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The Canadian Earth System Model version 5 (CanESM5) developed at Environment and Climate Change Canada's Canadian Centre for Climate Modelling and Analysis (CCCma) is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A 40-member ensemble of CanESM5 retrospective decadal forecasts (or hindcasts) is integrated for 10 years from realistic initial states once a year during 1961 to the present using prescribed external forcing. The results are part of CCCma's contribution to the Decadal Climate Prediction Project (DCPP) component of CMIP6. This paper evaluates CanESM5 large ensemble decadal hindcasts against observational benchmarks and against historical climate simulations initialized from pre-industrial control run states. The focus is on the evaluation of the potential predictability and actual skill of annual and multi-year averages of key oceanic and atmospheric fields at regional and global scales. The impact of initialization on prediction skill is quantified from the hindcasts decomposition into uninitialized and initialized components. The dependence of potential and actual skill on ensemble size is examined. CanESM5 decadal hindcasts skillfully predict upper-ocean states and surface climate with a significant impact from initialization that depend on climate variable, forecast range, and geographic location. Deficiencies in the skill of North Atlantic surface climate are identified and potential causes discussed. The inclusion of biogeochemical modules in CanESM5 enables the prediction of carbon cycle variables which are shown to be potentially skillful on decadal timescales, with a strong long-lasting impact from initialization on skill in the ocean and a moderate short-lived impact on land. [ABSTRACT FROM AUTHOR]

Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO 2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities. [ABSTRACT FROM AUTHOR]

A new computationally efficient version of the Norwegian Earth System Model (NorESM) is presented. This new version (here termed NorESM1-F) runs about 2.5 times faster (e.g., 90 model years per day on current hardware) than the version that contributed to the fifth phase of the Coupled Model Intercomparison project (CMIP5), i.e., NorESM1-M, and is therefore particularly suitable for multimillennial paleoclimate and carbon cycle simulations or large ensemble simulations. The speed-up is primarily a result of using a prescribed atmosphere aerosol chemistry and a tripolar ocean–sea ice horizontal grid configuration that allows an increase of the ocean–sea ice component time steps. Ocean biogeochemistry can be activated for fully coupled and semi-coupled carbon cycle applications. This paper describes the model and evaluates its performance using observations and NorESM1-M as benchmarks. The evaluation emphasizes model stability, important large-scale features in the ocean and sea ice components, internal variability in the coupled system, and climate sensitivity. Simulation results from NorESM1-F in general agree well with observational estimates and show evident improvements over NorESM1-M, for example, in the strength of the meridional overturning circulation and sea ice simulation, both important metrics in simulating past and future climates. Whereas NorESM1-M showed a slight global cool bias in the upper oceans, NorESM1-F exhibits a global warm bias. In general, however, NorESM1-F has more similarities than dissimilarities compared to NorESM1-M, and some biases and deficiencies known in NorESM1-M remain. [ABSTRACT FROM AUTHOR]

Paleoclimate reconstructions of the Early Eocene provide important data constraints on the climate and hydrologic cycle under extreme warm conditions. Available terrestrial water isotope records have been primarily interpreted to signal an enhanced hydrologic cycle in the Early Eocene associated with large-scale warming induced by high atmospheric CO2. However, orbital-scale variations in these isotope records have been difficult to quantify and largely overlooked, even though orbitally driven changes in solar irradiance can impact temperature and the hydrologic cycle. In this study, we fill this gap using water isotope–climate simulations to investigate the orbital sensitivity of Earth's hydrologic cycle under different CO2 background states. We analyze the relative difference between climatic changes resulting from CO2 and orbital changes and find that the seasonal climate responses to orbital changes are larger than CO2 -driven changes in several regions. Using terrestrial δ18O and δ2H records from the Paleocene–Eocene Thermal Maximum (PETM), we compare our modeled isotopic seasonal range to fossil evidence and find approximate agreement between empirical and simulated isotopic compositions. The limitations surrounding the equilibrated snapshot simulations of this transient event and empirical data include timing and time interval discrepancies between model and data, the preservation state of the proxy, analytical uncertainty, the relationship between δ18O or δ2H and environmental context, and vegetation uncertainties within the simulations. In spite of the limitations, this study illustrates the utility of fully coupled, isotope-enabled climate models when comparing climatic changes and interpreting proxy records in times of extreme warmth. [ABSTRACT FROM AUTHOR]

