CRESCENDO publications


Narrowing the range of future climate projections using historical observations of atmospheric CO2 

Ben B. B. Booth, Glen R. Harris, James M. Murphy, Jo I. House, Chris D. Jones, David Sexton and  Stephen Sitch. 2016 J. Climate, doi:10.1175/JCLI-D-16-0178.1, in press.

Abstract: Uncertainty in the behaviour of the carbon cycle is important in driving the range in future projected climate change. Previous comparisons of model responses with historical CO2 observations have suggested a strong constraint on simulated projections that could narrow the range considered plausible. Here we use a new 57 member perturbed parameter ensemble of variants of an Earth System model for 3 future scenarios, that (a) explores a wider range of potential climate responses than before, and (b) includes the impact of past uncertainty in carbon emissions on simulated trends. These two factors represent a more complete exploration of uncertainty, although they lead to a weaker constraint on the range of future CO2 concentrations as compared to earlier studies. Nevertheless, CO2 observations are shown to be effective at narrowing the distribution, excluding 30 of 57 simulations as inconsistent with historical CO2 changes. The perturbed model variants excluded are mainly at the high end of the future projected CO2 changes, with only 8 of the 26 variants projecting RCP8.5 2100 concentrations in excess of 1100 ppm retained. Interestingly, a minority of the high-end variants were able to capture historical CO2 trends, with the large magnitude response emerging later in the century (due to either high climate sensitivities, strong carbon feedbacks, or both). Comparison with observed CO2 is effective at narrowing both the range and distribution of projections out to mid 21st century for all scenarios, and to 2100 for a scenario with low emissions.

Poorest countries experience earlier anthropogenic emergence of daily temperature extremes

Luke J Harrington, David J Frame, Erich M Fischer, Ed Hawkins, Manoj Joshi and Chris D Jones. 2016 Environ. Res. Lett. 11 055007,  doi:10.1088/1748-9326/11/5/055007

Abstract: Understanding how the emergence of the anthropogenic warming signal from the noise of internal variability translates to changes in extreme event occurrence is of crucial societal importance. By utilising simulations of cumulative carbon dioxide (CO2) emissions and temperature changes from eleven earth system models, we demonstrate that the inherently lower internal variability found at tropical latitudes results in large increases in the frequency of extreme daily temperatures (exceedances of the 99.9th percentile derived from pre-industrial climate simulations) occurring much earlier than for mid-to-high latitude regions. Most of the world’s poorest people live at low latitudes, when considering 2010 GDP-PPP per capita; conversely the wealthiest population quintile disproportionately inhabit more variable mid-latitude climates. Consequently, the fraction of the global population in the lowest socio-economic quintile is exposed to substantially more frequent daily temperature extremes after much lower increases in both mean global warming and cumulative CO2 emissions. Video Abstract:

Global Carbon Budget 2016

Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, et al. Earth Syst. Sci. Data 2016, 8, 605-649, doi:10.5194/essd-8-605-2016

Short summary: The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.

Coastal-ocean uptake of anthropogenic carbon

Timothée Bourgeois, James C. Orr, Laure Resplandy, Jens Terhaar, Christian Ethé, Marion Gehlen, and Laurent Bopp. Biogeosciences 2016, 13, 4167–4185, doi:10.5194/bg-13-4167-2016

Short summary: The global coastal ocean took up 0.1 Pg C yr−1 of anthropogenic carbon during 1993–2012 based on new biogeochemical simulations with an eddying 3-D global model. That is about half of the most recent estimate, an extrapolation based on surface areas. It should not be confused with the continental shelf pump, perhaps 10 times larger, which includes natural as well as anthropogenic carbon. Coastal uptake of anthropogenic carbon is limited by its offshore transport.

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

Brian C. O’Neill, Claudia Tebaldi, Detlef P. van Vuuren, Veronika Eyring, Pierre Friedlingstein, George Hurtt, Reto Knutti, Elmar Kriegler, Jean-Francois Lamarque, Jason Lowe, Gerald A. Meehl, Richard Moss, Keywan Riahi, and Benjamin M. Sanderson. Geosci. Model Dev. 2016, 9, 3461-3482, doi:10.5194/gmd-9-3461-2016

Short summary: The Scenario Model Intercomparison Project (ScenarioMIP) will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. The design consists of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions. Climate model projections will facilitate integrated studies of climate change as well as address targeted scientific questions.

Towards improved and more routine Earth system model evaluation in CMIP

Veronika Eyring, Peter J. Gleckler, Christoph Heinze, Ronald J. Stouffer, Karl E. Taylor, V. Balaji, Eric Guilyardi, Sylvie Joussaume, Stephan Kindermann, Bryan N. Lawrence, Gerald A. Meehl, Mattia Righi, and Dean N. Williams. Earth Syst. Dynam. 2016, 7, 813-830, doi:10.5194/esd-7-813-2016

Short summary: We argue that the CMIP community has reached a critical juncture at which many baseline aspects of model evaluation need to be performed much more efficiently to enable a systematic and rapid performance assessment of the large number of models participating in CMIP, and we announce our intention to implement such a system for CMIP6. At the same time, continuous scientific research is required to develop innovative metrics and diagnostics that help narrowing the spread in climate projections.

