CRESCENDO publications

2016

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.

2017

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, doi.org/10.5194/gmd-10-2057-2017

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, dx.doi.org/10.1175/JCLI-D-16-0662.s1.

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.


2018

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2019

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2020

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