Generation Canadian Earth System Model Research Articles

Future Scenarios of Bioclimatic Viticulture Indices in the Eastern Mediterranean: Insights into Sustainable Vineyard Management in a Changing Climate

The evaluation of bioclimatic viticulture indices (BVIs) zones, similar to any other crop, necessitates a comprehensive understanding of the spatial variability of climate data. This study focuses on assessing the suitability of BVIs in the Jabal Al Arab region, a significant viticulture area in the Eastern Mediterranean. The aim is to analyze four temperature-based bioclimatic indices and the hydrothermal coefficient (HTC) to map their patterns and spatial variation across the region under climate change scenarios. Daily temperature data from 15 meteorological stations and 57 rain gauges spanning 1984–2014 were utilized, along with downscaled future scenarios (the Representative Concentration Pathways (RCPs) based on the second generation Canadian Earth System Model (CanESM2)) for 2016–2100. Additionally, statistical analysis and hybrid interpolation (regression-kriging) were employed to accurately map the BVIs throughout the region. The results reveal substantial spatial variability in Jabal Al Arab’s climate, with heat accumulation and the hydrothermal index during the growing season significantly influenced by elevation and distance to the seacoast. Additionally, the viticulture zones vary based on the specific index used and the projected future climate scenarios compared to the current climate. Climate change projections indicate a trend toward warmer conditions in the future. Under the RCP scenarios, the region can be categorized into up to three bioclimatic classes for certain indices, in contrast to the current climate with six classes. These findings offer valuable insights into viticulture suitability within each climatic region and facilitate the identification of homogeneous zones. By employing consistent bioclimatic indices and advanced hybrid interpolation techniques, this study enables meaningful comparisons of Jabal Al Arab with other viticulture regions worldwide. Such information is crucial for selecting suitable grapevine varieties and assessing the potential for grape production in the future.

STATISTICAL DOWNSCALED LOCAL CLIMATE MODEL FOR FUTURE RAINFALL CHANGES ANALYSIS: A CASE STUDY OF HYOGO PREFECTURE, JAPAN

<p>For decades, climate models have been used to understand the present and historical climates, especially global climate models (GCMs). They are used to understand the interaction between climate system processes and forecast future climates. However, the issue of low resolution and accuracy often lead to inadequacy in capturing the variations in climate variables related to impact assessment. In order to capture the local climate changes in Hyogo Prefecture of Western Japan, a local climate modelling based on Second Generation Canadian Earth System Model (CanESM2) was applied using the statistical downscaling technique. Representative Concentration Pathway (RCP) 4.5 and 8.5 scenario were used in generating future climate models. The reliability of models was tested with Linear Regression, Pearson correlation, and Cronbach Alpha. Moderate relationship between rainfall data and both RCP scenarios was found in all chosen stations. Spatial analysis outcome showed that there is a possibility of increase in annual rainfall in Hyogo prefecture, where the increase is significant in Northern region. There is a possibility of increase in maximum and minimum temperature in four selected stations due to the increase of greenhouse gas emissions.</p>

Development of regional climate model for Hyogo prefecture, Japan using statistical downscaling method on CanESM2 RCP2.6, 4.5 and 8.5 scenarios

For decades, climate models have been used to understand the present and historical climates, especially global climate models (GCMs). They are used to understand the interaction between climate system processes and forecast future climates. However, the issue of low resolution and accuracy often lead to inadequacy in capturing the variations in climate variables related to impact assessment. In order to capture the local climate changes in Hyogo Prefecture, a regional climate modelling based on Second Generation Canadian Earth System Model (CanESM2) was applied using the statistical downscaling technique. Representative Concentration Pathway (RCP) 2.6, 4.5 and 8.5 were used in generating future climate models. The reliability of three models was tested with linear regression, Pearson correlation, probability density function (PDF) and Cronbach Alpha. A moderate relationship between rainfall data and RCP4.5 was found in all chosen stations. Spatial analysis outcome showed that there is a possibility of decreased annual rainfall in the North-eastern (which city/town) and South-western (which city/town?) regions in Hyogo Prefecture.

