Earth System Model Of Intermediate Complexity Research Articles

The Stability of the AMOC During Heinrich Events Is Not Dependent on the AMOC Strength in an Intermediate Complexity Earth System Model Ensemble

AbstractPrevious studies that used Earth system models of intermediate complexity showed that stronger background winds drove a more vigorous and stable Atlantic Meridional Overturning Circulation (AMOC), while those with weaker winds had a more sluggish and unstable AMOC. In other studies, ensembles under vertical mixing uncertainty showed the opposite effect, where the simulations with a stronger AMOC were more unstable. To tackle this conundrum, we produce a model ensemble featuring uncertainties related to wind forcing and vertical mixing to understand the role of feedbacks on the AMOC stability. We show that the stability of the AMOC is not influenced by vertical mixing and the AMOC strength, and rather, it is determined by the strength of the Northern Hemisphere winds. Paleoproxies indicate an AMOC shutdown during the last Heinrich Stadial. Our comparisons to sea surface temperature proxies show a better fit with the simulations under a stable AMOC, which corresponds to a forced off‐state. The sign of the AMOC‐driven freshwater transport in the South Atlantic, which is regarded as an index for its stability, is shown not to be an absolute measure, although its evolution agrees with the salt advection feedback.

How parameter specification of an Earth system model of intermediate complexity influences its climate simulations

Earth system models (ESMs) consist of parameterization schemes based on one’s perception of how the Earth system functions. A typical ESM contains a large number of parameters (i.e., the constants and exponents in the parameterization schemes) whose specification can have a significant impact on an ESM’s simulation capabilities. Sensitivity analyses (SA) is an important tool for assessing how parameter specification influences model simulations. In this study, we used an Earth system model of intermediate complexity (EMIC)—LOVECLIM as an example to illustrate how SA methods can be used to identify the most sensitive parameters that control the simulations of several key global water and energy cycle variables, including global annual mean absolute surface air temperature (TG), precipitation and evaporation over the land and over the oceans (PL, PO, EL, EO), and land runoff (RL). We also demonstrate how judiciously specifying model parameters can improve the simulations of those variables. Three SA methods MARS, RF, and sparse PCE-based Sobol’ method were used to evaluate a pool of 25 adjustable parameters chosen from land, atmosphere, and ocean components of LOVECLIM and their results were intercompared to ensure robustness of the results. It is found that with different parameter specification, TG can vary from 10 to 20 °C, and the values of PL, PO, EL, and EO can change by more than 100%. An interesting observation is that the value of RL vary from 13,000 to 35,000 km3, far below the observed climatological value of 40,000 km3, indicating a model structural deficiency in representing land runoff by LOVECLIM which must be corrected to obtain more reasonable global water budgets. We also note that parameter sensitivities are significantly different at different latitudes. Finally, we showed that global water and energy cycle simulations can be significantly improved by even a crude automatic parameter tuning, indicating that parameter optimization can be a viable way to improve ESM climate simulations. The results from this study should help us to understand the parameter uncertainty of a full-scale ESM.

Asymmetric dynamical ocean responses in warming icehouse and cooling greenhouse climates

Warm periods in Earth’s history tend to cool more slowly than cool periods warm. Here we explore initial differences in how the global ocean takes up and gives up heat and carbon in forced rapid warming and cooling climate scenarios. We force an intermediate-complexity earth system model using two atmospheric CO2 scenarios. A ramp-up (1% per year increase in atmospheric CO2 for 150 years) starts from an average global CO2 concentration of 285 ppm to represent warming of an icehouse climate. A ramp-down (1% per year decrease in atmospheric CO2 for 150 years) starts from an average global CO2 concentration of 1257 ppm to represent cooling of a greenhouse climate. Atmospheric CO2 is then held constant in each simulation and the model is integrated an additional 350 years. The ramp-down simulation shows a weaker response of surface air temperature to changes in radiative forcing relative to the ramp-up scenario. This weaker response is due to a relatively large and fast release of heat from the ocean to the atmosphere. This asymmetry in heat exchange in cooling and warming scenarios exists mainly because of differences in the response of the ocean circulation to forcing. In the ramp-up, increasing stratification and weakening of meridional overturning circulation slows ocean heat and carbon uptake. In the ramp-down, cooling accelerates meridional overturning and deepens vertical mixing, accelerating the release of heat and carbon stored at depth. Though idealized, our experiments offer insight into differences in ocean dynamics in icehouse and greenhouse climate transitions.

