Pre-industrial Climate Research Articles

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region

Tibetan permafrost largely formed during the late Pleistocene glacial period and shrank in the Holocene Thermal Maximum period. Quantifying the impacts of paleoclimatic extremes on soil carbon stock can shed light on the vulnerability of permafrost carbon in the future. Here, we synthesize data from 1114 sites across the Tibetan permafrost region to report that paleoclimate is more important than modern climate in shaping current permafrost carbon distribution, and its importance increases with soil depth, mainly through forming the soilʼs physiochemical properties. We derive a new estimate of modern soil carbon stock to 3 m depth by including the paleoclimate effects, and find that the stock ({mathrm{36}}{mathrm{.6}}_{{mathrm{ - 2}}{mathrm{.4}}}^{{mathrm{ + 2}}.3} PgC) is triple that predicted by ecosystem models (11.5 ± 4.2 s.e.m PgC), which use pre-industrial climate to initialize the soil carbon pool. The discrepancy highlights the urgent need to incorporate paleoclimate information into model initialization for simulating permafrost soil carbon stocks.

Evidence of crop production losses in West Africa due to historical global warming in two crop models

Achieving food security goals in West Africa will depend on the capacity of the agricultural sector to feed the rapidly growing population and to moderate the adverse impacts of climate change. Indeed, a number of studies anticipate a reduction of the crop yield of the main staple food crops in the region in the coming decades due to global warming. Here, we found that crop production might have already been affected by climate change, with significant yield losses estimated in the historical past. We used a large ensemble of historical climate simulations derived from an atmospheric general circulation model and two process-based crop models, SARRA-H and CYGMA, to evaluate the effects of historical climate change on crop production in West Africa. We generated two ensembles of 100 historical simulations of yields of sorghum and millet corresponding to two climate conditions for each crop model. One ensemble is based on a realistic simulation of the actual climate, while the other is based on a climate simulation that does not account for human influences on climate systems (that is, the non-warming counterfactual climate condition). We found that the last simulated decade, 2000–2009, is approximately 1 °C warmer in West Africa in the ensemble accounting for human influences on climate, with more frequent heat and rainfall extremes. These altered climate conditions have led to regional average yield reductions of 10–20% for millet and 5–15% for sorghum in the two crop models. We found that the average annual production losses across West Africa in 2000–2009 associated with historical climate change, relative to a non-warming counterfactual condition (that is, pre-industrial climate), accounted for 2.33–4.02 billion USD for millet and 0.73–2.17 billion USD for sorghum. The estimates of production losses presented here can be a basis for the loss and damage associated with climate change to date and useful in estimating the costs of the adaptation of crop production systems in the region.

Simulating the climate response to atmospheric oxygen variability in the Phanerozoic: a focus on the Holocene, Cretaceous and Permian

Abstract. The amount of dioxygen (O2) in the atmosphere may have varied from as little as 5 % to as much as 35 % during the Phanerozoic eon (54 Ma–present). These changes in the amount of O2 are large enough to have led to changes in atmospheric mass, which may alter the radiative budget of the atmosphere, leading to this mechanism being invoked to explain discrepancies between climate model simulations and proxy reconstructions of past climates. Here, we present the first fully 3-D numerical model simulations to investigate the climate impacts of changes in O2 under different climate states using the coupled atmosphere–ocean Hadley Centre Global Environmental Model version 3 (HadGEM3-AO) and Hadley Centre Coupled Model version 3 (HadCM3-BL) models. We show that simulations with an increase in O2 content result in increased global-mean surface air temperature under conditions of a pre-industrial Holocene climate state, in agreement with idealised 1-D and 2-D modelling studies. We demonstrate the mechanism behind the warming is complex and involves a trade-off between a number of factors. Increasing atmospheric O2 leads to a reduction in incident shortwave radiation at the Earth's surface due to Rayleigh scattering, a cooling effect. However, there is a competing warming effect due to an increase in the pressure broadening of greenhouse gas absorption lines and dynamical feedbacks, which alter the meridional heat transport of the ocean, warming polar regions and cooling tropical regions. Case studies from past climates are investigated using HadCM3-BL and show that, in the warmest climate states in the Maastrichtian (72.1–66.0 Ma), increasing oxygen may lead to a temperature decrease, as the equilibrium climate sensitivity is lower. For the Asselian (298.9–295.0 Ma), increasing oxygen content leads to a warmer global-mean surface temperature and reduced carbon storage on land, suggesting that high oxygen content may have been a contributing factor in preventing a “Snowball Earth” during this period of the early Permian. These climate model simulations reconcile the surface temperature response to oxygen content changes across the hierarchy of model complexity and highlight the broad range of Earth system feedbacks that need to be accounted for when considering the climate response to changes in atmospheric oxygen content.

Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests

AbstractChanging climate conditions impact ecosystem dynamics and have local to global impacts on water and carbon cycles. Many processes in dynamic vegetation models (DVMs) are parameterized, and the unknown/unknowable parameter values introduce uncertainty that has rarely been quantified in projections of forced changes. In this study, we identify processes and parameters that introduce the largest uncertainties in the vegetation state simulated by the DVM Top‐down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) coupled to a regional climate model. We adjust parameters simultaneously in an ensemble of equilibrium vegetation simulations and use statistical emulation to explore sensitivities to, and interactions among, parameters. We find that vegetation distribution is most sensitive to parameters related to carbon allocation and competition. Using a suite of statistical emulators, we identify regions of parameter space that reduce the error in modeled forest cover by 31±9%. We then generate large initial atmospheric condition ensembles with 10 improved DVM parameterizations under preindustrial, contemporary, and future climate conditions to assess uncertainty in the forced response due to parameterization. We find that while most parameterizations agree on the direction of future vegetation transitions in the western United States, the magnitude varies considerably: for example, in the northwest coast the expansion of broadleaf trees and corresponding decline of needleleaf trees ranges from 4 to 28% across 10 DVM parameterizations under projected future climate conditions. We demonstrate that model parameterization contributes to uncertainty in vegetation transition and carbon cycle feedback under nonstationary climate conditions, which has important implications for carbon stocks, ecosystem services, and climate feedback.

Response of vegetation cover to CO2 and climate changes between Last Glacial Maximum and pre-industrial period in a dynamic global vegetation model

Climate and atmospheric CO2 strongly influence the vegetation distribution and the terrestrial carbon storage. Process-based dynamic global vegetation models (DGVM) are important tools for simulating past vegetation dynamics and carbon cycle; yet the link between spatial gradients of climate and vegetation cover in geological past has received less attention. In this study, we simulate the distribution of vegetation under three CO2 levels for two climate states, the Last Glacial Maximum (LGM) and Pre-industrial (PI) climate with fire activated or deactivated using the ORCHIDEE-MICT DGVM. Results show that elevated CO2 and warmer climate promote global total tree cover but the impacts are different between forest biomes. Regional tree cover is highly regulated by mean annual precipitation (MAP) especially in the tropics, and by temperature for the boreal-arctic tree line. Based on quantile nonlinear regressions, we analyze the MAP threshold at which maximum tree cover is reached. This threshold is significantly reduced with elevated CO2 for tropical and temperate trees. With higher CO2, increased tree cover leads to reduced fire ignition and burned area, and provides a positive feedback to tree cover, especially in Africa. Besides, in our model, increasing CO2-induced enhancement of gross primary productivity (GPP) is more prominent for tropical trees than for temperate and boreal trees, and for dry regions than wet regions. This difference explains why CO2 is the major factor influencing forest cover in the tropics. It also highlights that special attention should be paid to collect paleo-vegetation data across savannas-forest transition in dry regions.

