variability with a small contribution from sea ice; cools Eurasia) and thermodynamics (linked to sea ice retreat; warms Eurasia). This approach, combined with recognition that there is uncertainty in the hypothesized mechanisms themselves, allow both viewpoints (and others) to co-exist and contribute to our understanding of Eurasian cooling. A simple autoregressive model shows that Eurasian cooling of this magnitude is consistent with internal variability, with some periods being more susceptible to strong cooling than others. Rather than posit a "yes-or-no" causal relationship between sea ice and Eurasian cooling, a more constructive way forward is to consider whether the cooling trend was more likely given the observed sea ice loss, as well as other sources of low-frequency variability. Taken in this way both sea ice and internal variability are factors that affect the likelihood of strong regional cooling in the presence of ongoing global warming. [ABSTRACT FROM AUTHOR]

In the context of climate change, emissions of different species (e.g., carbon dioxide and methane) are not directly comparable since they have different radiative efficiencies and lifetimes. Since comparisons via detailed climate models are computationally expensive and complex, emission metrics were developed to allow a simple and straightforward comparison of the estimated climate impacts of emissions of different species. Emission metrics are not unique and variety of different emission metrics has been proposed, with key choices being the climate impacts and time horizon to use for comparisons. In this paper, we present analytical expressions and describe how to calculate common emission metrics for different species. We include the climate metrics radiative forcing, integrated radiative forcing, temperature change and integrated temperature change in both absolute form and normalised to a reference gas. We consider pulse emissions, sustained emissions and emission scenarios. The species are separated into three types: CO2 which has a complex decay over time, species with a simple exponential decay, and ozone precursors (NOx, CO, VOC) which indirectly effect climate via various chemical interactions. We also discuss deriving Impulse Response Functions, radiative efficiency, regional dependencies, consistency within and between metrics and uncertainties. We perform various applications to highlight key applications of emission metrics, which show that emissions of CO2 are important regardless of what metric and time horizon is used, but that the importance of short lived climate forcers varies greatly depending on the metric choices made. Further, the ranking of countries by emissions changes very little with different metrics despite large differences in metric values, except for the shortest time horizons (GWP20). [ABSTRACT FROM AUTHOR]

We examine the influence of increased resolution on four long-standing biases using five different climate models developed within the PRIMAVERA project. The biases are the warm eastern tropical oceans, the double Intertropical Convergence Zone (ITCZ), the warm Southern Ocean, and the cold North Atlantic. Atmosphere resolution increases from ∼100 –200 to ∼25 –50 km, and ocean resolution increases from ∼1∘ (eddy-parametrized) to ∼0.25∘ (eddy-present). For one model, ocean resolution also reaches 1/12 ∘ (eddy-rich). The ensemble mean and individual fully coupled general circulation models and their atmosphere-only versions are compared with satellite observations and the ERA5 reanalysis over the period 1980–2014. The four studied biases appear in all the low-resolution coupled models to some extent, although the Southern Ocean warm bias is the least persistent across individual models. In the ensemble mean, increased resolution reduces the surface warm bias and the associated cloud cover and precipitation biases over the eastern tropical oceans, particularly over the tropical South Atlantic. Linked to this and to the improvement in the precipitation distribution over the western tropical Pacific, the double-ITCZ bias is also reduced with increased resolution. The Southern Ocean warm bias increases or remains unchanged at higher resolution, with small reductions in the regional cloud cover and net cloud radiative effect biases. The North Atlantic cold bias is also reduced at higher resolution, albeit at the expense of a new warm bias that emerges in the Labrador Sea related to excessive ocean deep mixing in the region, especially in the ORCA025 ocean model. Overall, the impact of increased resolution on the surface temperature biases is model-dependent in the coupled models. In the atmosphere-only models, increased resolution leads to very modest or no reduction in the studied biases. Thus, both the coupled and atmosphere-only models still show large biases in tropical precipitation and cloud cover, and in midlatitude zonal winds at higher resolutions, with little change in their global biases for temperature, precipitation, cloud cover, and net cloud radiative effect. Our analysis finds no clear reductions in the studied biases due to the increase in atmosphere resolution up to 25–50 km, in ocean resolution up to 0.25 ∘ , or in both. Our study thus adds to evidence that further improved model physics, tuning, and even finer resolutions might be necessary. [ABSTRACT FROM AUTHOR]