LCice 1.0 – a generalized Ice Sheet System Model coupler for LOVECLIM version 1.3: description, sensitivities, and validation with the Glacial Systems Model (GSM version D2017.aug17)

Abstract. We have coupled an Earth system model of intermediate complexity (LOVECLIM) to the Glacial Systems Model (GSM) using the LCice 1.0 coupler. The coupling scheme is flexible enough to enable asynchronous coupling between any glacial cycle ice sheet model and (with some code work) any Earth system model of intermediate complexity (EMIC). This coupling includes a number of interactions between ice sheets and climate that are often neglected: dynamic meltwater runoff routing, novel downscaling for precipitation that corrects orographic forcing to the higher resolution ice sheet grid (“advective precipitation”), dynamic vertical temperature gradient, and ocean temperatures for sub-shelf melt. The sensitivity of the coupled model with respect to the selected parameterizations and coupling schemes is investigated. Each new coupling feature is shown to have a significant impact on ice sheet evolution. An ensemble of runs is used to explore the behaviour of the coupled model over a set of 2000 parameter vectors using present-day (PD) initial and boundary conditions. The ensemble of coupled model runs is compared against PD reanalysis data for atmosphere (2 m temperature, precipitation, jet stream, and Rossby number of jet), ocean (sea ice and Atlantic Meridional Overturning Circulation – AMOC), and Northern Hemisphere ice sheet thickness and extent. The parameter vectors are then narrowed by rejecting model runs (1700 CE to present) with regional land ice volume changes beyond an acceptance range. The selected subset forms the basis for ongoing work to explore the spatial–temporal phase space of the last two glacial cycles.

Hazards of decreasing marine oxygen: the near-term and millennial-scale benefits of meeting the Paris climate targets

Abstract. Ocean deoxygenation is recognized as key ecosystem stressor of the future ocean and associated climate-related ocean risks are relevant for current policy decisions. In particular, benefits of reaching the ambitious 1.5 ∘C warming target mentioned by the Paris Agreement compared to higher temperature targets are of high interest. Here, we model oceanic oxygen, warming and their compound hazard in terms of metabolic conditions on multi-millennial timescales for a range of equilibrium temperature targets. Scenarios where radiative forcing is stabilized by 2300 are used in ensemble simulations with the Bern3D Earth System Model of Intermediate Complexity. Transiently, the global mean ocean oxygen concentration decreases by a few percent under low forcing and by 40 % under high forcing. Deoxygenation peaks about a thousand years after stabilization of radiative forcing and new steady-state conditions are established after AD 8000 in our model. Hypoxic waters expand over the next millennium and recovery is slow and remains incomplete under high forcing. Largest transient decreases in oxygen are projected for the deep sea. Distinct and near-linear relationships between the equilibrium temperature response and marine O2 loss emerge. These point to the effectiveness of the Paris climate target in reducing marine hazards and risks. Mitigation measures are projected to reduce peak decreases in oceanic oxygen inventory by 4.4 % ∘C−1 of avoided equilibrium warming. In the upper ocean, the decline of a metabolic index, quantified by the ratio of O2 supply to an organism's O2 demand, is reduced by 6.2 % ∘C−1 of avoided equilibrium warming. Definitions of peak hypoxia demonstrate strong sensitivity to additional warming. Volumes of water with less than 50 mmol O2 m−3, for instance, increase between 36 % and 76 % ∘C−1 of equilibrium temperature response. Our results show that millennial-scale responses should be considered in assessments of ocean deoxygenation and associated climate-related ocean risks. Peak hazards occur long after stabilization of radiative forcing and new steady-state conditions establish after AD 8000.

The importance of snow albedo for ice sheet evolution over the last glacial cycle

Abstract. The surface energy and mass balance of ice sheets strongly depends on the amount of solar radiation absorbed at the surface, which is mainly controlled by the albedo of snow and ice. Here, using an Earth system model of intermediate complexity, we explore the role played by surface albedo for the simulation of glacial cycles. We show that the evolution of the Northern Hemisphere ice sheets over the last glacial cycle is very sensitive to the representation of snow albedo in the model. It is well known that the albedo of snow depends strongly on snow grain size and the content of light-absorbing impurities. Excluding either the snow aging effect or the dust darkening effect on snow albedo leads to an excessive ice build-up during glacial times and consequently to a failure in simulating deglaciation. While the effect of snow grain growth on snow albedo is well constrained, the albedo reduction due to the presence of dust in snow is much more uncertain because the light-absorbing properties of dust vary widely as a function of dust mineral composition. We also show that assuming slightly different optical properties of dust leads to very different ice sheet and climate evolutions in the model. Conversely, ice sheet evolution is less sensitive to the choice of ice albedo in the model. We conclude that a proper representation of snow albedo is a fundamental prerequisite for a successful simulation of glacial cycles.