Research priorities for negative emissions

S Fuss, C D Jones, F Kraxner, G P Peters, P Smith, M Tavoni, D P van Vuuren, J G Canadell, R B Jackson, J Milne, J R Moreira, N Nakicenovic, A Sharifi and Y Yamagata. 2016 Environ. Res. Lett. 11 115007 doi:10.1088/1748-9326/11/11/115007

Abstract: Carbon dioxide removal from the atmosphere (CDR)—also known as ‘negative emissions’—features prominently in most 2 °C scenarios and has been under increased scrutiny by scientists, citizens, and policymakers. Critics argue that ‘negative emission technologies’ (NETs) are insufficiently mature to rely on them for climate stabilization. Some even argue that 2 °C is no longer feasible or might have unacceptable social and environmental costs. Nonetheless, the Paris Agreement endorsed an aspirational goal of limiting global warming to even lower levels, arguing that climate impacts—especially for vulnerable nations such as small island states—will be unacceptably severe in a 2 °C world. While there are few pathways to 2 °C that do not rely on negative emissions, 1.5 °C scenarios are barely conceivable without them. Building on previous assessments of NETs, we identify some urgent research needs to provide a more complete picture for reaching ambitious climate targets, and the role that NETs can play in reaching them.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

Andrea Alessandri, Franco Catalano, Matteo De Felice, Bart Van Den Hurk, Francisco Doblas Reyes, Souhail Boussetta, Gianpaolo Balsamo, Paul A. Miller. 2016 Clim. Dyn. doi:10.1007/s00382-016-3372-4

Abstract: The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Human-induced greening of the northern extratropical land surface

Jiafu Mao, Aurélien Ribes, Binyan Yan, Xiaoying Shi1 Peter E. Thornton, Roland Séférian, Philippe Ciais et al. Nature Climate Change Volume:6, Pages:959–963 Year published:(2016) DOI:doi:10.1038/nclimate3056

At a glance: Significant land greening in the northern extratropical latitudes (NEL) has been documented through satellite observations during the past three decades. This enhanced vegetation growth has broad implications for surface energy, water and carbon budgets, and ecosystem services across multiple scales. Discernible human impacts on the Earth’s climate system have been revealed by using statistical frameworks of detection–attribution. These impacts, however, were not previously identified on the NEL greening signal, owing to the lack of long-term observational records, possible bias of satellite data, different algorithms used to calculate vegetation greenness, and the lack of suitable simulations from coupled Earth system models (ESMs). Here we have overcome these challenges to attribute recent changes in NEL vegetation activity. We used two 30-year-long remote-sensing-based leaf area index (LAI) data sets, simulations from 19 coupled ESMs with interactive vegetation, and a formal detection and attribution algorithm. Our findings reveal that the observed greening record is consistent with an assumption of anthropogenic forcings, where greenhouse gases play a dominant role, but is not consistent with simulations that include only natural forcings and internal climate variability. These results provide the first clear evidence of a discernible human fingerprint on physiological vegetation changes other than phenology and range shifts.

Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2

Sabrina Wenzel, Peter M. Cox, Veronika Eyring & Pierre Friedlingstein. Nature (2016) doi:10.1038/nature19772. Published online 28 September 2016

At a glance: Uncertainties in the response of vegetation to rising atmospheric CO2 concentrations contribute to the large spread in projections of future climate change. Climate–carbon cycle models generally agree that elevated atmospheric CO2 concentrations will enhance terrestrial gross primary productivity (GPP). However, the magnitude of this CO2 fertilization effect varies from a 20 per cent to a 60 per cent increase in GPP for a doubling of atmospheric CO2 concentrations in model studies. Here we demonstrate emergent constraints on large-scale CO2 fertilization using observed changes in the amplitude of the atmospheric CO2 seasonal cycle that are thought to be the result of increasing terrestrial GPP. Our comparison of atmospheric CO2 measurements from Point Barrow in Alaska and Cape Kumukahi in Hawaii with historical simulations of the latest climate–carbon cycle models demonstrates that the increase in the amplitude of the CO2 seasonal cycle at both measurement sites is consistent with increasing annual mean GPP, driven in part by climate warming, but with differences in CO2 fertilization controlling the spread among the model trends. As a result, the relationship between the amplitude of the CO2 seasonal cycle and the magnitude of CO2 fertilization of GPP is almost linear across the entire ensemble of models. When combined with the observed trends in the seasonal CO2 amplitude, these relationships lead to consistent emergent constraints on the CO2 fertilization of GPP. Overall, we estimate a GPP increase of 37 ± 9 per cent for high-latitude ecosystems and 32 ± 9 per cent for extratropical ecosystems under a doubling of atmospheric CO2 concentrations on the basis of the Point Barrow and Cape Kumukahi records, respectively.

C4MIP – The Coupled Climate-Carbon Cycle Model Intercomparicon project: experimental protocol for CMIP6

CD. Jones, V Arora, P Friedlingstein, L Bopp, V Brovkin et al. Geosci. Model Dev. 9, 2853-2880. Published: 16 Mar 2016, doi:10.5194/gmd-2016-36

Short summary: How the carbon cycle interacts with climate will affect future climate change and how society plans emissions reductions to achieve climate targets. The Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) is an endorsed activity of CMIP6 and aims to quantify these interactions and feedbacks in state-of-the-art climate models. This paper lays out the experimental protocol for modelling groups to follow to contribute to C4MIP. It is a contribution to the CMIP6 GMD special issue.

Simulating the Earth system response to negative emissions

C D Jones, P Ciais, S J Davis, P Friedlingstein, T Gasser, G P Peters, J Rogelj, D P van Vuuren, J G Canadell, A Cowie, R B Jackson, M Jonas, E Kriegler, E Littleton, J A Lowe, J Milne, G Shrestha, P Smith, A Torvanger and A Wiltshire (2016). Environmental Research Letters, 11: 095012

Abstract: Natural carbon sinks currently absorb approximately half of the anthropogenic CO2 emitted by fossil fuel burning, cement production and land-use change. However, this airborne fraction may change in the future depending on the emissions scenario. An important issue in developing carbon budgets to achieve climate stabilisation targets is the behaviour of natural carbon sinks, particularly under low emissions mitigation scenarios as required to meet the goals of the Paris Agreement. A key requirement for low carbon pathways is to quantify the effectiveness of negative emissions technologies which will be strongly affected by carbon cycle feedbacks. Here we find that Earth system models suggest significant weakening, even potential reversal, of the ocean and land sinks under future low emission scenarios. For the RCP2.6 concentration pathway, models project land and ocean sinks to weaken to 0.8 ± 0.9 and 1.1 ± 0.3 GtC yr−1 respectively for the second half of the 21st century and to −0.4 ± 0.4 and 0.1 ± 0.2 GtC yr−1 respectively for the second half of the 23rd century. Weakening of natural carbon sinks will hinder the effectiveness of negative emissions technologies and therefore increase their required deployment to achieve a given climate stabilisation target. We introduce a new metric, the perturbation airborne fraction, to measure and assess the effectiveness of negative emissions.

Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

R Séférian, M Gehlen, L Bopp, L Resplandy, JC Orr, et al. – Geosci. Model Dev., 9, 1827-1851, 2016

Short summary: This paper explores how the large diversity in spin-up protocols used for ocean biogeochemistry in CMIP5 models contributed to inter-model differences in modeled fields. We show that a link between spin-up duration and skill-score metrics emerges from both individual IPSL-CM5A-LR’s results and an ensemble of CMIP5 models. Our study suggests that differences in spin-up protocols constitute a source of inter-model uncertainty which would require more attention in future intercomparison exercises.

Decadal predictions of the North Atlantic CO2 uptake

Hongmei Li, Tatiana Ilyina, Wolfgang A. Müller & Frank Sienz – Nature Communications 7, Article number:11076 doi:10.1038/ncomms11076

Abstract: As a major CO2 sink, the North Atlantic, especially its subpolar gyre region, is essential for the global carbon cycle. Decadal fluctuations of CO2 uptake in the North Atlantic subpolar gyre region are associated with the evolution of the North Atlantic Oscillation, the Atlantic meridional overturning circulation, ocean mixing and sea surface temperature anomalies. While variations in the physical state of the ocean can be predicted several years in advance by initialization of Earth system models, predictability of CO2 uptake has remained unexplored. Here we investigate the predictability of CO2 uptake variations by initialization of the MPI-ESM decadal prediction system. We find large multi-year variability in oceanic CO2 uptake and demonstrate that its potential predictive skill in the western subpolar gyre region is up to 4–7 years. The predictive skill is mainly maintained in winter and is attributed to the improved physical state of the ocean.

Evaluating CMIP5 ocean biogeochemistry and Southern Ocean carbon uptake using atmospheric potential oxygen: Present‐day performance and future projection

CD Nevison, M Manizza, RF Keeling et al. – Geophysical Research Letters, 2016 – Volume 43, Issue 5, 16 March 2016 Pages 2077–2085 DOI: 10.1002/2015GL067584

Abstract: Observed seasonal cycles in atmospheric potential oxygen (APO ~ O2 + 1.1 CO2) were used to evaluate eight ocean biogeochemistry models from the Coupled Model Intercomparison Project (CMIP5). Model APO seasonal cycles were computed from the CMIP5 air-sea O2 and CO2 fluxes and compared to observations at three Southern Hemisphere monitoring sites. Four of the models captured either the observed APO seasonal amplitude or phasing relatively well, while the other four did not. Many models had an unrealistic seasonal phasing or amplitude of the CO2 flux, which in turn influenced APO. By 2100 under RCP8.5, the models projected little change in the O2 component of APO but large changes in the seasonality of the CO2 component associated with ocean acidification. The models with poorer performance on present-day APO tended to project larger net carbon uptake in the Southern Ocean, both today and in 2100.

Soil frost-induced soil moisture precipitation feedback over high northern latitudes

Stefan Hagemann, Tanja Blome, Altug Ekici, and Christian Beer – Earth Syst. Dynam., 7, 611-625, 2016

Short summary: The present study analyzes how cold region physical soil processes, especially freezing of soil water, impact large-scale hydrology and climate over northern hemisphere high latitude land areas. For this analysis, an atmosphere/land global climate model was used. It is shown that including these processes in the model leads to improved discharge in spring and a positive land atmosphere feedback to precipitation over the high latitudes that has previously not been noted for the high latitudes.


Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

Paolo Davini, Jost von Hardenberg, Susanna Corti, Hannah M. Christensen, Stephan Juricke, Aneesh Subramanian, Peter A. G. Watson, Antje Weisheimer, and Tim N. Palmer. Geosci. Model Dev., 10, 1383-1402, 2017.

Short summary: The Climate SPHINX project is a large set of more than 120 climate simulations run with the EC-Earth global climate. It explores the sensitivity of present-day and future climate to the model horizontal resolution (from 150 km up to 16 km) and to the introduction of two stochastic physics parameterisations. Results shows that the the stochastic schemes can represent a cheaper alternative to a resolution increase, especially for the representation of the tropical climate variability.

Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

Silvia Terzago, Jost von Hardenberg, Elisa Palazzi, and Antonello Provenzale. The Cryosphere, 11, 1625-1645, 2017.

Short summary: The estimate of the current and future conditions of snow resources in mountain areas depends on the availability of reliable fine-resolution data sets and of climate models capable of properly representing snow processes and snow–climate interactions. This work considers the snow water equivalent data sets from remote sensing, reanalyses, regional and global climate models available for the Alps and explores their ability to provide a coherent view of the snowpack features and its changes.

Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10)

Daniel S. Goll, Alexander J. Winkler, Thomas Raddatz, Ning Dong, Ian Colin Prentice, Philippe Ciais, and Victor Brovkin. Geosci. Model Dev., 10, 2009-2030, 2017.

Short summary: The response of soil organic carbon decomposition to warming and the interactions between nitrogen and carbon cycling affect the feedbacks between the land carbon cycle and the climate. In the model JSBACH carbon–nitrogen interactions have only a small effect on the feedbacks, whereas modifications of soil organic carbon decomposition have a large effect. The carbon cycle in the improved model is more resilient to climatic changes than in previous version of the model.

Quantifying uncertainties of permafrost carbon-climate feedbacks

Burke, E. J., Ekici, A., Huang, Y., Chadburn, S. E., Huntingford, C., Ciais, P., Friedlingstein, P., Peng, S., and Krinner, G. Biogeosciences, 14, 3051-3066, 2017.

Short summary: There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.

Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users

Andrea Alessandri, Matteo De FeliceFranco CatalanoJune-Yi LeeBin WangDoo Young LeeJin-Ho YooAntije Weisheimer. Clim Dyn (2017).