Contribution of Global Warming and Atmospheric Circulation to the Hottest Spring in Eastern China in 2018

The spring of 2018 was the hottest on record since 1951 over eastern China based on station observations, being 2.5°C higher than the 1961–90 mean and with more than 900 stations reaching the record spring mean temperature. This event exerted serious impacts in the region on agriculture, plant phenology, electricity transmission systems, and human health. In this paper, the contributions of human-induced climate change and anomalous anticyclonic circulation to this event are investigated using the newly homogenized observations and updated Met Office Hadley Centre system for attribution of extreme events, as well as CanESM2 (Second Generation Canadian Earth System Model) simulations. Results indicate that both anthropogenic influences and anomalous anticyclonic circulation played significant roles in increasing the probability of the 2018 hottest spring. Quantitative estimates of the probability ratio show that anthropogenic forcing may have increased the chance of this event by ten-fold, while the anomalous circulation increased it by approximately two-fold. The persistent anomalous anticyclonic circulation located on the north side of China blocked the air with lower temperature from high latitudes into eastern China. Without anthropogenic forcing or without the anomalous circulation in northern China, the occurrence probability of the extreme warm spring is significantly reduced.

The seasonal footprinting mechanism in large ensemble simulations of the second generation Canadian earth system model: uncertainty due to internal climate variability

Previous studies indicated that the wintertime North Pacific Oscillation (NPO) could exert marked impacts on the following winter El Niño-Southern Oscillation (ENSO) via the seasonal footprinting mechanism (SFM). Here, we examine this winter NPO-ENSO relationship in a 50-member ensemble of historical simulations conducted with the Canadian Centre for Climate Modeling and Analysis second generation Canadian Earth System Model (CanESM2) over the period of 1950–2005. The observed NPO pattern, featured by a meridional dipole atmospheric anomaly over the North Pacific, can be well reproduced by all of the 50 ensemble members. The multi-member ensemble (MME) mean can well simulate the observed NPO-ENSO relationship, as well as the SFM process. However, there exists a large spread of the results among the 50 members due to internal climate variability. Internal climate variability influences the winter NPO-ENSO relationship through modulating the subtropical center of the NPO. Specifically, the ensemble members with high NPO-ENSO correlations tend to have strong atmospheric anomalies over the subtropical North Pacific in winter. The atmospheric circulation anomaly brings strong sea surface temperature and precipitation anomalies in the tropical central Pacific and westerly wind anomalies over the tropical western Pacific in the following spring. These anomalies sustain in the following seasons and eventually lead to ENSO events in the following winter.

Future Assessment of Precipitation and Temperature for Developing Urban Catchment Under Impact of Climate Change

In this study, the attempt is made to investigate the impact of future climate changes related to three weather parameter maximum temperature (Tmax), minimum temperature (Tmin) and precipitation for study area were projected for two future time slice (2017–2058), and (2059–2100) from the three Global Climate Models (GCMs), CanESM2, CGCM3 and HadCM3 under different representative concentration pathway (RCPs) scenarios (RCP2.5, RCP4.5, and RCP8.5) using statistical downscaling model (SDSM). The predictor variables are downloaded from National Center for Environmental Prediction/Atmospheric Research (NCEP/NCAR) and simulations from the three Global Climate Models (GCMs), Second Generation Canadian Earth System Model (CanESM2), Canadian Centre for Climate Modelling and Analysis (CGCM3) and Hadley Centre for Climate Prediction and Research/Met Office (HadCM3) variability and changes in Tmax, Tmin and precipitation under different (RCPs) scenarios have been presented for two future time slice. The performance for three models showed maximum/minimum temperature increases in future for almost all the (RCPs) scenarios. Also precipitation of the entire catchment was found to increasing trends for all scenarios. In case of HadCM3 model, under RCP8.5 scenarios for the period (2017-2058), changes in max temperature, min temperature, and precipitation are forecasted as 0.72 °C, 1.42 °C, and 2.82 mm and for the period (2059-2100) are 1.16 °C, 2.14 °C, and 6.85 mm.The results obtained from HadCM3 model is higher side as compared with CanESM2, CGCM3.These results can provide understanding of the hydrologic role of future climate change scenarios, which is essential for probable impacts of climate change for planning and management of appropriate choice for designing the storm water drainage system and infrastructure for newly growing urbanization under climate change are of great concern to hydrologists, water managers, and policymakers.