The Medieval Climate Anomaly in Oceania

Temperatures in Oceania have risen by 0.5–1 °C over the past 100 years, resulting in significant retreat of New Zealand’s glaciers as an example. To better understand natural and anthropogenic contributions to this warming process, the observed climatic change must be placed in a longer-term palaeotemperature context. Of interest is the Medieval Climate Anomaly (MCA, 1000–1200 AD), a recognized period of natural pre-industrial climate change, associated with marked temperature and hydroclimatic variability that is best known from the Northern Hemisphere. Temperature reconstructions for Oceania were traditionally based on two classical tree ring series. Here, we enlarge the Oceania reference data set with another 13 published temperature reconstructions from SE Australia, New Zealand, and West Papua. These are based on a variety of proxy types and help to geographically and methodologically augment the regional palaeoclimate database. The proxy series have been thoroughly compared and the MCA trends palaeoclimatologically mapped. Ten out of the 15 sites show a relatively warm MCA, compared to the last 1500 years, with warming generally occurring in the envelope period 900–1500 AD. In some sites of SE Australia and at the west coast of New Zealand’s South Island, warming appears to be delayed by 200–300 years. The end of the medieval warming at around 1500 AD occurred about two centuries later than on most other continents, suggesting a possible interhemispheric climate lag mechanism possibly involving deep-water circulation. Likely drivers for the medieval warming in Oceania are atmospheric-ocean cycles such as the Southern Annular Mode and El Niño-Southern Oscillation, in combination with solar activity changes. MCA palaeotemperature data are still lacking for large parts of Oceania, namely the arid and tropical parts of Australia, Micronesia, central and northern Polynesia, as well as central and eastern Melanesia, highlighting the need for future research.

On the Role of the Atmospheric Energy Transport in 2 × CO2–Induced Polar Amplification in CESM1

AbstractA doubling of the atmospheric CO2 content leads to global warming that is amplified in the polar regions. The CO2 forcing also leads to a change of the atmospheric energy transport. This transport change affects the local warming induced by the CO2 forcing. Using the Community Earth System Model (CESM), the direct response to the transport change is investigated. Divergences of the transport change associated with a CO2 doubling are implemented as a forcing in the 1 × CO2 preindustrial control climate. This forcing is zero in the global mean. In response to a CO2 increase in CESM, the northward atmospheric energy transport decreases at the Arctic boundary. However, the transport change still leads to a warming of the Arctic. This is due to a shift between dry static and latent transport components, so that although the dry static transport decreases, the latent transport increases at the Arctic boundary, which is consistent with other model studies. Because of a greenhouse effect associated with the latent transport, the cooling caused by a change of the dry static component is more than compensated for by the warming induced by the change of the latent transport. Similar results are found for the Antarctic region, but the transport change is larger in the Southern Hemisphere than in its northern counterpart. As a consequence, the Antarctic region warms to the extent that this warming leads to global warming that is likely enhanced by the surface albedo feedback associated with considerable ice retreat in the Southern Hemisphere.

Modeling the late Pliocene global monsoon response to individual boundary conditions

The late Pliocene is a pre-Quaternary warming period compared to the preindustrial period. Here, based on the updated PRISM4 (Pliocene Research, Interpretation and Synoptic Mapping version 4) boundary conditions from the Pliocene Model Intercomparison Project phase 2 (PlioMIP2), seven experiments are conducted to simulate the global monsoon in the late Pliocene interglacial period and further investigate the impacts from changes in the individual boundary conditions by using the Community Earth System Model (CESM 1.0.4). The simulated late Pliocene interglacial climate is generally warmer and wetter than the preindustrial period climate, with an expanded monsoon domain, particularly in North Africa, Asia and Australia. The differences in topography, vegetation and lakes outside of Greenland and Antarctica account for the greatest contribution to monsoon changes. Moreover, orbital parameter variations further significantly affect monsoon domains and lead to significant fluctuations in monsoon precipitation and winds on the orbital scale, and the changed magnitude is even larger than that between the late Pliocene and preindustrial period when orbital forcing is not considered.