Abstract: Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles. Previous works suggested that the potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. In this work we combine the two MME Seasonal Prediction Systems (SPSs) independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities. To this aim, all the possible multi-model combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation compared to previous estimates from the contributing MMEs. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The number and selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models. To verify the above results for a real world application, the Grand ENSEMBLES-APCC/CliPAS MME is used to predict retrospective energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990–2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. The above results demonstrate for the first time the potential of the Grand MME to significantly contribute in obtaining useful predictions at the seasonal time-scale.

CO2 loss by permafrost thawing implies additional emissions reductions to limit warming to 1.5 or 2 °C

Eleanor J. Burke, Sarah E. Chadburn, Chris Huntingford and Chris D. Jones. Environmental Research Letters, in press.

Abstract: Large amounts of carbon are stored in the permafrost of the northern high latitude land. As permafrost degrades under a warming climate, some of this carbon will decompose and be released to the atmosphere. This positive climate-carbon feedback will reduce the natural carbon sinks and thus lower anthropogenic CO2 emissions compatible with the goals of the Paris Agreement. Simulations using an ensemble of the JULES-IMOGEN intermediate complexity climate model (including climate response and process uncertainty) and a stabilization target of 2 °C, show that including the permafrost carbon pool in the model increases the land carbon emissions at stabilization by between 0.09 and 0.19 Gt C year-1 (10th to 90th percentile). These emissions are only slightly reduced to between 0.08 and 0.16 Gt C year-1 (10th to 90th percentile) when considering 1.5 C stabilization targets. This suggests that uncertainties caused by the differences in stabilization target are small compared with those associated with model parameterisation uncertainty. Inertia means that permafrost carbon loss may continue for many years after anthropogenic emissions have stabilized. Simulations suggest that between 225 and 345 Gt C (10th to 90th percentile) are in thawed permafrost and may eventually be released to the atmosphere for stabilization target of 2 °C. This value is 60 to 100 Gt C less for a 1.5 °C target. The inclusion of permafrost carbon will add to the demands on negative emission technologies which are already present in most low emissions scenarios.

Ocean (de)oxygenation from the Last Glacial Maximum to the twenty-first century: insights from Earth System models

L. Bopp, L. Resplandy, A. Untersee, P. Le Mezo, M. Kageyama. Philos Trans A Math Phys Eng Sci. 2017 Sep 13;375(2102). doi: 10.1098/rsta.2016.0323.

Abstract: All Earth System models project a consistent decrease in the oxygen content of oceans for the coming decades because of ocean warming, reduced ventilation and increased stratification. But large uncertainties for these future projections of ocean deoxygenation remain for the subsurface tropical oceans where the major oxygen minimum zones are located. Here, we combine global warming projections, model-based estimates of natural short-term variability, as well as data and model estimates of the Last Glacial Maximum (LGM) ocean oxygenation to gain some insights into the major mechanisms of oxygenation changes across these different time scales. We show that the primary uncertainty on future ocean deoxygenation in the subsurface tropical oceans is in fact controlled by a robust compensation between decreasing oxygen saturation (O2sat) due to warming and decreasing apparent oxygen utilization (AOU) due to increased ventilation of the corresponding water masses. Modelled short-term natural variability in subsurface oxygen levels also reveals a compensation between O2sat and AOU, controlled by the latter. Finally, using a model simulation of the LGM, reproducing data-based reconstructions of past ocean (de)oxygenation, we show that the deoxygenation trend of the subsurface ocean during deglaciation was controlled by a combination of warming-induced decreasing O2sat and increasing AOU driven by a reduced ventilation of tropical subsurface waters.This article is part of the themed issue ‘Ocean ventilation and deoxygenation in a warming world’.

Biogeochemical modelling of dissolved oxygen in a changing ocean

Oliver Andrews, Erik Buitenhuis, Corinne Le Quéré, Parvadha Suntharalingam. Philos Trans A Math Phys Eng Sci. 2017 Sep 13;375(2102). doi: 10.1098/rsta.2016.0328.

Abstract: Secular decreases in dissolved oxygen concentration have been observed within the tropical oxygen minimum zones (OMZs) and at mid- to high latitudes over the last approximately 50 years. Earth system model projections indicate that a reduction in the oxygen inventory of the global ocean, termed ocean deoxygenation, is a likely consequence of on-going anthropogenic warming. Current models are, however, unable to consistently reproduce the observed trends and variability of recent decades, particularly within the established tropical OMZs. Here, we conduct a series of targeted hindcast model simulations using a state-of-the-art global ocean biogeochemistry model in order to explore and review biases in model distributions of oceanic oxygen. We show that the largest magnitude of uncertainty is entrained into ocean oxygen response patterns due to model parametrization of pCO2-sensitive C : N ratios in carbon fixation and imposed atmospheric forcing data. Inclusion of a pCO2-sensitive C : N ratio drives historical oxygen depletion within the ocean interior due to increased organic carbon export and subsequent remineralization. Atmospheric forcing is shown to influence simulated interannual variability in ocean oxygen, particularly due to differences in imposed variability of wind stress and heat fluxes.This article is part of the themed issue ‘Ocean ventilation and deoxygenation in a warming world’.

Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

James C. Orr, Raymond G. Najjar, Olivier Aumont, Laurent Bopp, John L. Bullister, Gokhan Danabasoglu, Scott C. Doney, John P. Dunne, Jean-Claude Dutay, Heather Graven, Stephen M. Griffies, Jasmin G. John, Fortunat Joos, Ingeborg Levin et al. Geosci. Model Dev., 10, 2169-2199, 2017.

Short summary: The Ocean Model Intercomparison Project (OMIP) is a model comparison effort under Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Its physical component is described elsewhere in this special issue. Here we describe its ocean biogeochemical component (OMIP-BGC), detailing simulation protocols and analysis diagnostics. Simulations focus on ocean carbon, other biogeochemical tracers, air-sea exchange of CO2 and related gases, and chemical tracers used to evaluate modeled circulation.