Comparing Meteorological Data Sets in the Evaluation of Climate Change Impact on Hydrological Indicators: A Case Study on a Mexican Basin

This study evaluates the choice of the meteorological data set in the simulation of the streamflow of a Mexican basin, in the bias correction of climate simulations, and in the climate change impact on hydrological indicators. The selected meteorological data sets come from stations, two interpolated data sets and one reanalysis data set. The climate simulations were taken from the five-member ensemble from the second generation Canadian Earth System Model (CanESM2) under two representative concentration pathways (RCPs), for a reference period (1981–2000) and two future periods (2041–2060 and 2081–2100). The selected lumped hydrological model is GR4J, which is a daily lumped four-parameter rainfall-runoff model. Firstly, the results show that GR4J can be calibrated and validated with the meteorological data sets to simulate daily streamflow; however, the hydrological model leads to different hydrological responses for the basin. Secondly, the bias correction procedure obtains a similar relative climate change signal for the variables, but the magnitude of the signal strongly varies with the source of meteorological data. Finally, the climate change impact on hydrological indicators also varies depending on the meteorological data source, thus, for the overall mean flow, this uncertainty is greater than the uncertainty related to the natural variability. On the other hand, mixed results were found for high flows. All in all, the selection of meteorological data source should be taken into account in the evaluation of climate change impact on water resources.

Incorporation of Long Term Climate Changes in Hydrological Modelling

One of climate change's most important concerns at the moment is its impact on hydrology as it has direct links with agriculture, vegetation, and livelihood. This study tries to analyze potential future climate change in the Kumaradhara river basin. This study involved three steps: (1) acquiring and using general circulation model (GCM) to project future global climate scenarios; (2) establishing statistical relationships between GCM data and observed data using Statistical Downscaling Model (SDSM); (3) downscaling the second generation Canadian Earth system Model (CanESM2)GCM output based on the established statistical relationship. The statistical downscaling is carried out for three scenarios used in the fifth evaluation report of the recent Intergovernmental Panel on Climate Change (IPCC) viz., Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5. The statistical downscaling Model (SDSM) results showed that the mean annual daily precipitation is altered in the basin under all the scenarios but it will be different in different time periods depending on scenarios and the basin will experience the reduced precipitation levels in summer. Also the precipitation will marginally rise in all the time slices with reference to baseline data. We can conclude from the results that this region's climate will affect future farming as the availability of water is bound to change. This study should, however, be followed up by a larger study incorporating multiple CMIP5 models such that changes in hydrological-regimes can be examined appropriately.

Statistically downscaled climate dataset for East Africa

For many regions of the world, current climate change projections are only available at coarser spatial resolution from Global Climate Models (GCMs) that cannot directly be used in impact assessment and adaptation studies at regional and local scale. Impact assessment studies require high-resolution climate data to drive impact assessment models. To overcome this data challenge, we produced a station based climate projection (precipitation and maximum and minimum temperature) for Ethiopia, Kenya, and Tanzania using observed daily data from 211 stations obtained from the National Meteorological Agency of Ethiopia and international databases. Moreover, 26 large-scale climate variables derived from the National Centers for Environmental Prediction reanalysis data (1961–2005) and second generation Canadian Earth System Model (CanESM2, 1961–2100) are used. Statistical Down-Scaling Model (SDSM) is used to produce the required high-resolution climate projection by developing a statistical relationship between the large- and local-scale climate variables. The predictors are analysed more than 16458 times and we provided 20 ensembles for the current (1961–2005) and future (2006–2100, under RCP2.6, RCP4.5, and RCP8.5) climate.