Global vegetation distribution driving factors in two Dynamic Global Vegetation Models of contrasting complexities

Abstract This study compares the dynamic vegetation response in two Dynamic Global Vegetation Models (DGVMs) with contrasting processes complexity to changes in climate and atmospheric CO2. We consider observed pre-industrial climates and four different simulated climate change states relative to preindustrial conditions: the mid-Holocene (6 ka), the pre-industrial state with halved CO2 levels (140 ppm), doubled CO2 (560 ppm), and quadrupled CO2 (1120 ppm). The two DVGMs are LPJ-GUESS and VECODE. The input climate is derived from an earth system model of intermediate complexity (iLOVECLIM). We evaluate the sensitivities of these two DGVMs to changing climate and CO2 levels and assess the impact of their respective complexity on these sensitivities. Our results show that both DGVMs yield results consistent with the broad features of pre-industrial vegetation dynamics and changes in vegetation from mid-Holocene to pre-industrial. They also agree with the patterns of vegetation responses to the more extreme varying CO2 scenarios, yet with stronger magnitudes in LPJ-GUESS than in VECODE; in particular, large uncertainties are associated with the response of tropical vegetation to varying CO2 levels. LPJ-GUESS simulates stronger positive responses of global net primary production (NPP) to elevated CO2 levels than VECODE, particularly in tropical regions. The increase in global NPP differs by 8% between the two DGVMs under 2*CO2 scenarios. Also, LPJ-GUESS simulates tropical vegetation sensitivities, defined here as the changes in tree-cover per degree of temperature anomaly, varying from 0.5 (°C−1), 0.25 (°C−1) to 0.15 (°C−1) under ½*CO2, 2*CO2, and 4*CO2 scenarios. In VECODE these values are around 0.05 (°C−1) for all scenarios. The higher sensitivity of LPJ-GUESS to CO2 concentration levels is likely related to the inclusion of more detailed ecophysiological processes. The two DGVMs' different complexity of eco-physiological processes also impacts on vegetation requirements for rainfall due to the physiological effects that more efficient water use of vegetation is facilitated under elevated atmospheric CO2 concentration. The sensitivity of global Leaf Area Index (LAI) in the two DGVMs decreases with the increasing atmospheric CO2 from pre-industrial level to 4*CO2 scenario. The uncertainties of vegetation simulations are mainly contributed by the tropical vegetation response to climate and CO2 concentration due to the inclusion of ecosystem processes in both DGVMs and the scheme of vegetation classification. Based on our results, we recommend to use a standard set of vegetation types and to set up systematic simulations detecting the range of vegetation sensitivity to varying CO2 and climate forcing when inter-comparing different DGVMs.

Limited capacity of tree growth to mitigate the global greenhouse effect under predicted warming

It is generally accepted that animal heartbeat and lifespan are often inversely correlated, however, the relationship between productivity and longevity has not yet been described for trees growing under industrial and pre-industrial climates. Using 1768 annually resolved and absolutely dated ring width measurement series from living and dead conifers that grew in undisturbed, high-elevation sites in the Spanish Pyrenees and the Russian Altai over the past 2000 years, we test the hypothesis of grow fast—die young. We find maximum tree ages are significantly correlated with slow juvenile growth rates. We conclude, the interdependence between higher stem productivity, faster tree turnover, and shorter carbon residence time, reduces the capacity of forest ecosystems to store carbon under a climate warming-induced stimulation of tree growth at policy-relevant timescales.

What Formed the North-South Contrasting Pattern of Summer Rainfall Changes over Eastern China?

The south-flood-north-drought pattern of summer rainfall change over eastern China has been attributed to external forcing (greenhouse gas concentration and aerosol emission changes) and a coupled ocean-atmosphere mode (the Pacific Decadal Oscillation; PDO). Here, we investigate the possibility whether the north-south contrasting pattern of summer rainfall change may occur without external forcing and the PDO effect. Analysis of preindustrial and historical climate model simulations and climatological sea surface temperature–forced atmospheric model simulations identified the north-south pattern of summer rainfall changes under constant external forcing and without the PDO signal. This suggests a possible role of atmospheric internal variability. The decadal rainfall change pattern appears as a manifestation of change in the frequency of occurrence of rainfall anomaly distribution from one specific pattern to the other between two neighboring periods. The external forcing and the ocean-atmosphere coupled mode are not necessary conditions for the occurrence of the north-south pattern of summer rainfall changes over eastern China.