Large historical growth in global terrestrial gross primary production

Campbell, J.E., Berry, J.A., Seibt, U., Smith, S.J., Montzka, S.A., Launois, T., Belviso, S., Bopp, L., and Laine, M. Nature 544, 84–87 (06 April 2017). doi:10.1038/nature22030

Abstract: Growth in terrestrial gross primary production (GPP)—the amount of carbon dioxide that is ‘fixed’ into organic material through the photosynthesis of land plants—may provide a negative feedback for climate change1,2. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth3. As a consequence, modelling estimates of terrestrial carbon storage, and of feedbacks between the carbon cycle and climate, remain poorly constrained4. Here we present a global, measurement-based estimate of GPP growth during the twentieth century that is based on long-term atmospheric carbonyl sulfide (COS) records, derived from ice-core, firn and ambient air samples5. We interpret these records using a model that simulates changes in COS concentration according to changes in its sources and sinks—including a large sink that is related to GPP. We find that the observation-based COS record is most consistent with simulations of climate and the carbon cycle that assume large GPP growth during the twentieth century (31% ± 5% growth; mean ± 95% confidence interval). Although this COS analysis does not directly constrain models of future GPP growth, it does provide a global-scale benchmark for historical carbon-cycle simulations.

Big in the benthos: Future change of seafloor community biomass in a global, body size-resolved model

Andrew Yool, Adrian P. Martin, Thomas R. Anderson, Brian J. Bett, Daniel O. B. Jones, Henry A. Ruhl. Global Change Biol. Volume 23, Issue 9, September 2017 Pages 3554–3566

Abstract: Deep-water benthic communities in the ocean are almost wholly dependent on near-surface pelagic ecosystems for their supply of energy and material resources. Primary production in sunlit surface waters is channelled through complex food webs that extensively recycle organic material, but lose a fraction as particulate organic carbon (POC) that sinks into the ocean interior. This exported production is further rarefied by microbial breakdown in the abyssal ocean, but a residual ultimately drives diverse assemblages of seafloor heterotrophs. Advances have led to an understanding of the importance of size (body mass) in structuring these communities. Here we force a size-resolved benthic biomass model, BORIS, using seafloor POC flux from a coupled ocean-biogeochemistry model, NEMO-MEDUSA, to investigate global patterns in benthic biomass. BORIS resolves 16 size classes of metazoans, successively doubling in mass from approximately 1 μg to 28 mg. Simulations find a wide range of seasonal responses to differing patterns of POC forcing, with both a decline in seasonal variability, and an increase in peak lag times with increasing body size. However, the dominant factor for modelled benthic communities is the integrated magnitude of POC reaching the seafloor rather than its seasonal pattern. Scenarios of POC forcing under climate change and ocean acidification are then applied to investigate how benthic communities may change under different future conditions. Against a backdrop of falling surface primary production (−6.1%), and driven by changes in pelagic remineralization with depth, results show that while benthic communities in shallow seas generally show higher biomass in a warmed world (+3.2%), deep-sea communities experience a substantial decline (−32%) under a high greenhouse gas emissions scenario. Our results underscore the importance for benthic ecology of reducing uncertainty in the magnitude and seasonality of seafloor POC fluxes, as well as the importance of studying a broader range of seafloor environments for future model development.

Beyond equilibrium climate sensitivity

Reto Knutti, Maria A. A. Rugenstein and Gabriele C. Hegerl. Nature Geoscience 10, 727–736 (2017). doi:10.1038/ngeo3017.

Abstract: Equilibrium climate sensitivity characterizes the Earth’s long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the ‘likely’ range for climate sensitivity of 1.5 °C to 4.5 °C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 °C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.

Aerosols in the Pre-industrial Atmosphere

Kenneth S. Carslaw, Hamish Gordon, Douglas S. Hamilton, Jill S. Johnson, Leighton A. Regayre, M. Yoshioka, Kirsty J. Pringle. 2017 Curr Clim Change Rep (2017) 3:1–15.

Abstract: We review what is known about the microphysical, chemical, and radiative properties of aerosols in the pre-industrial atmosphere and the processes that control them. Aerosol properties were controlled by a combination of natural emissions, modification of the natural emissions by human activities such as land-use change, and anthropogenic emissions from biofuel combustion and early industrial processes. Although aerosol concentrations were lower in the pre-industrial atmosphere than today, model simulations show that relatively high aerosol concentrations could have been maintained over continental regions due to biogenically controlled new particle formation and wildfires. Despite the importance of pre-industrial aerosols for historical climate change, the relevant processes and emissions are given relatively little consideration in climate models, and there have been very few attempts to evaluate them. Consequently, we have very low confidence in the ability of models to simulate the aerosol conditions that form the baseline for historical climate simulations. Nevertheless, it is clear that the 1850s should be regarded as an early industrial reference period, and the aerosol forcing calculated from this period is smaller than the forcing since 1750. Improvements in historical reconstructions of natural and early anthropogenic emissions, exploitation of new Earth system models, and a deeper understanding and evaluation of the controlling processes are key aspects to reducing uncertainties in future.

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

Raivonen, M., Smolander, S., Backman, L., Susiluoto, J., Aalto, T., Markkanen, T., Mäkelä, J., Rinne, J., Peltola, O., Aurela, M., Tomasic, M., Li, X., Larmola, T., Juutinen, S., Tuittila, E.-S., Heimann, M., Sevanto, S., Kleinen, T., Brovkin, V. 2017 Geosci. Model Dev., 10, 4665–4691.

Short summary: Wetlands are one of the most significant natural sources of the strong greenhouse gas methane. We developed a model that can be used within a larger wetland carbon model to simulate the methane emissions. In this study, we present the model and results of its testing. We found that the model works well with different settings and that the results depend primarily on the rate of input anoxic soil respiration and also on factors that affect the simulated oxygen concentrations in the wetland soil.