Regional climate projections for impact assessment studies in East Africa

In order to overcome limitations of climate projections from Global Climate Models (GCMs), such as coarse spatial resolution and biases, in this study, the Statistical Down-Scaling Model (SDSM) is used to downscale daily precipitation and maximum and minimum temperature (T-max and T-min) required by impact assessment models. We focus on East Africa, a region known to be highly vulnerable to climate change and at the same time facing challenges concerning availability and accessibility of climate data. SDSM is first calibrated and validated using observed daily precipitation, (T-max, and T-min) from 214 stations and predictors derived from the reanalysis data of the National Centers for Environmental Prediction. For projection (2006–2100), the same predictors derived from the second generation Canadian Earth System Model (CanESM2) are used. SDSM projections show an increase in precipitation during the short-rain season (October–December) in large parts of the region in the 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100). During the long-rain season (March–May (MAM)) precipitation is expected to increase (up to 680 mm) in Ethiopia, mainly in the western part, and Kenya and decrease (up to −500 mm) in Tanzania in the 2020s, 2050s, and 2080s. However, the western part of Ethiopia will be much drier than the baseline period (1961–1990) during June–September (JJAS) in the 2020s, 2050s, and 2080s, which indicates a shift in precipitation from JJAS to MAM. Annually, precipitation, T-max, and T-min will be higher than during the baseline period throughout the 21 century in large parts of the region. The projection based on SDSM is in line with the direction of CMIP5 GCMs but differs in magnitude, particularly for T-max and T-min. Overall, we conclude that the downscaled data allow for much more fine-scaled adaptation plans and ultimately better management of the impacts of projected climate in basins of Ethiopia, Kenya, and Tanzania.

Hydrologic Impacts of Ensemble-RCM-Projected Climate Changes in the Athabasca River Basin, Canada

Abstract In this study, the Providing Regional Climates for Impacts Studies (PRECIS) and the Regional Climate Model (RegCM) system as well as the Variable Infiltration Capacity (VIC) macroscale hydrologic model were integrated into a general framework to investigate impacts of future climates on the hydrologic regime of the Athabasca River basin. Regional climate models (RCMs) including PRECIS and RegCM were used to develop ensemble high-resolution climate projections for 1979–2099. RCMs were driven by the boundary conditions from the Hadley Centre Global Environment Model, version 2 with Earth system configurations (HadGEM2-ES); the Second Generation Canadian Earth System Model (CanESM2); and the Geophysical Fluid Dynamics Laboratory Earth System Model with MOM (GFDL-ESM2M) under the representative concentration pathways (RCPs). The ensemble climate simulations were validated through comparison with observations for 1984–2003. The RCMs project increases in temperature, precipitation, and wind speed under RCPs across most of the Athabasca River basin. Meanwhile, VIC was calibrated using the University of Arizona Shuffled Complex Evolution method (SCE-UA). The performance of the VIC model in replicating the characteristics of the observed streamflow was validated for 1994–2003. Changes in runoff and streamflow under RCPs were then simulated by the validated VIC model. The validation results demonstrate that the ensemble-RCM-driven VIC model can effectively reproduce historical climatological and hydrological patterns in the Athabasca River basin. The ensemble-RCM-driven VIC model shows that monthly streamflow is projected to increase in the 2050s and 2080s under RCPs, with notably higher flows expected in the spring for the 2080s. This will have substantial impacts on water balance on the Athabasca River basin, thus affecting the surrounding industry and ecosystems. The developed framework can be applied to other regions for exploration of hydrologic impacts under climate change.

Dependence of Present and Future European Temperature Extremes on the Location of Atmospheric Blocking.

The impact of atmospheric blocking on European heat waves (HWs) and cold spells (CSs) is investigated for present and future conditions . A 50‐member ensemble of the second generation Canadian Earth System Model is used to quantify the role of internal variability in the response to blocking. We find that the present blocking‐extreme temperature link is well represented compared to ERA‐Interim, despite a significant underestimation of blocking frequency in most ensemble members. Our results show a strong correlation of blocking with northern European HWs in summer, spring, and fall. However, we also find a strong anticorrelation between blocking and HW occurrence in southern Europe in all seasons. Blocking increases the CS frequency particularly in southern Europe in fall, winter, and spring but reduces it in summer. For the future we find that blocking will continue to play an important role in the development of both CSs and HWs in all seasons.