The transient climate response to cumulative CO2 emissions (TCRE) is a useful metric of climate warming that directly relates the cause of climate change (cumulative carbon emissions) to the most used index of climate change (global mean near-surface temperature change). In this paper, analytical reasoning is used to investigate why TCRE is near constant over a range of cumulative emissions up to 2000 Pg of carbon. In addition, a climate model of intermediate complexity, forced with a constant flux of CO2 emissions, is used to explore the effect of terrestrial carbon cycle feedback strength on TCRE. The analysis reveals that TCRE emerges from the diminishing radiative forcing from CO2 per unit mass being compensated for by the diminishing ability of the ocean to take up heat and carbon. The relationship is maintained as long as the ocean uptake of carbon, which is simulated to be a function of the CO2 emissions rate, dominates changes in the airborne fraction of carbon. Strong terrestrial carbon cycle feedbacks have a dependence on the rate of carbon emission and, when present, lead to TRCE becoming rate dependent. Despite these feedbacks, TCRE remains roughly constant over the range of the representative concentration pathways and therefore maintains its primary utility as a metric of climate change. [ABSTRACT FROM AUTHOR]

Forest fragmentation impacts carbon uptake and storage; however, the magnitude and direction of fragmentation impacts on soil respiration remain poorly characterized. We quantify soil respiration rates along edge‐to‐interior transects in two temperate broadleaf forests in the eastern United States that vary in climate, species composition, and soil type. We observe average soil respiration rates 15–26% higher at the forest edge compared to the interior, corresponding to large gradients in soil temperature. We find no significant difference in the sensitivity of soil respiration to temperature between the forest edge and interior. Fragmentation and resultant shifts in microenvironment alter forest productivity and soil respiration near forest edges. Ecosystem models do not currently represent edge dynamics, but given the prevalence of landscape fragmentation and its effect on carbon cycling along forest edges, this omission likely introduces an important source of uncertainty in our understanding of terrestrial carbon dynamics with a changing landscape and climate. Plain Language Summary: Forests continuously release carbon dioxide into the atmosphere via the decomposition of soil organic matter and biological activities of belowground organisms in a process known as soil respiration. When intact forests are broken up (either naturally or by humans), the remaining fragments experience distinct environmental conditions near the edges. Previous work shows that temperate forests can capture and store more atmospheric carbon per unit area near forest edges; however, it is unknown how the presence of forest edges impacts the rate of carbon loss via soil respiration. Here we measure soil respiration rates along forest edges, where the local soil temperatures tend to be warmer than the forest interior. We find that near the edges, soil respiration rates are higher than the forest interior. We attribute the increased soil respiration rate to warmer forest edge soil temperatures. Our results suggest that estimates of soil respiration in the temperate forest region may be underestimating biological emissions of carbon dioxide. Altogether, our research identifies an important phenomenon previously unaccounted for in our understanding of the carbon cycle with important implications for estimating forest carbon exchanges in fragmented landscapes, particularly as the climate continues to warm. Key Points: Soil respiration increases with proximity to temperature forest edgesEdge soil respiration enhancements are driven by large positive gradients in soil temperatureForest edge carbon dynamics are generally omitted from ecosystem models and carbon accounting frameworks [ABSTRACT FROM AUTHOR]