Impact of the 2 °C target on global woody biomass use

Pekka Lauri, Nicklas Forsell, Anu Korosuo, Petr Havlík, Michael Obersteiner, Annika Nordin. 2017 Forest Policy and Economics Volume 83, October 2017, Pages 121-130.

Abstract: In this study we investigate the implications of reaching the 2 °C climate target for global woody biomass use by applying the Global Biosphere Management Model (GLOBIOM) and the recently published SSP-RCP scenario calculations. We show that the higher biomass demand for energy needed to reach the 2 °C target can be achieved without significant distortions to woody biomass material use and that it can even benefit certain forest industries and regions. This is because the higher woody biomass use for energy increases the demand for forest industry by-products, which makes forest industry final products production more profitable and compensates for the cost effect of increased competition over raw materials. The higher woody biomass use for energy is found to benefit sawnwood, plywood and chemical pulp production, which provide large amounts of by-products, and to inhibit fiberboard and mechanical pulp production, which provide small amounts of by-products. At the regional level, the higher woody biomass use for energy is found to benefit material production in regions, which use little roundwood for energy (Russia, North-America and EU28), and to inhibit material production in regions, which use large amounts of roundwood for energy (Asia, Africa and South-America). Even if the 2 °C target increases harvest volumes in the tropical regions significantly compared to the non-mitigation scenario, harvest volumes remain in these regions at a relatively low level compared to the harvest potential.

Historical greenhouse gas concentrations for climate modelling (CMIP6)

Malte Meinshausen, Elisabeth Vogel, Alexander Nauels, Katja Lorbacher, Nicolai Meinshausen, David M. Etheridge, Paul J. Fraser, Stephen A. Montzka, Peter J. Rayner, Cathy M. Trudinger, et al. 2017 Geosci. Model Dev., 10, 2057-2116,

Short summary: Climate change is primarily driven by human-induced increases of greenhouse gas (GHG) concentrations. Based on ongoing community efforts (e.g. AGAGE and NOAA networks, ice cores), this study presents historical concentrations of CO2, CH4, N2O and 40 other GHGs from year 0 to year 2014. The data is recommended as input for climate models for pre-industrial, historical runs under CMIP6. Global means, but also latitudinal by monthly surface concentration fields are provided.

Future global mortality from changes in air pollution attributable to climate change

Raquel A. Silva, J. Jason West, Jean-François Lamarque, Drew T. Shindell, William J. Collins, Greg Faluvegi, Gerd A. Folberth, Larry W. Horowitz, Tatsuya Nagashima, et al. 2017 Nature Climate Change, Published online: 31 JULY 2017, doi:10.1038/nclimate3354

Abstract: Ground-level ozone and fine particulate matter (PM 2.5) are associated with premature human mortality1, 2, 3, 4; their future concentrations depend on changes in emissions, which dominate the near-term5, and on climate change6, 7. Previous global studies of the air-quality-related health effects of future climate change8, 9 used single atmospheric models. However, in related studies, mortality results differ among models10, 11, 12. Here we use an ensemble of global chemistry–climate models13 to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.5 (ref. 14), is probably positive. We estimate 3,340 (−30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (−195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM 2.5, we estimate 55,600 (−34,300 to 164,000) deaths in 2030 and 215,000 (−76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM 2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.

Emergent constraints in climate projections: a case study of changes in high latitude temperature variability

Aleksandra Borodina, Erich M. Fischer, and Reto Knutti. 2017 Journal of Climate 30: 3655-3670,

Abstract: Climate projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensemble show a decrease in interannual surface temperature variability over high latitudes with a large intermodel spread, in particular over the areas of sea ice retreat. Here relationships are found between the models’ present-day performance in sea ice–related metrics and future changes in temperature variability. These relations, so-called emergent constraints, can produce ensembles of models calibrated with present-day observations with a narrower spread across their members than across the full ensemble. The underlying assumption is that models in better agreement with observations or reanalyses in a carefully selected metric probably have a more realistic representation of local processes, and therefore are more reliable for projections. Thus, the reliability of this method depends on the availability of high-quality observations or reanalyses. This work represents a step toward formalization of the emergent constraints framework, as so far there is no consensus on how the constraints should be best implemented. The authors quantify the reduction in spread from emerging constraints for various metrics and their combinations, different emission scenarios, and seasons. Some of the general features of emerging constraints are discussed, and how to effectively aggregate information across metrics and seasons to achieve the largest reduction in model spread. It is demonstrated, based on the case of temperature variability, that a robust constraint can be obtained by combining relevant metrics across all seasons. Such a constraint results in a strongly reduced spread across model projections, which is consistent with a process understanding of variability changes due to sea ice retreat.

A climate model projection weighting scheme accounting for performance and interdependence

Knutti, R., J. Sedláček, B. M. Sanderson, R. Lorenz, E. M. Fischer, and V. Eyring. 2017 Geophys. Res. Lett., 44, 1909–1918, doi:10.1002/2016GL072012.

Abstract: Uncertainties of climate projections are routinely assessed by considering simulations from different models. Observations are used to evaluate models, yet there is a debate about whether and how to explicitly weight model projections by agreement with observations. Here we present a straightforward weighting scheme that accounts both for the large differences in model performance and for model interdependencies, and we test reliability in a perfect model setup. We provide weighted multimodel projections of Arctic sea ice and temperature as a case study to demonstrate that, for some questions at least, it is meaningless to treat all models equally. The constrained ensemble shows reduced spread and a more rapid sea ice decline than the unweighted ensemble. We argue that the growing number of models with different characteristics and considerable interdependence finally justifies abandoning strict model democracy, and we provide guidance on when and how this can be achieved robustly.

Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

Paolo Davini, Jost von Hardenberg, Susanna Corti, Hannah M. Christensen, Stephan Juricke, Aneesh Subramanian, Peter A. G. Watson, Antje Weisheimer, and Tim N. Palmer. 2017 Geosci. Model Dev., 10, 1383-1402, doi:10.5194/gmd-10-1383-2017.