Influences of Temperature and Precipitation on Historical and Future Snowpack Variability over the Northern Hemisphere in the Second Generation Canadian Earth System Model

This study examines the changing roles of temperature and precipitation on snowpack variability in the Northern Hemisphere for Second Generation Canadian Earth System Model (CanESM2) historical (1850–2005) and future (2006–2100) climate simulations. The strength of the linear relationship between monthly snow water equivalent (SWE) in January–April and precipitation P or temperature T predictors is found to be a sigmoidal function of the mean temperature over the snow season up to the indicated month. For P predictors, the strength of this relationship increases for colder snow seasons, whereas for T predictors it increases for warmer snow seasons. These behaviors are largely explained by the daily temperature percentiles below freezing during the snow accumulation period. It is found that there is a threshold temperature (−5±1°C, depending on month in the snow season and largely independent of emission scenario), representing a crossover point below which snow seasons are sufficiently cold that P is the primary driver of snowpack amount and above which T is the primary driver. This isotherm allows one to delineate the snow-climate regions and elevation zones in which snow-cover amounts are more vulnerable to a warming climate. As climate projections indicate that seasonal isotherms shift northward and toward higher elevations, regions where snowpack amount is mainly driven by precipitation recede, whereas temperature-sensitive snow-covered areas extend to higher latitudes and/or elevations, with resulting impacts on ecosystems and society.

Seasonal prediction of the East Asian summer monsoon with a partial-least square model

Seasonal prediction of the East Asian summer monsoon (EASM) strength is probably one of the most challenging and crucial issues for climate prediction over East Asia. In this paper, a statistical method called partial-least square (PLS) regression is utilized to uncover principal sea surface temperature (SST) modes in the winter preceding the EASM. Results show that the SST pattern of the first PLS mode is associated with the turnabout of warming (or cooling) phase of a mega-El Nino/Southern Oscillation (mega-ENSO) (a leading mode of interannual-to-interdecadal variations of global SST), whereas that of the second PLS mode leads the warming/cooling mega-ENSO by about 1 year, signaling precursory conditions for mega-ENSO. These indicate that mega-ENSO may provide a critical predictability source for the EASM strength. Based on a 40-year training period (1958–1997), a PLS prediction model is constructed using the two leading PLS modes and 3-month-lead hindcasts are performed for the validation period of 1998–2013. A promising skill is obtained, which is comparable to the ensemble mean of versions 3 and 4 of the Canadian Community Atmosphere Model (CanCM3/4) hindcasts from the newly developed North American Multi-model Ensemble Prediction System regarding the interannual variations of the EASM strength. How to improve dynamical model simulation of the EASM is also examined through comparing the CanCM3/4 hindcast (1982–2010) with the 106-year historical run (1900–2005) by the Second Generation Canadian Earth System Model (CanESM2). CanCM3/4 exhibits a high skill in the EASM hindcast period 1982–2010 during which it also has a better performance in capturing the relationship between the EASM and mega-ENSO. By contrast, the simulation skill of CanESM2 is quite low and it is unable to reproduce the linkage between the EASM and mega-ENSO. All these results emphasize importance of mega-ENSO in seasonal prediction and dynamical model simulation of the EASM.