The dynamical core of the Aeolus 1.0 statistical–dynamical atmosphere model: validation and parameter optimization

Abstract. We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical–dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies. Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0. We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983–2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño–Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function. With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation. The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower troposphere mass flux show good results in particular in the Northern Hemisphere. In the Southern Hemisphere, the model tends to produce too-weak zonal-mean zonal winds and a too-narrow Hadley circulation. We discuss possible reasons for these model biases as well as planned future model improvements and applications.

State‐Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

AbstractGrowing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state‐dependence. We present a comprehensive assessment of ECS state‐dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher‐forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D‐LPX model, this state‐dependence is mainly due to the weakening sea ice‐albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean‐mixing adjustments, state‐dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state‐dependence.

Lead–lag relationships between global mean temperature and the atmospheric CO2 content in dependence of the type and time scale of the forcing

By employing an Earth system model of intermediate complexity (EMIC) developed at the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS CM), mutual lags between global mean surface air temperature, T and the atmospheric CO2 content, q, in dependence of the type and time scale of the external forcing are explored. In the simulation, which follows the protocol of the Coupled Models Intercomparison Project, phase 5, T leads q for volcanically-induced climate variations. In contrast, T lags behind q for changes caused by anthropogenic CO2 emissions into the atmosphere. In additional idealized numerical experiments, driven by periodic external emissions of carbon dioxide into the atmosphere, T always lags behind q as expected. In contrast, if the model is driven by the periodic non-greenhouse radiative forcing, T leads q for the external forcing time scale ≤4×102yr, while q leads T at longer scales. The latter is an example that lagged correlations do not necessarily represent causal relationships in a system. This apparently counter-intuitive result, however, is a direct consequence of i) temperature sensitivity of the soil carbon stock (which decreases if climate is warmed and increases if climate is cooled), ii) conservation of total mass of carbon in the system in the absence of external carbon emissions, iii) increased importance of the oceanic branch of the carbon cycle at longer time scales. The results obtained with an EMIC are further interpreted with a conceptual Earth system model consisting of an energy balance climate model and a globally averaged carbon cycle model. The obtained results have implications to the empirical studies attempting to understand the origins of the contemporary climate change by applying lead–lag relationships to empirical data.

Global biogeophysical interactions between historical deforestation and climate through land surface albedo and interactive ocean

Deforestation is expanding and accelerating into the remaining areas of undisturbed forest, and the quality of the remaining forests is declining today. Assessing the climatic impacts of deforestation can help to rectify this alarming situation. In this paper, how historical deforestation may affect global climate through interactive ocean and surface albedo is examined using an Earth system model of intermediate complexity (EMIC). Control and anomaly integrations are performed for 1000 years. In the anomaly case, cropland is significantly expanded since AD 1700. The response of climate in deforested areas is not uniform between the regions. In the background of a global cooling of 0.08 °C occurring with cooler surface air above 0.4 °C across 30° N to 75° N from March to September, the surface albedo increase has a global cooling effect in response to global-scale replacement of forests by cropland, especially over northern mid-high latitudes. The northern mid-latitude (30° N–60° N) suffers a prominent cooling in June, suggesting that this area is most sensitive to cropland expansion through surface albedo. Most regions show a consistent trend between the overall cooling in response to historical deforestation and its resulting cooling due to surface albedo anomaly. Furthermore, the effect of the interactive ocean on shaping the climate response to deforestation is greater than that of prescribed SSTs in most years with a maximum spread of 0.05 °C. This difference is more prominent after year 1800 than that before due to the more marked deforestation. These findings show the importance of the land cover change and the land surface albedo, stressing the necessity to analyze other biogeophysical processes of deforestation using interactive ocean.