Short summary: The Climate SPHINX project is a large set of more than 120 climate simulations run with the EC-Earth global climate. It explores the sensitivity of present-day and future climate to the model horizontal resolution (from 150 km up to 16 km) and to the introduction of two stochastic physics parameterisations. Results shows that the the stochastic schemes can represent a cheaper alternative to a resolution increase, especially for the representation of the tropical climate variability.

A vertical representation of soil carbon in the JULES land surface scheme (vn4.3_permafrost) with a focus on permafrost regions

Eleanor J. Burke, Sarah E. Chadburn, and Altug Ekici. 2017 Geosci. Model Dev., 10, 959-975, doi:10.5194/gmd-10-959-2017.

Short summary: There is a large amount of relatively inert organic carbon locked into permafrost soils. In a warming climate the permafrost will thaw and this organic carbon will become vulnerable to decomposition. This process is not typically included within Earth system models (ESMs). This paper describes the development of a vertically resolved soil organic carbon decomposition model which, in the future, can be included within the UKESM to quantify the response of the climate to permafrost carbon loss.

Emergent constraints on projections of declining primary production in the tropical oceans

Lester Kwiatkowski, Laurent Bopp, Olivier Aumont, Philippe Ciais, Peter M. Cox, Charlotte Laufkötter, Yue Li & Roland Séférian. 2017 Nature Climate Change 7, 355–358 (2017), doi:10.1038/nclimate3265.

Abstract: Marine primary production is a fundamental component of the Earth system, providing the main source of food and energy to the marine food web, and influencing the concentration of atmospheric CO 2 (refs 1,2). Earth system model (ESM) projections of global marine primary production are highly uncertain with models projecting both increases3, 4 and declines of up to 20% by 21005, 6. This uncertainty is predominantly driven by the sensitivity of tropical ocean primary production to climate change, with the latest ESMs suggesting twenty-first-century tropical declines of between 1 and 30% (refs 5,6). Here we identify an emergent relationship7, 8, 9, 10, 11 between the long-term sensitivity of tropical ocean primary production to rising equatorial zone sea surface temperature (SST) and the interannual sensitivity of primary production to El Niño/Southern Oscillation (ENSO)-driven SST anomalies. Satellite-based observations of the ENSO sensitivity of tropical primary production are then used to constrain projections of the long-term climate impact on primary production. We estimate that tropical primary production will decline by 3 ± 1% per kelvin increase in equatorial zone SST. Under a business-as-usual emissions scenario this results in an 11 ± 6% decline in tropical marine primary production and a 6 ± 3% decline in global marine primary production by 2100.

An observation-based constraint on permafrost loss as a function of global warming

S. E. Chadburn, E. J. Burke, P. M. Cox, P. Friedlingstein, G. Hugelius & S. Westermann. 2017 Nature Climate Change 7, 340–344 (2017), doi:10.1038/nclimate3262.

Abstract: Permafrost, which covers 15 million km2 of the land surface, is one of the components of the Earth system that is most sensitive to warming1, 2. Loss of permafrost would radically change high-latitude hydrology and biogeochemical cycling, and could therefore provide very significant feedbacks on climate change3, 4, 5, 6, 7, 8. The latest climate models all predict warming of high-latitude soils and thus thawing of permafrost under future climate change, but with widely varying magnitudes of permafrost thaw9, 10. Here we show that in each of the models, their present-day spatial distribution of permafrost and air temperature can be used to infer the sensitivity of permafrost to future global warming. Using the same approach for the observed permafrost distribution and air temperature, we estimate a sensitivity of permafrost area loss to global mean warming at stabilization of million km2 °C−1 (1σ confidence), which is around 20% higher than previous studies9. Our method facilitates an assessment for COP21 climate change targets11: if the climate is stabilized at 2 °C above pre-industrial levels, we estimate that the permafrost area would eventually be reduced by over 40%. Stabilizing at 1.5 °C rather than 2 °C would save approximately 2 million km2 of permafrost.

Variable reactivity of particulate organic matter in a global ocean biogeochemical model

Olivier Aumont, Marco van Hulten, Matthieu Roy-Barman, Jean-Claude Dutay, Christian Éthé, and Marion Gehlen. 2017 Biogeosciences, 14, 2321–2341, doi:10.5194/bg-14-2321-2017 .

Short summary: The marine biological carbon pump is dominated by the vertical transfer of particulate organic carbon (POC) from the surface ocean to its interior. In this study, we explore the impacts of a variable composition of this organic matter using a global ocean biogeochemical model. We show that accounting for a variable lability of POC increases POC concentrations by up to 2 orders of magnitude in the ocean’s interior. Furthermore, the amount of carbon that reaches the sediments is twice as large.

Rapid emergence of climate change in environmental drivers of marine ecosystems

Stephanie A. Henson, Claudie Beaulieu, Tatiana Ilyina, Jasmin G. John, Matthew Long, Roland Séférian, Jerry Tjiputra & Jorge L. Sarmiento. 2017 Nature Communications 8, Article number: 14682 (2017), doi:10.1038/ncomms14682.

Abstract: Climate change is expected to modify ecological responses in the ocean, with the potential for important effects on the ecosystem services provided to humankind. Here we address the question of how rapidly multiple drivers of marine ecosystem change develop in the future ocean. By analysing an ensemble of models we find that, within the next 15 years, the climate change-driven trends in multiple ecosystem drivers emerge from the background of natural variability in 55% of the ocean and propagate rapidly to encompass 86% of the ocean by 2050 under a ‘business-as-usual’ scenario. However, we also demonstrate that the exposure of marine ecosystems to climate change-induced stress can be drastically reduced via climate mitigation measures; with mitigation, the proportion of ocean susceptible to multiple drivers within the next 15 years is reduced to 34%. Mitigation slows the pace at which multiple drivers emerge, allowing an additional 20 years for adaptation in marine ecological and socio-economic systems alike.