A Conceptual Model of Ocean Heat Uptake under Climate Change

Abstract A conceptual model of ocean heat uptake is developed as a multilayer generalization of Gnanadesikan. The roles of Southern Ocean Ekman and eddy transports, North Atlantic Deep Water (NADW) formation, and diapycnal mixing in controlling ocean stratification and transient heat uptake are investigated under climate change scenarios, including imposed surface warming, increased Southern Ocean wind forcing, with or without eddy compensation, and weakened meridional overturning circulation (MOC) induced by reduced NADW formation. With realistic profiles of diapycnal mixing, ocean heat uptake is dominated by Southern Ocean Ekman transport and its long-term adjustment controlled by the Southern Ocean eddy transport. The time scale of adjustment setting the rate of ocean heat uptake increases with depth. For scenarios with increased Southern Ocean wind forcing or weakened MOC, deepened stratification results in enhanced ocean heat uptake. In each of these experiments, the role of diapycnal mixing in setting ocean stratification and heat uptake is secondary. Conversely, in experiments with enhanced diapycnal mixing as employed in “upwelling diffusion” slab models, the contributions of diapycnal mixing and Southern Ocean Ekman transport to the net heat uptake are comparable, but the stratification extends unrealistically to the sea floor. The simple model is applied to interpret the output of an Earth system model, the Second Generation Canadian Earth System Model (CanESM2), in which the atmospheric CO2 concentration is increased by 1% yr−1 until quadrupling, where it is found that Southern Ocean Ekman transport is essential to reproduce the magnitude and vertical profile of ocean heat uptake.

Terrestrial ecosystems response to future changes in climate and atmospheric CO<sub>2</sub> concentration

Abstract. The response of the terrestrial carbon cycle to future changes in climate and atmospheric CO2 is assessed by analysing simulation results for the 2006–2100 period made with the second generation Canadian Earth system model (CanESM2) for the RCP 2.6, RCP 4.5 and RCP 8.5 climate change scenarios. Our interest is in the extent to which global terrestrial carbon pools and sinks, in particular those of the Amazonian region, are vulnerable to the adverse effects of climate change. CanESM2 results indicate that land remains an overall sink of atmospheric carbon for the 2006–2100 period. The net carbon uptake by land in response to changes in climate and atmospheric CO2 is close to 20, 80 and 140 Pg C for the RCP 2.6, 4.5 and 8.5 scenarios, respectively. The latitudinal structure of future atmosphere–land CO2 flux remains similar to that observed for the historical period with northern mid- to high-latitude regions gaining carbon from the atmosphere while the tropics remain either carbon neutral or a modest source of atmospheric carbon depending on scenario. These changes occur in conjunction with simulated precipitation and soil moisture increases over northern mid- and high-latitude land regions and precipitation and soil moisture decreases over the South American continent in all scenarios. Compared to other regions of the globe, which are either carbon sinks or near neutral, the Amazonian region is simulated to be a net source of carbon during the 21st century. Moreover, and unexpectedly, the rate of carbon loss to the atmosphere from the Amazonian region is largely independent of the differences between the three scenarios considered.

Surface Air Temperature Changes over the Twentieth and Twenty-First Centuries in China Simulated by 20 CMIP5 Models

Abstract Historical temperature variability over China during the twentieth century and projected changes under three emission scenarios for the twenty-first century are evaluated on the basis of a multimodel ensemble of 20 GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and two observational datasets. Changes relative to phase 3 of the Coupled Model Intercomparison Project (CMIP3) are assessed, and the performance of individual GCMs is also quantified. Compared with observations, GCMs have substantial cold biases over the Tibetan Plateau, especially in the cold season. The timing and location of these biases also correspond to the greatest disagreement among the individual models, indicating GCMs’ limitations in reproducing climatic features in this complex terrain. The CMIP5 multimodel ensemble shows better agreement with observations than CMIP3 in terms of the temperature biases. Both CMIP3 and CMIP5 capture the climatic warming over the twentieth century. However, the magnitude of the annual mean temperature trends is underestimated. There is also limited agreement in the spatial and seasonal patterns of temperature trends over China. Based on six statistical measures, four individual models—the Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR), Second Generation Canadian Earth System Model (CanESM2), Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM), and Community Climate System Model, version 4 (CCSM4)—best represent surface air temperature variability over China. The future temperature projections indicate that the representative concentration pathway (RCP) 8.5 and RCP 4.5 scenarios exhibit a gradual increase in annual temperature during the twenty-first century at a rate of 0.60° and 0.27°C (10 yr)−1, respectively. As the lowest-emission mitigation scenario, RCP 2.6 projects the lowest rate of temperature increase [0.10°C (10 yr)−1]. By the end of the twenty-first century, temperature is projected to increase by 1.7°–5.7°C, with larger warming over northern China and the Tibetan Plateau.