Agricultural non-CO2 emission reduction potential in the context of the 1.5 °C target

Agricultural methane and nitrous oxide emissions represent around 10–12% of total anthropogenic GHG emissions and have a key role to play in achieving a 1.5 °C (above pre-industrial) climate stabilization target. Using a multi-model assessment approach, we quantify the potential contribution of agriculture to the 1.5 °C target and decompose the mitigation potential by emission source, region and mitigation mechanism. The results show that the livestock sector will be vital to achieve emission reductions consistent with the 1.5 °C target mainly through emission-reducing technologies or structural changes. Agriculture may contribute emission reductions of 0.8–1.4 Gt of CO2-equivalent (CO2e) yr−1 at just US$20 per tCO2e in 2050. Combined with dietary changes, emission reductions can be increased to 1.7–1.8 GtCO2e yr−1. At carbon prices compatible with the 1.5 °C target, agriculture could even provide average emission savings of 3.9 GtCO2e yr−1 in 2050, which represents around 8% of current GHG emissions. Agricultural CH4 and N2O emissions represent around 11% of total anthropogenic GHGs. Here agriculture mitigation potentials are quantified, in the context of the 1.5 °C target, and decomposed by emission source, region and mitigation mechanism.

Link between the North Atlantic Oscillation and the surface mass balance components of the Greenland Ice Sheet under preindustrial and last interglacial climates: a study with a coupled global circulation model

Abstract. The relationship between the surface mass balance (SMB) components (accumulation and melting) of the Greenland Ice Sheet (GrIS) and the North Atlantic Oscillation (NAO) is examined from numerical simulations performed with a new atmospheric stretched grid configuration of the Centre National de Recherches Météorologiques Coupled Model (CNRM-CM) version 5.2 under three periods: preindustrial climate, a warm phase (early Eemian, 130 ka BP) and a cool phase (late Eemian, 115 ka BP) of the last interglacial. The horizontal grid of the atmospheric component of CNRM-CM5.2 is stretched from the tilted pole on Baffin Bay (72∘ N, 65∘ W) in order to obtain a higher spatial resolution on Greenland. The correlation between simulated SMB anomalies averaged over Greenland and the NAO index is weak in winter and significant in summer (about 0.6 for the three periods). In summer, spatial correlations between the NAO index and SMB components display different patterns from one period to another. These differences are analyzed in terms of the respective influence of the positive and negative phases of the NAO on accumulation and melting. Accumulation in south Greenland is significantly correlated with the positive (negative) phase of the NAO in a warm (cold) climate. Under preindustrial and 115 ka BP climates, melting along the margins is more correlated with the positive phase of the NAO than with its negative phase, whereas at 130 ka BP it is more correlated with the negative phase of the NAO in north and northeast Greenland.

Improved Aerosol Processes and Effective Radiative Forcing in HadGEM3 and UKESM1

AbstractAerosol processes and, in particular, aerosol‐cloud interactions cut across the traditional physical‐Earth system boundary of coupled Earth system models and remain one of the key uncertainties in estimating anthropogenic radiative forcing of climate. Here we calculate the historical aerosol effective radiative forcing (ERF) in the HadGEM3‐GA7 climate model in order to assess the suitability of this model for inclusion in the UK Earth system model, UKESM1. The aerosol ERF, calculated for the year 2000 relative to 1850, is large and negative in the standard GA7 model leading to an unrealistic negative total anthropogenic forcing over the twentieth century. We show how underlying assumptions and missing processes in both the physical model and aerosol parameterizations lead to this large aerosol ERF. A number of model improvements are investigated to assess their impact on the aerosol ERF. These include an improved representation of cloud droplet spectral dispersion, updates to the aerosol activation scheme, and black carbon optical properties. One of the largest contributors to the aerosol forcing uncertainty is insufficient knowledge of the preindustrial aerosol climate. We evaluate the contribution of uncertainties in the natural marine emissions of dimethyl sulfide and organic aerosol to the ERF. The combination of model improvements derived from these studies weakens the aerosol ERF by up to 50% of the original value and leads to a total anthropogenic historical forcing more in line with assessed values.