Extending the relationship between global warming and cumulative carbon emissions to multi-millennial timescales

The transient climate response to cumulative carbon emissions (TCRE) is a highly policy-relevant quantity in climate science. The TCRE suggests that peak warming is linearly proportional to cumulative carbon emissions and nearly independent of the emissions scenario. Here, we use simulations of the Earth System Model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to show that global mean surface temperature may increase by 0.5 °C after carbon emissions are stopped at 2 °C global warming, implying an increase in the coefficient relating global warming to cumulative carbon emissions on multi-centennial timescales. The simulations also suggest a 20% lower quota on cumulative carbon emissions allowed to achieve a policy-driven limit on global warming. ESM estimates from the Coupled Model Intercomparison Project Phase 5 (CMIP5–ESMs) qualitatively agree on this result, whereas Earth System Models of Intermediate Complexity (EMICs) simulations, used in the IPCC 5th assessment report to assess the robustness of TCRE on multi-centennial timescales, suggest a post-emissions decrease in temperature. The reason for this discrepancy lies in the smaller simulated realized warming fraction in CMIP5–ESMs, including GFDL ESM2M, than in EMICs when carbon emissions increase. The temperature response to cumulative carbon emissions can be characterized by three different phases and the linear TCRE framework is only valid during the first phase when carbon emissions increase. For longer timescales, when emissions tape off, two new metrics are introduced that better characterize the time-dependent temperature response to cumulative carbon emissions: the equilibrium climate response to cumulative carbon emissions and the multi-millennial climate response to cumulative carbon emissions.

Potential increasing dominance of heterotrophy in the global ocean

Autotrophy is largely resource-limited in the modern ocean. Paleo evidence indicates this was not necessarily the case in warmer climates, and modern observations as well as standard metabolic theory suggest continued ocean warming could shift global ecology towards heterotrophy, thereby reducing autotrophic nutrient limitation. Such a shift would entail strong nutrient recycling in the upper ocean and high rates of net primary production (NPP), yet low carbon export to the deep ocean and sediments. We demonstrate transition towards such a state in the early 22nd century as a response to business-as-usual representative concentration pathway forcing (RCP8.5) in an intermediate complexity Earth system model in three configurations; with and without an explicit calcifier phytoplankton class and calcite ballast model. In all models nutrient regeneration in the near-surface becomes an increasingly important driver of primary production. The near-linear relationship between changes in NPP and global sea surface temperature (SST) found over the 21st century becomes exponential above a 2–4 global mean SST change. This transition to a more heterotrophic ocean agrees roughly with metabolic theory.

A preliminary study to investigate the biogeophysical impact of desertification on climate based on different latitudinal bands

ABSTRACTDesertification is an international environmental challenge which poses a risk to portions of over 100 countries. Research into desertification and climate change has the potential to contribute to natural resources management and adaptation to climatic and other changes in Earth systems. An Earth system model of intermediate complexity (EMIC), the McGill Paleoclimate Model‐2 (MPM‐2) was used to explore the climatic biogeophysical effects of desertification in different latitude bands from 1700 to 2000 AD. It was found that latitudinal‐band desertification attributable to forest and grass removal caused global cooling, land surface albedo increasing and precipitation reduction in the Northern Hemisphere as well as heat transport increasing in global ocean. These results highlighted global climate reaction to local desertification and demonstrated that the location of the desertification projected a potentially differential impact on local and global climate. That was, desertification in 0°–15°N gave a somewhat minor effect on global and local climate; desertification in 45°–60°N caused a significant reduction in global temperature while desertification in 15°–30°N induced a prominent reduction in local temperature. In response to desertification, surface albedo change as a forcing was the dominant biogeophysical driver of climate over the Northern Hemisphere while precipitation change as a response was probably the primary driver of climate over the Southern Hemisphere. Overall, the regional desertification may cause a global climatic effect, especially concerning desert expansion along the 15°–30°N and 45°–60°N latitude bands, which led to a more prominent effect on the Earth's climate and even oceanic circulation. The results of this study provide useful information when comparing the effects of desertification in different latitude bands on climate.

