Description: The potential of Coastal Ocean Alkalinization (COA), a carbon dioxide removal (CDR) climate engineering strategy that chemically increases ocean carbon uptake and storage, is investigated with an Earth system model of intermediate complexity. The CDR potential and possible environmental side effects are estimated for various COA deployment scenarios, assuming olivine as the alkalinity source in ice-free coastal waters (about 8.6% of the global ocean's surface area), with dissolution rates being a function of grain size, ambient seawater temperature and pH. Our results indicate that for a large-enough olivine deployment of small-enough grain sizes (10 μm), atmospheric CO2 could be reduced by more than 800 GtC by the year 2100. However, COA with coarse olivine grains (1000 μm) has little CO2 sequestration potential on this time scale. Ambitious CDR with fine olivine grains would increase coastal aragonite saturation Ω to levels well beyond those that are currently observed. When imposing upper limits for aragonite saturation levels (Ωlim) in the grid boxes subject to COA (Ωlim = 3.4 and 9 chosen as examples), COA still has the potential to reduce atmospheric CO2 by 265 GtC (Ωlim=3.4) to 790 GtC (Ωlim=9) and increase ocean carbon storage by 290 Gt (Ωlim=3.4) to 913 Gt (Ωlim=9) by year 2100.

Description: To maintain the chance of keeping the average global temperature increase below 2 degrees C and to limit long-term climate change, removing carbon dioxide from the atmosphere (carbon dioxide removal, CDR) is becoming increasingly necessary. We analyze optimal and cost-effective climate policies in the dynamic integrated assessment model (IAM) of climate and the economy (DICE2016R) and investigate (1) the utilization of (ocean) CDR under different climate objectives, (2) the sensitivity of policies with respect to carbon cycle feedbacks, and (3) how well carbon cycle feedbacks are captured in the carbon cycle models used in state-of-the-art IAMs. Overall, the carbon cycle model in DICE2016R shows clear improvements compared to its predecessor, DICE2013R, capturing much better long-term dynamics and also oceanic carbon outgassing due to excess oceanic storage of carbon from CDR. However, this comes at the cost of a (too) tight short-term remaining emission budget, limiting the model suitability to analyze low-emission scenarios accurately. With DICE2016R, the compliance with the 2 degrees C goal is no longer feasible without negative emissions via CDR. Overall, the optimal amount of CDR has to take into account (1) the emission substitution effect and (2) compensation for carbon cycle feedbacks.

Description: The ice albedo feedback is one of the key factors of accelerated temperature increase in the high northern latitudes under global warming. This study assesses climate impacts and risks of idealized Arctic Ocean albedo modification (AOAM), a proposed climate engineering method, during transient cli- mate change simulations with varying representative concentration pathway (RCP) scenarios. We find no potential for reversing trends in all assessed Arctic climate metrics under increasing atmospheric CO2 con- centrations. AOAM only yields an initial offset during the first years after implementation. Nevertheless, sea ice loss can be delayed by 25(60) years in the RCP8.5(RCP4.5) scenario and the delayed thawing of perma- frost soils in the AOAM simulations prevents up to 40(32) Pg of carbon from being released by 2100. AOAM initially dampens the decline of the Atlantic Meridional Overturning and delays the onset of open ocean deep convection in the Nordic Seas under the RCP scenarios. Both these processes cause a subsurface warming signal in the AOAM simulations relative to the default RCP simulations with the potential to desta- bilize Arctic marine gas hydrates. Furthermore, in 2100, the RCP8.5 AOAM simulation diverts more from the 2005–2015 reference state in many climate metrics than the RCP4.5 simulation without AOAM. Considering the demonstrated risks, we conclude that concerning longer time scales, reductions in emissions remain the safest and most effective way to prevent severe changes in the Arctic.

Description: We used an earth system model of intermediate complexity to study the effects of Solar Radiation Management (SRM) by sea spray geoengineering on ocean biogeochemistry. SRM slightly decreased global ocean net primary productivity (NPP) relative to the control run. The lower temperatures in the SRM run decreased NPP directly but also indirectly increased NPP in some regions due to changes in nutrient availability resulting from changes in ocean stratification and circulation. Reduced light availability had a minor effect on global total NPP but a major regional effect near the nutrient rich upwelling region off the coast of Peru, where light availability is the main limiting factor for phytoplankton growth in our model. Unused nutrients from regions with decreased NPP also fueled NPP elsewhere. In the context of RCP4.5 simulation used here, SRM decreased ocean carbon uptake due to changes in atmospheric CO2 concentrations, seawater chemistry, NPP, temperature, and ocean circulation.