Role of Ocean Model Formulation in Climate Response Uncertainty

AbstractOceanic heat uptake (OHU) is a significant source of uncertainty in both the transient and equilibrium responses to increasing the planetary radiative forcing. OHU differs among climate models and is related in part to their representation of vertical and lateral mixing. This study examines the role of ocean model formulation—specifically the choice of the vertical coordinate and the strength of the background diapycnal diffusivity Kd—in the millennial-scale near-equilibrium climate response to a quadrupling of atmospheric CO2. Using two fully coupled Earth system models (ESMs) with nearly identical atmosphere, land, sea ice, and biogeochemical components, it is possible to independently configure their ocean model components with different formulations and produce similar near-equilibrium climate responses. The SST responses are similar between the two models (r2 = 0.75, global average ~4.3°C) despite their initial preindustrial climate mean states differing by 0.4°C globally. The surface and interior responses of temperature and salinity are also similar between the two models. However, the Atlantic meridional overturning circulation (AMOC) responses are different between the two models, and the associated differences in ventilation and deep-water formation have an impact on the accumulation of dissolved inorganic carbon in the ocean interior. A parameter sensitivity analysis demonstrates that increasing the amount of Kd produces very different near-equilibrium climate responses within a given model. These results suggest that the impact of the ocean vertical coordinate on the climate response is small relative to the representation of subgrid-scale mixing.

Atmospheric processing of iron in mineral and combustion aerosols: development of an intermediate-complexity mechanism suitable for Earth system models

Abstract. Atmospheric processing of iron in dust and combustion aerosols is simulated using an intermediate-complexity soluble iron mechanism designed for Earth system models. The solubilization mechanism includes both a dependence on aerosol water pH and in-cloud oxalic acid. The simulations of size-resolved total, soluble and fractional iron solubility indicate that this mechanism captures many but not all of the features seen from cruise observations of labile iron. The primary objective was to determine the extent to which our solubility scheme could adequately match observations of fractional iron solubility. We define a semi-quantitative metric as the model mean at points with observations divided by the observational mean (MMO). The model is in reasonable agreement with observations of fractional iron solubility with an MMO of 0.86. Several sensitivity studies are performed to ascertain the degree of complexity needed to match observations; including the oxalic acid enhancement is necessary, while different parameterizations for calculating model oxalate concentrations are less important. The percent change in soluble iron deposition between the reference case (REF) and the simulation with acidic processing alone is 63.8 %, which is consistent with previous studies. Upon deposition to global oceans, global mean combustion iron solubility to total fractional iron solubility is 8.2 %; however, the contribution of fractional iron solubility from combustion sources to ocean basins below 15∘ S is approximately 50 %. We conclude that, in many remote ocean regions, sources of iron from combustion and dust aerosols are equally important. Our estimates of changes in deposition of soluble iron to the ocean since preindustrial climate conditions suggest roughly a doubling due to a combination of higher dust and combustion iron emissions along with more efficient atmospheric processing.

Crop production losses associated with anthropogenic climate change for 1981–2010 compared with preindustrial levels

The accumulated evidence indicates that agricultural production is being affected by climate change. However, most of the available evidence at a global scale is based on statistical regressions. Corroboration using independent methods, specifically process‐based modelling, is important for improving our confidence in the evidence. Here, we estimate the impacts of climate change on the global average yields of maize, rice, wheat and soybeans for 1981–2010, relative to the preindustrial climate. We use the results of factual and non‐warming counterfactual climate simulations performed with an atmospheric general circulation model that do and do not include anthropogenic forcings to climate systems, respectively, as inputs into a global gridded crop model. The results of a 100‐member ensemble climate and crop simulation suggest that climate change has decreased the global mean yields of maize, wheat and soybeans by 4.1, 1.8 and 4.5%, respectively, relative to the counterfactual simulation (preindustrial climate), even when carbon dioxide (CO2) fertilization and agronomic adjustments are considered. For rice, no significant impacts (−1.8%) are detected. The uncertainties in estimated yield impacts represented by the 90% probability interval that are derived from the ensemble members are −8.5 to +0.5% for maize, −8.4 to −0.5% for soybeans, −9.6 to +12.4% for rice and − 7.5 to +4.3% for wheat. Based on the yield impacts, the estimates of average annual production losses throughout the world for the most recent years of the study (2005–2009) account for 22.3 billion USD (B$) for maize, 6.5 B$ for soybeans, 0.8 B$ for rice and 13.6 B$ for wheat. Our assessment confirms that climate change has modulated recent yields and led to production losses, and our adaptations to date have not been sufficient to offset the negative impacts of climate change, particularly at lower latitudes.