The response of the biosphere to variation in climate plays a key role in predicting the carbon cycle, hydrological cycle, terrestrial surface energy balance, and the feedbacks in the climate system. Predicting the response of Earth's biosphere to global warming requires the ability to mechanistically represent the processes controlling photosynthesis, respiration, and water use. This study uses observations of the sensitivity of leaf area to the physical environment to identify where ecosystem functioning is well simulated in an ensemble of Earth system models. These patterns and data–model comparisons are leveraged to hypothesize which physiological mechanisms—photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability—dominate the ecosystem response in places with different climates. The models are generally successful in reproducing the broad sign and shape of the sensitivity of leaf area to interannual variations in climate, except for simulating generally decreased leaf area during warmer years in places with hot, wet climates. In addition, simulated sensitivity of the leaf area to temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified sensitivity and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that the simulated sensitivities of vegetation climate are too strong in the models. Finally, models and observations share an abrupt threshold between dry regions and wet regions around 1000 mm yr−1. [ABSTRACT FROM AUTHOR]

Uncertainty in the simulation of the carbon cycle contributes significantly to uncertainty in the projections of future climate change. We use observations of forest fraction to constrain carbon cycle and land surface input parameters of the global climate model FAMOUS, in the presence of an uncertain structural error. Using an ensemble of climate model runs to build a computationally cheap statistical proxy (emulator) of the climate model, we use history matching to rule out input parameter settings where the corresponding climate model output is judged sufficiently different from observations, even allowing for uncertainty. Regions of parameter space where FAMOUS best simulates the Amazon forest fraction are incompatible with the regions where FAMOUS best simulates other forests, indicating a structural error in the model. We use the emulator to simulate the forest fraction at the best set of parameters implied by matching the model to the Amazon, Central African, South East Asian, and North American forests in turn. We can find parameters that lead to a realistic forest fraction in the Amazon, but that using the Amazon alone to tune the simulator would result in a significant overestimate of forest fraction in the other forests. Conversely, using the other forests to tune the simulator leads to a larger underestimate of the Amazon forest fraction. We use sensitivity analysis to find the parameters which have the most impact on simulator output and perform a history-matching exercise using credible estimates for simulator discrepancy and observational uncertainty terms. We are unable to constrain the parameters individually, but we rule out just under half of joint parameter space as being incompatible with forest observations. We discuss the possible sources of the discrepancy in the simulated Amazon, including missing processes in the land surface component and a bias in the climatology of the Amazon. [ABSTRACT FROM AUTHOR]

We analyse how climate change may alter risks posed by droughts to carbon fluxes in European ecosystems. The approach follows a recently proposed framework for risk analysis based on probability theory. In this approach, risk is quantified as the product of hazard probability and ecosystem vulnerability. The probability of a drought hazard is calculated here from the Standardized Precipitation-Evapotranspiration Index (SPEI). Vulnerability is calculated from the response to drought simulated by process-based vegetation models. We use six different models: three for generic vegetation (JSBACH, LPJmL, ORCHIDEE) and three for specific ecosystems (Scots pine forests: BASFOR; winter wheat fields: EPIC; grasslands: PASIM). The periods 1971-2000 and 2071-2100 are compared. Climate data are based on gridded observations and on output from the regional climate model REMO using the SRES A1B scenario. The risk analysis is carried out for ~ 18 000 grid cells of 0.25 x 0.25° across Europe. For each grid cell, drought vulnerability and risk are quantified for five seasonal variables: net primary and ecosystem productivity (NPP, NEP), heterotrophic respiration (Rh), soil water content and evapotranspiration. In this analysis, climate change leads to increased drought risks for net primary productivity in the Mediterranean area: five of the models estimate that risk will exceed 15%. The risks increase mainly because of greater drought probability; ecosystem vulnerability will increase to a lesser extent. Because NPP will be affected more than Rh, future carbon sequestration (NEP) will also be at risk predominantly in southern Europe, with risks exceeding 0.25 g C m-2 d-1 according to most models, amounting to reductions in carbon sequestration of 20 to 80%. [ABSTRACT FROM AUTHOR]