Advancement toward coupling of the VAMPER permafrost model within the Earth system model <I>i</I>LOVECLIM (version 1.0): description and validation

Abstract. The VU Amsterdam Permafrost (VAMPER) permafrost model has been enhanced with snow thickness and active layer calculations in preparation for coupling within the iLOVECLIM Earth system model of intermediate complexity (EMIC). In addition, maps of basal heat flux and lithology were developed within ECBilt, the atmosphere component of iLOVECLIM, so that VAMPER may use spatially varying parameters of geothermal heat flux and porosity values. The enhanced VAMPER model is validated by comparing the simulated modern-day extent of permafrost thickness with observations. To perform the simulations, the VAMPER model is forced by iLOVECLIM land surface temperatures. Results show that the simulation which did not include the snow cover option overestimated the present permafrost extent. However, when the snow component is included, the simulated permafrost extent is reduced too much. In analyzing simulated permafrost depths, it was found that most of the modeled thickness values and subsurface temperatures fall within a reasonable range of the corresponding observed values. Discrepancies between simulated and observed permafrost depth distribution are due to lack of captured effects from features such as topography and organic soil layers. In addition, some discrepancy is also due to disequilibrium with the current climate, meaning that some observed permafrost is a result of colder states and therefore cannot be reproduced accurately with constant iLOVECLIM preindustrial forcings.

Global warming caused by afforestation in the Southern Hemisphere

Using an earth system model of intermediate complexity (EMIC), the McGill Paleoclimate Model-2 (MPM-2), this paper examines the climatic biogeophysical effects of afforestation in the southern hemisphere (SH) with a focus on land–atmosphere interactions and the modeling influence of the dynamic ocean in the background of the earth system. Increased forest cover affects the albedo feedback and the supply of water, which in turn influences temperature. These changes largely control the net impact of the SH afforestation based on latitudinal band. In response to afforestation in 0–15°S and 0–40°S, the local surface air temperature significantly increases at a maximum value around 5°S during autumn. This warming is attributed to decreased land surface albedo dominating over enhanced precipitation which is resulted from increased tree cover. Forest expansions in 15–30°S and 30–40°S induce diminished land surface albedo and precipitation locally, leading to a warming around 25°S during spring and a warming around 35°S in winter, respectively. The maximum differences in the modeled responses of afforestation on latitude band basis are seen to be 7–10 times larger for the same season. Our results show that capturing how and where biogeophysical changes due to forest expansion warm a specific region requires an accurate global simulation of afforestation geographically. This provides potential for further improving detection and attribution of regional afforestation effects. Furthermore, a dynamic ocean simulation results in a warming compared with a fixed one over most forcing originating areas in response to afforestation. We demonstrate that unless the dynamic ocean is considered we risk influenced conclusions regarding the drivers of temperature changes over regions of afforestation.

Contribution of surface roughness to simulations of historical deforestation

Surface roughness which partitions surface net radiation into energy fluxes is a key parameter for estimation of biosphere–atmosphere interactions and climate variability. An earth system model of intermediate complexity (EMIC), MPM-2, is used to derive the impact of surface roughness on climate from simulations of historical land cover change effects. The direct change in surface roughness leads to a global surface warming of 0.08°C through altering the turbulence in the boundary layer. The regional temperature response to surface roughness associated deforestation is very strong at northern mid-latitudes with a most prominent warming of 0.72°C around 50°N in the Eurasia continent during summer. They can be explained mainly as direct and indirect consequences of decreases in surface albedo and increases in precipitation in response to deforestation, although there are a few significant changes in precipitation. There is also a prominent warming of 0.25°C around 40°N in the North American continent. This study indicates that land surface roughness plays a significant role which is comparable with the whole land conversion effect in climate change. Therefore, further investigation of roughness–climate relationship is needed to incorporate these aspects.

Modeling in Earth system science up to and beyond IPCC AR5

Abstract Changes in the natural environment that are the result of human activities are becoming evident. Since these changes are interrelated and can not be investigated without interdisciplinary collaboration between scientific fields, Earth system science (ESS) is required to provide a framework for recognizing anew the Earth system as one composed of its interacting subsystems. The concept of ESS has been partially realized by Earth system models (ESMs). In this paper, we focus on modeling in ESS, review related findings mainly from the latest assessment report of the Intergovernmental Panel on Climate Change, and introduce tasks under discussion for the next phases of the following areas of science: the global nitrogen cycle, ocean acidification, land-use and land-cover change, ESMs of intermediate complexity, climate geoengineering, ocean CO2 uptake, and deposition of bioavailable iron in marine ecosystems. Since responding to global change is a pressing mission in Earth science, modeling will continue to contribute to the cooperative growth of diversifying disciplines and expanding ESS, because modeling connects traditional disciplines through explicit interaction between them.