Investigation of the mechanisms leading to the 2017 Montreal flood

Significant flood damage occurred near Montreal in May 2017, as flow from the upstream Ottawa River basin (ORB) reached its highest levels in over 50 years. Analysis of observations and experiments performed with the fifth generation Canadian Regional Climate Model (CRCM5) show that much above average April precipitation over the ORB, a large fraction of which fell as rain on an existing snowpack, increased streamflow to near record-high levels. Subsequently, two heavy rainfall events affected the ORB in the first week of May, ultimately resulting in flooding. This heavy precipitation during April and May was linked to large-scale atmospheric features. Results from sensitivity experiments with CRCM5 suggest that the mass and distribution of the snowpack have a major influence on spring streamflow in the ORB. Furthermore, the importance of using an appropriate frozen soil parameterization when modelling spring streamflows in cold regions was confirmed. Event attribution using CRCM5 showed that events such as the heavy April 2017 precipitation accumulation over the ORB are between two and three times as likely to occur in the present-day climate as in the pre-industrial climate. This increase in the risk of heavy precipitation is linked to increased atmospheric moisture due to warmer temperatures in the present-day climate, a direct consequence of anthropogenic emissions, rather than changes in rain-generating mechanisms or circulation patterns. Warmer temperatures in the present-day climate also reduce early-spring snowpack in the ORB, offsetting the increase in rainfall and resulting in no discernible change to the likelihood of extreme surface runoff.

Glacial Inception in Marine Isotope Stage 19: An Orbital Analog for a Natural Holocene Climate

The Marine Isotope Stage 19c (MIS19c) interglaciation is regarded as the best orbital analog to the Holocene. The close of MIS19c (~777,000 years ago) thus serves as a proxy for a contemporary climate system unaffected by humans. Our global climate model simulation driven by orbital parameters and observed greenhouse gas concentrations at the end of MIS19c is 1.3 K colder than the reference pre-industrial climate of the late Holocene (year 1850). Much stronger cooling occurs in the Arctic, where sea ice and year-round snow cover expand considerably. Inferred regions of glaciation develop across northeastern Siberia, northwestern North America, and the Canadian Archipelago. These locations are consistent with evidence from past glacial inceptions and are favored by atmospheric circulation changes that reduce ablation of snow cover and increase accumulation of snowfall. Particularly large buildups of snow depth coincide with presumed glacial nucleation sites, including Baffin Island and the northeast Canadian Archipelago. These findings suggest that present-day climate would be susceptible to glacial inception if greenhouse gas concentrations were as low as they were at the end of MIS 19c.

Simultaneous Regional Detection of Land‐Use Changes and Elevated GHG Levels: The Case of Spring Precipitation in Tropical South America

AbstractA decline in dry season precipitation over tropical South America has a large impact on ecosystem health of the region. Results here indicate that the magnitude of negative trends in dry season precipitation in the past decades exceeds the estimated range of trends due to natural variability of the climate system defined in both the preindustrial climate and during the 850–1850 millennium. The observed drying is associated with an increase in vapor pressure deficit. The univariate detection analysis shows that greenhouse gas (GHG) forcing has a systematic influence in negative 30‐year trends of precipitation ending in 1998 and later on. The bivariate attribution analysis demonstrates that forcing by elevated GHG levels and land‐use change are attributed as key causes for the observed drying during 1983–2012 over the southern Amazonia and central Brazil. We further show that the effect of GS signal (GHG and sulfate aerosols) based on RCP4.5 scenario already has a detectable influence in the observed drying. Thus, we suggest that the recently observed “drier dry season” is a feature which will continue and intensify in the course of unfolding anthropogenic climate change. Such change could have profound societal and ecosystem impacts over the region.