Description: First Workshop of the Carbon Dioxide Removal Model Intercomparison Project; Potsdam, Germany, 20–22 September 2016

Description: Selecting appropriate indicators is essential to aggregate the information provided by climate model outputs into a manageable set of relevant metrics on which assessments of climate engineering (CE) can be based. From all the variables potentially available from climate models, indicators need to be selected that are able to inform scientists and society on the development of the Earth system under CE, as well as on possible impacts and side effects of various ways of deploying CE or not. However, the indicators used so far have been largely identical to those used in climate change assessments and do not visibly reflect the fact that indicators for assessing CE (and thus the metrics composed of these indicators) may be different from those used to assess global warming. Until now, there has been little dedicated effort to identifying specific indicators and metrics for assessing CE. We here propose that such an effort should be facilitated by a more decision-oriented approach and an iterative procedure in close interaction between academia, decision makers, and stakeholders. Specifically, synergies and trade-offs between social objectives reflected by individual indicators, as well as decision-relevant uncertainties should be considered in the development of metrics, so that society can take informed decisions about climate policy measures under the impression of the options available, their likely effects and side effects, and the quality of the underlying knowledge base.

Description: Climate engineering (CE) measures are increasingly discussed when dealing with the adverse impacts of climate change. While much research has focused on individual methods, few studies attempt to compare and rank the effectiveness of these measures. Furthermore, model uncertainties are seldom acknowledged and lesser still, estimated when CE scenarios are assessed. In this work, we quantify the variance in outcomes due to poorly constrained model parameters under several idealized CE scenarios. The four scenarios considered are (1) warming under the high emission scenario Representative Concentration Pathway 8.5 without CE applied and the same emission scenario with (2) afforestation,(3) solar radiation management, and (4) artificial ocean alkalinization. By considering the parametric uncertainty in model outputs, we demonstrate the problems with comparing these scenarios using a single parameter setting. Using statistical emulation, we estimate the probability distributions of several model outcomes. Based on such distributions, we suggest an approach to ranking the effectiveness of the scenarios considered according to their probability of avoiding climate thresholds.

Description: Southern Ocean (SO) physical and biological processes are known to have a large impact on global biogeochemistry. However, the role that SO biology plays in determining ocean oxygen concentrations is not completely understood. These dynamics are investigated here by shutting off SO biology in two marine biogeochemical models. The results suggest that SO biological processes reduce the ocean's oxygen content, mainly in the deep ocean, by 14 to 19%. However, since these processes also trap nutrients that would otherwise be transported northward to fuel productivity and subsequent organic matter export, consumption, and the accompanying oxygen consumption in midlatitude to low-latitude waters, SO biology helps to maintain higher oxygen concentrations in these subsurface waters. Thereby, SO biology can influence the size of the tropical oxygen minimum zones. As a result of ocean circulation the link between SO biological processes and remote oxygen changes operates on decadal to centennial time scales.

Description: With almost 700 Pg of carbon, marine dissolved organic carbon (DOC) stores more carbon than all living biomass on Earth combined. However, the controls behind the persistence and the spatial patterns of DOC concentrations on the basin scale remain largely unknown, precluding quantitative assessments of the fate of this large carbon pool in a changing climate. Net removal rates of DOC along the overturning circulation suggest lifetimes of millennia. These net removal rates are in stark contrast to the turnover times of days to weeks of heterotrophic microorganisms, which are the main consumers of organic carbon in the ocean. Here, we present a dynamic “MICrobial DOC” model (MICDOC) with an explicit representation of picoheterotrophs to test whether ecological mechanisms may lead to observed decadal to millennial net removal rates. MICDOC is in line with 〉40,000 DOC observations. Contrary to other global models, the reactivity of DOC fractions is not prescribed, but emerges from a dynamic feedback between microbes and DOC governed by carbon and macronutrient availability. A colimitation of macronutrients and organic carbon on microbial DOC uptake explains 〉70% of the global variation of DOC concentrations, and governs characteristic features of its distribution. Here, decadal to millennial net removal rates emerge from microbial processes acting on time scales of days to weeks, suggesting that the temporal variability of the marine DOC inventory may be larger than previously thought. With MICDOC, we provide a foundation for assessing global effects on DOC related to changes in heterotrophic microbial communities in a future ocean Plain Language Summary The ocean stores more carbon as dissolved organic compounds (DOC) than all animals and plants on land and the oceans combined. However, numerical models used for future climate scenarios lack an implementation of processes transforming DOC back to CO 2 by marine microorganisms. Here, we present a global dynamical ocean model that explicitly considers the processes of DOC degradation by marine microorganisms. In the present ocean, the availability of organic carbon but also nitrogen and phosphorus control the amount of carbon stored as DOC, as the lack of these nutrients inhibits its degradation by bacteria. The identification of these ecological controls allows a quantitative assessment of the fate of this large carbon reservoir in the future. The findings indicate that the marine DOC reservoir is potentially more dynamic than previously thought, since decadal to millennial scale net removal rates might be a result of microbial processes acting on shorter time scales Key Points A model to reconcile millennial‐scale bulk dissolved organic carbon degradation rates and short‐term microbial turnover times is presented Macronutrient colimitation can explain observed concentration patterns of dissolved organic carbon in the surface ocean Continuous microbial reworking suggests a higher temporal variability of the marine dissolved organic matter inventory than previously thought