Statistical downscaling of a climate simulation of the last glacial cycle: temperature and precipitation over Northern Europe

Abstract. Earth system models of intermediate complexity (EMICs) have proven to be able to simulate the large-scale features of glacial–interglacial climate evolution. For many climatic applications the spatial resolution of the EMICs' output is, however, too coarse, and downscaling methods are needed. In this study we introduce a way to use generalized additive models (GAMs) for downscaling the large-scale output of an EMIC in very different climatological conditions ranging from glacial periods to current relatively warm climates. GAMs are regression models in which a combination of explanatory variables is related to the response through a sum of spline functions. We calibrated the GAMs using observations of the recent past climate and the results of short time-slice simulations of glacial climate performed by the relatively high-resolution general circulation model CCSM (Community Climate System Model) and the regional climate model RCA3 (Rossby Centre regional Atmospheric climate model). As explanatory variables we used the output of a simulation by the CLIMBER-2 (CLIMate and BiosphERe model 2) EMIC of the last glacial cycle, coupled with the SICOPOLIS (SImulation COde for POLythermal Ice Sheets) ice sheet model, i.e. the large-scale temperature and precipitation data of CLIMBER-2, and the elevation, distance to ice sheet, slope direction and slope angle from SICOPOLIS. The fitted GAMs were able to explain more than 96% of the temperature response with a correlation of >0.98 and more than 59% of the precipitation response with a correlation of >0.72. The first comparison with two pollen-based reconstructions of temperature for Northern Europe showed that CLIMBER-2 data downscaled by GAMs corresponded better with the reconstructions than did the bilinearly interpolated CLIMBER-2 surface temperature.

A framework for modeling uncertainty in regional climate change

In this study, we present a new modeling framework and a large ensemble of climate projections to investigate the uncertainty in regional climate change over the United States (US) associated with four dimensions of uncertainty. The sources of uncertainty considered in this framework are the emissions projections, global climate system parameters, natural variability and model structural uncertainty. The modeling framework revolves around the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model with an Earth System Model of Intermediate Complexity (EMIC) (with a two-dimensional zonal-mean atmosphere). Regional climate change over the US is obtained through a two-pronged approach. First, we use the IGSM-CAM framework, which links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Second, we use a pattern-scaling method that extends the IGSM zonal mean based on climate change patterns from various climate models. Results show that the range of annual mean temperature changes are mainly driven by policy choices and the range of climate sensitivity considered. Meanwhile, the four sources of uncertainty contribute more equally to end-of-century precipitation changes, with natural variability dominating until 2050. For the set of scenarios used in this study, the choice of policy is the largest driver of uncertainty, defined as the range of warming and changes in precipitation, in future projections of climate change over the US.

Deep water formation in the North Pacific and deglacial CO2rise

Deep water formation in the North Atlantic and Southern Ocean is widely thought to influence deglacial CO_2 rise and climate change; here we suggest that deep water formation in the North Pacific may also play an important role. We present paired radiocarbon and boron isotope data from foraminifera from sediment core MD02-2489 at 3640 m in the North East Pacific. These show a pronounced excursion during Heinrich Stadial 1, with benthic-planktic radiocarbon offsets dropping to ~350 years, accompanied by a decrease in benthic δ^(11)B. We suggest that this is driven by the onset of deep convection in the North Pacific, which mixes young shallow waters to depth, old deep waters to the surface, and low-pH water from intermediate depths into the deep ocean. This deep water formation event was likely driven by an increase in surface salinity, due to subdued atmospheric/monsoonal freshwater flux during Heinrich Stadial 1. The ability of North Pacific Deep Water (NPDW) formation to explain the excursions seen in our data is demonstrated in a series of experiments with an intermediate complexity Earth system model. These experiments also show that breakdown of stratification in the North Pacific leads to a rapid ~30 ppm increase in atmospheric CO_2, along with decreases in atmospheric δ^(13)C and Δ^(14)C, consistent with observations of the early deglaciation. Our inference of deep water formation is based mainly on results from a single sediment core, and our boron isotope data are unavoidably sparse in the key HS1 interval, so this hypothesis merits further testing. However, we note that there is independent support for breakdown of stratification in shallower waters during this period, including a minimum in δ^(15)N, younging in intermediate water ^(14)C, and regional warming. We also re-evaluate deglacial changes in North Pacific productivity and carbonate preservation in light of our new data and suggest that the regional pulse of export production observed during the Bolling-Allerod is promoted by relatively stratified conditions, with increased light availability and a shallow, potent nutricline. Overall, our work highlights the potential of NPDW formation to play a significant and hitherto unrealized role in deglacial climate change and CO_2 rise.