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

William J. Collins, Jean-François Lamarque, Michael Schulz, Olivier Boucher, Veronika Eyring, Michaela I. Hegglin, Amanda Maycock, Gunnar Myhre, Michael Prather, Drew Shindell, and Steven J. Smith. 2017 Geosci. Model Dev., 10, 585-607, doi:10.5194/gmd-10-585-2017

Short summary: We have designed a set of climate model experiments called the Aerosol Chemistry Model Intercomparison Project (AerChemMIP). These are designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases in the climate models that are used to simulate past and future climate. We hope that many climate modelling centres will choose to run these experiments to help understand the contribution of aerosols and chemistry to climate change.

Review of the global models used phase 1 of the Chemistry-Climate Model Initiative (CCMI)

Olaf Morgenstern, Michaela I. Hegglin, Eugene Rozanov, Fiona M. O’Connor, N. Luke Abraham, Hideharu Akiyoshi, Alexander T. Archibald, Slimane Bekki, Neal Butchart, Martyn P. Chipperfield, et al. 2017 Geosci. Model Dev., 10, 639-671, doi:10.5194/gmd-10-639-2017

Short summary: We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.

The Met Office HadGEM3-ES chemistry–climate model: evaluation of stratospheric dynamics and its impact on ozone

Steven C. Hardiman, Neal Butchart, Fiona M. O’Connor, and Steven T. Rumbold. 2017 Geosci. Model Dev., 10, 1209-1232, doi:10.5194/gmd-10-1209-2017

Short summary: We present a review of the make-up of 20 models participating in the Chemistry–Climate Model Initiative (CCMI). In comparison to earlier such activities, most of these models comprise a whole-atmosphere chemistry, and several of them include an interactive ocean module. This makes them suitable for studying the interactions of tropospheric air quality, stratospheric ozone, and climate. The paper lays the foundation for other studies using the CCMI simulations for scientific analysis.


Diverging seasonal extremes for ocean acidification during the twenty-first century

Lester Kwiatkowski & James C. Orr. Nature Climate Change 8, 141–145 (2018).  doi:10.1038/s41558-017-0054-0

Abstract: How ocean acidification will affect marine organisms depends on changes in both the long-term mean and the short-term temporal variability of carbonate chemistry. Although the decadal-to-centennial response to atmospheric CO2 and climate change is constrained by observations and models, little is known about corresponding changes in seasonality, particularly for pH. Here we assess the latter by analysing nine earth system models (ESMs) forced with a business-as-usual emissions scenario. During the twenty-first century, the seasonal cycle of surface-ocean pH was attenuated by 16 ± 7%, on average, whereas that for hydrogen ion concentration [H+] was amplified by 81 ± 16%. Simultaneously, the seasonal amplitude of the aragonite saturation state (Ωarag) was attenuated except in the subtropics, where it was amplified. These contrasting changes derive from regionally varying sensitivities of these variables to atmospheric CO2 and climate change and to diverging trends in seasonal extremes in the primary controlling variables (temperature, dissolved inorganic carbon and alkalinity). Projected seasonality changes will tend to exacerbate the impacts of increasing [H+] on marine organisms during the summer and ameliorate the impacts during the winter, although the opposite holds in the high latitudes. Similarly, over most of the ocean, impacts from declining Ωarag are likely to be intensified during the summer and dampened during the winter.

Impact on short-lived climate forcers increases projected warming due to deforestation

C. E. Scott, S. A. Monks, D. V. Spracklen, S. R. Arnold, P. M. Forster, A. Rap, M. Äijälä, P. Artaxo, K. S. Carslaw, M. P. Chipperfield, M. Ehn, S. Gilardoni, L. Heikkinen, M. Kulmala, T. Petäjä, C. L. S. Reddington, L. V. Rizzo, E. Swietlicki, E. Vignati & C. Wilson. Nature Communications 9, Article number: 157 (2018). doi:10.1038/s41467-017-02412-4.

Abstract: The climate impact of deforestation depends on the relative strength of several biogeochemical and biogeophysical effects. In addition to affecting the exchange of carbon dioxide (CO2) and moisture with the atmosphere and surface albedo, vegetation emits biogenic volatile organic compounds (BVOCs) that alter the formation of short-lived climate forcers (SLCFs), which include aerosol, ozone and methane. Here we show that a scenario of complete global deforestation results in a net positive radiative forcing (RF; 0.12 W m−2) from SLCFs, with the negative RF from decreases in ozone and methane concentrations partially offsetting the positive aerosol RF. Combining RFs due to CO2, surface albedo and SLCFs suggests that global deforestation could cause 0.8 K warming after 100 years, with SLCFs contributing 8% of the effect. However, deforestation as projected by the RCP8.5 scenario leads to zero net RF from SLCF, primarily due to nonlinearities in the aerosol indirect effect.

Substantial large-scale feedbacks between natural aerosols and climate

C. E. Scott, S. R. Arnold, S. A. Monks, A. Asmi, P. Paasonen & D. V. Spracklen. Nature Geoscience 11, 44–48 (2018) doi:10.1038/s41561-017-0020-5

Abstract: The terrestrial biosphere is an important source of natural aerosol. Natural aerosol sources alter climate, but are also strongly controlled by climate, leading to the potential for natural aerosol–climate feedbacks. Here we use a global aerosol model to make an assessment of terrestrial natural aerosol–climate feedbacks, constrained by observations of aerosol number. We find that warmer-than-average temperatures are associated with higher-than-average number concentrations of large (>100 nm diameter) particles, particularly during the summer. This relationship is well reproduced by the model and is driven by both meteorological variability and variability in natural aerosol from biogenic and landscape fire sources. We find that the calculated extratropical annual mean aerosol radiative effect (both direct and indirect) is negatively related to the observed global temperature anomaly, and is driven by a positive relationship between temperature and the emission of natural aerosol. The extratropical aerosol–climate feedback is estimated to be −0.14 W m−2 K−1 for landscape fire aerosol, greater than the −0.03 W m−2 K−1 estimated for biogenic secondary organic aerosol. These feedbacks are comparable in magnitude to other biogeochemical feedbacks, highlighting the need for natural aerosol feedbacks to be included in climate simulations.


No content yet


No content yet