Zero Emissions Commitment (ZEC), the expected change in global temperature following the cessation of anthropogenic greenhouse gas emissions, has recently been assessed by the Zero Emissions Commitment Model Intercomparison Project (ZECMIP). ZECMIP concluded that the component of ZEC from CO2 emissions will likely be close to zero in the decades following the cessation of emissions. However, of the 18 Earth system models that participated in ZECMIP only 2 included a representation of the permafrost carbon feedback to climate change. To better assess the potential impact of permafrost carbon decay on ZEC, a series of perturbed parameter experiments are here conducted with an Earth system model of intermediate complexity. The experiment suggests that the permafrost carbon cycle feedback will directly add 0.06 [0.02 to 0.14] ∘C to the benchmark the ZEC value assesses 50 years after 1000 PgC of CO2 has been emitted to the atmosphere. An additional 0.04 [0 to 0.06] ∘C is likely to been added relative to the benchmark ZEC value from the thaw-lag effect unaccounted for in the ZECMIP experiment design. Overall I assess that the permafrost carbon feedback is unlikely to change the assessment that ZEC is close to zero on decadal timescales; however, the feedback is expected to become more important over the coming centuries. [ABSTRACT FROM AUTHOR]

Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC Working Group II (WGII) a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system's behavior in the absence of climate change, where "climate change refers to any long-term trend in climate, irrespective of its cause" (IPCC, 2014). Impact attribution following this definition remains a challenge because the counterfactual baseline, which characterizes the system behavior in the hypothetical absence of climate change, cannot be observed. Process-based and empirical impact models can fill this gap as they allow us to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method. [ABSTRACT FROM AUTHOR]

Nonlinear responses to externally forced climate change are known to dampen or amplify the local climate impact due to complex cross-compartmental feedback loops in the Earth system. These feedbacks are less well represented in the traditional stand-alone atmosphere and ocean models on which many of today's regional climate assessments rely (e.g., EURO-CORDEX, NOSCCA and BACC II). This has promoted the development of regional climate models for the Baltic Sea region by coupling different compartments of the Earth system into more comprehensive models. Coupled models more realistically represent feedback loops than the information imposed on the region by prescribed boundary conditions and, thus, permit more degrees of freedom. In the past, several coupled model systems have been developed for Europe and the Baltic Sea region. This article reviews recent progress on model systems that allow two-way communication between atmosphere and ocean models; models for the land surface, including the terrestrial biosphere; and wave models at the air–sea interface and hydrology models for water cycle closure. However, several processes that have mostly been realized by one-way coupling to date, such as marine biogeochemistry, nutrient cycling and atmospheric chemistry (e.g., aerosols), are not considered here. In contrast to uncoupled stand-alone models, coupled Earth system models can modify mean near-surface air temperatures locally by up to several degrees compared with their stand-alone atmospheric counterparts using prescribed surface boundary conditions. The representation of small-scale oceanic processes, such as vertical mixing and sea-ice dynamics, appears essential to accurately resolve the air–sea heat exchange over the Baltic Sea, and these parameters can only be provided by online coupled high-resolution ocean models. In addition, the coupling of wave models at the ocean–atmosphere interface allows for a more explicit formulation of small-scale to microphysical processes with local feedbacks to water temperature and large-scale processes such as oceanic upwelling. Over land, important climate feedbacks arise from dynamical terrestrial vegetation changes as well as the implementation of land-use scenarios and afforestation/deforestation that further alter surface albedo, roughness length and evapotranspiration. Furthermore, a good representation of surface temperatures and roughness length over open sea and land areas is critical for the representation of climatic extremes such as heavy precipitation, storms, or tropical nights (defined as nights where the daily minimum temperature does not fall below 20 ∘C), and these parameters appear to be sensitive to coupling. For the present-day climate, many coupled atmosphere–ocean and atmosphere–land surface models have demonstrated the added value of single climate variables, in particular when low-quality boundary data were used in the respective stand-alone model. This makes coupled models a prospective tool for downscaling climate change scenarios from global climate models because these models often have large biases on the regional scale. However, the coupling of hydrology models to close the water cycle remains problematic, as the accuracy of precipitation provided by atmosphere models is, in most cases, insufficient to realistically simulate the runoff to the Baltic Sea without bias adjustments. Many regional stand-alone ocean and atmosphere models are tuned to suitably represent present-day climatologies rather than to accurately simulate climate change. Therefore, more research is required into how the regional climate sensitivity (e.g., the models' response to a given change in global mean temperature) is affected by coupling and how the spread is altered in multi-model and multi-scenario ensembles of coupled models compared with uncoupled ones. [ABSTRACT FROM AUTHOR]