Effect of Anthropogenic Land-Use and Land-Cover Changes on Climate and Land Carbon Storage in CMIP5 Projections for the Twenty-First Century

Abstract The effects of land-use changes on climate are assessed using specified-concentration simulations complementary to the representative concentration pathway 2.6 (RCP2.6) and RCP8.5 scenarios performed for phase 5 of the Coupled Model Intercomparison Project (CMIP5). This analysis focuses on differences in climate and land–atmosphere fluxes between the ensemble averages of simulations with and without land-use changes by the end of the twenty-first century. Even though common land-use scenarios are used, the areas of crops and pastures are specific for each Earth system model (ESM). This is due to different interpretations of land-use classes. The analysis reveals that fossil fuel forcing dominates land-use forcing. In addition, the effects of land-use changes are globally not significant, whereas they are significant for regions with land-use changes exceeding 10%. For these regions, three out of six participating models—the Second Generation Canadian Earth System Model (CanESM2); Hadley Centre Global Environmental Model, version 2 (Earth System) (HadGEM2-ES); and Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM)—reveal statistically significant changes in mean annual surface air temperature. In addition, changes in land surface albedo, available energy, and latent heat fluxes are small but significant for most ESMs in regions affected by land-use changes. These climatic effects are relatively small, as land-use changes in the RCP2.6 and RCP8.5 scenarios are small in magnitude and mainly limited to tropical and subtropical regions. The relative importance of the climatic effects of land-use changes is higher for the RCP2.6 scenario, which considers an expansion of biofuel croplands as a climate mitigation option. The underlying similarity among all models is the loss in global land carbon storage due to land-use changes.

Ocean Heat Transport and Its Projected Change in CanESM2

Abstract The meridional ocean heat transport (MOHT), its seasonal variability, and projected changes simulated by the second generation Canadian Earth System Model (CanESM2) are presented. The global mean MOHT is within the uncertainty of the observational estimates. However, a correct simulation of the MOHT for individual ocean basins is more challenging, and the Atlantic MOHT south of 30°N is underestimated. The partitioning of the MOHT into the overturning and gyre components is generally consistent with such partitioning in an observationally optimized ocean model. At low latitudes, the time-mean MOHT is dominated by its overturning component, whereas in the Southern Ocean and, especially, in the subpolar North Atlantic, it is the gyre component that plays a more important role. In the projected warmer climates, CanESM2 simulates a weakening of the poleward MOHT essentially in both hemispheres. The projected MOHT changes are largely determined by the overturning component, except in the subpolar Atlantic where it is dominated by the gyre component. Consistent with (the limited number of) previous studies, the seasonal variability of the MOHT is large and is mostly driven by the seasonal variability of the meridional Ekman transport. In the simulated warmer climates, the seasonal cycle of the MOHT is projected to change, mostly in the tropics and also in the Southern Hemisphere midlatitudes. The eddy contribution to the MOHT is broadly consistent with that in the observationally optimized eddy-permitting model. However, in the tropics a significant fraction of the eddy energy is converted back to the mean circulation, and the heat transports due to the parameterized and permitted eddies differ.

Improved constraints on 21st‐century warming derived using 160 years of temperature observations

Projections of 21st century warming may be derived by using regression‐based methods to scale a model's projected warming up or down according to whether it under‐ or over‐predicts the response to anthropogenic forcings over the historical period. Here we apply such a method using near surface air temperature observations over the 1851–2010 period, historical simulations of the response to changing greenhouse gases, aerosols and natural forcings, and simulations of future climate change under the Representative Concentration Pathways from the second generation Canadian Earth System Model (CanESM2). Consistent with previous studies, we detect the influence of greenhouse gases, aerosols and natural forcings in the observed temperature record. Our estimate of greenhouse‐gas‐attributable warming is lower than that derived using only 1900–1999 observations. Our analysis also leads to a relatively low and tightly‐constrained estimate of Transient Climate Response of 1.3–1.8°C, and relatively low projections of 21st‐century warming under the Representative Concentration Pathways. Repeating our attribution analysis with a second model (CNRM‐CM5) gives consistent results, albeit with somewhat larger uncertainties.