As global warming is proceeding due to rising greenhouse gas concentrations, the Earth system moves towards climate states that challenge adaptation. Past Earth system states are offering possible modelling systems for the global warming of the coming decades. These include the climate of the mid-Pliocene (∼ 3 Ma), the last interglacial (∼ 129–116 ka) and the mid-Holocene (∼ 6 ka). The simulations for these past warm periods are the key experiments in the Paleoclimate Model Intercomparison Project (PMIP) phase 4, contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6). Paleoclimate modelling has long been regarded as a robust out-of-sample test bed of the climate models used to project future climate changes. Here, we document the model setup for PMIP4 experiments with EC-Earth3-LR and present the large-scale features from the simulations for the mid-Holocene, the last interglacial and the mid-Pliocene. Using the pre-industrial climate as a reference state, we show global temperature changes, large-scale Hadley circulation and Walker circulation, polar warming, global monsoons and the climate variability modes – El Niño–Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). EC-Earth3-LR simulates reasonable climate responses during past warm periods, as shown in the other PMIP4-CMIP6 model ensemble. The systematic comparison of these climate changes in past three warm periods in an individual model demonstrates the model's ability to capture the climate response under different climate forcings, providing potential implications for confidence in future projections with the EC-Earth model. [ABSTRACT FROM AUTHOR]

Marine fronts delineate the boundary between distinct water masses and, through the advection of nutrients, are important facilitators of regional productivity and biodiversity. As the modern climate continues to change, the migration of frontal zones is evident, but a lack of information about their status prior to instrumental records hinders future projections. Here, we combine data from lipid biomarkers (archaeal isoprenoid glycerol dibiphytanyl glycerol tetraethers and algal highly branched isoprenoids) with planktic and benthic foraminifera assemblages to detail the biological response of the marine Arctic and polar front migrations on the North Iceland Shelf (NIS) over the last 8 kyr. This multi-proxy approach enables us to quantify the thermal structure relating to Arctic and polar front migration and test how this influences the corresponding changes in local pelagic productivity. Our data show that following an interval of Atlantic water influence, the Arctic front and its associated high pelagic productivity migrated southeastward to the NIS by ∼6.1 ka. Following a subsequent trend in regional cooling, Polar Water from the East Greenland Current and the associated polar front spread onto the NIS by ∼3.8 ka , greatly diminishing local algal productivity through the Little Ice Age. Within the last century, the Arctic and polar fronts have moved northward back to their current positions relative to the NIS and helped stimulate the productivity that partially supports Iceland's economy. Our Holocene records from the NIS provide analogues for how the current frontal configuration and the productivity that it supports may change as global temperatures continue to rise. [ABSTRACT FROM AUTHOR]

Changes in forest cover have a strong effect on climate through the alteration of surface biogeophysical and biogeochemical properties that affect energy, water and carbon exchange with the atmosphere. To quantify biogeophysical and biogeochemical effects of deforestation in a consistent setup, nine Earth system models (ESMs) carried out an idealized experiment in the framework of the Coupled Model Intercomparison Project, phase 6 (CMIP6). Starting from their pre-industrial state, models linearly replace 20×106 km 2 of forest area in densely forested regions with grasslands over a period of 50 years followed by a stabilization period of 30 years. Most of the deforested area is in the tropics, with a secondary peak in the boreal region. The effect on global annual near-surface temperature ranges from no significant change to a cooling by 0.55 ∘ C, with a multi-model mean of -0.22±0.21 ∘ C. Five models simulate a temperature increase over deforested land in the tropics and a cooling over deforested boreal land. In these models, the latitude at which the temperature response changes sign ranges from 11 to 43 ∘ N, with a multi-model mean of 23 ∘ N. A multi-ensemble analysis reveals that the detection of near-surface temperature changes even under such a strong deforestation scenario may take decades and thus longer than current policy horizons. The observed changes emerge first in the centre of deforestation in tropical regions and propagate edges, indicating the influence of non-local effects. The biogeochemical effect of deforestation are land carbon losses of 259±80 PgC that emerge already within the first decade. Based on the transient climate response to cumulative emissions (TCRE) this would yield a warming by 0.46 ± 0.22 ∘ C, suggesting a net warming effect of deforestation. Lastly, this study introduces the "forest sensitivity" (as a measure of climate or carbon change per fraction or area of deforestation), which has the potential to provide lookup tables for deforestation–climate emulators in the absence of strong non-local climate feedbacks. While there is general agreement across models in their response to deforestation in terms of change in global temperatures and land carbon pools, the underlying changes in energy and carbon fluxes diverge substantially across models and geographical regions. Future analyses of the global deforestation experiments could further explore the effect on changes in seasonality of the climate response as well as large-scale circulation changes to advance our understanding and quantification of deforestation effects in the ESM frameworks. [ABSTRACT FROM AUTHOR]