Ansatz einer umfassenden, vergleichenden Bewertung von Climate Engineering Massnahmen: Metriken, Indikatoren und Unsicherheiten

Climate Engineering (CE) as an option to prevent dangerous climate change has reached the political debate. For a well informed decision on CE research and deployment in the future, work towards a comprehensive, comparative assessment is needed. In the first part of this thesis, climate impacts and side effects of an artificial Arctic ocean albedo modification scheme are studied. The second part of this thesis presents a parameter sensitivity study on the uncertainty in the response of transpiration to CO2 and implications for climate change. Is the application of indicators used for the historical time period valid for a comprehensive assessment of future climate change? In the third part of the thesis we introduce a methodological approach to systematically evaluate correlation matrices, identifying robust indicators from Earth system variables, to be used in a natural-science based assessment. In the fourth part of this thesis this method is applied to three exemplary CE scenarios: Large-scale afforestation, ocean alkalinity enhancement and solar radiation management. Changes in correlation patterns provide information on which variables might become more relevant under CE scenarios. To enable a comprehensive comparison of the three scenarios, the common correlation matrix is systematically evaluated to identify an indicator set. A preliminary evaluation of the three scenarios based on these indicators remains inconclusive. If the indicators are further aggregated into a metric to reduce the complexity, a ranking of the different scenarios becomes evident. Given all assumptions, we find that overall the RCP4.5 scenario performs ’best’ in staying close to todays climate state. Solar Radiation Management is identified as the ’best’ CE scenario, followed by Ocean Alkalinity Enhancement and Large-scale Afforestation. These analyses advance the natural-science based assessment of CE, which is essential prior to a decision making process.Auf politischer Ebene hat man begonnen über Climate Engineering (CE) als mögliche Option gegen den mensch-gemachten Klimawandel zu sprechen. Um gut informierte Entscheidungen zum Thema zukünftiger Forschung oder potentiellen Umsetzung von CE Massnahmen zu treffen, benötigt man eine umfassende und vergleichende Einschätzung der verschiedenen Methoden. Im ersten Teil der Arbeit werden Effekte und Nebenwirkungen der CE Methode Ozeanoberlächenaufhellung in der Arktis (AOAM) untersucht. Im zweiten Teil der Arbeit wird eine Parameter Studie zur CO2 Sensitivität von Vegetationstranspiration vorgestellt. Ist es ausreichend die Indikatoren für die historische Zeitspanne zu benutzen, um zukünftigen Klimawandel umfassend zu beschreiben? Im dritten Teil der Arbeit wird eine Methodik eingeführt, um systematisch Korrelationsmatrizen auszuwerten. Das ermöglicht die Identifizierung eines Indikatorensets für eine umfassende, naturwissenschaftliche Beurteilung der gegebenen Fragestellung. Im vierten Teil der Arbeit wird diese Methode auf drei CE Szenarien angewendet, wodurch Änderungen in den jeweiligen Korrelationsmustern gegenüber der zwei Klimawandel Szenarien identifiziert werden können. Eine erste Beurteilung der drei exemplarischen CE Methoden, basierend auf den ausgewählten Indikatoren, bleibt zunächst ergebnislos. Erst wenn die Indikatoren zu einer Metrik zusammen gefasst werden, gelangen wir zu einem klareren Ranking der Szenarien. Unter den gegebenen Annahmen, stellen wir fest, dass das RCP4.5 Szenario am nächsten an dem gewählten Referenzklimazustand bleibt. Das Strahlungsmanagement Szenario ist das ’beste’ CE Szenario, gefolgt von der Ozeankalkung und der gross-skaligen Aufforstung. Diese Analysen bringen das naturwissenschaftliche Verständnis von verschiedenen CE Methoden voran, welches massgeblich für eine spätere Entscheidungsfindung ist

Korrelationen zwischen Änderungen des Windstresses, des Meeresspiegels und der Dichteschichtung im atlantischen Sektor des Südlichen Ozeans im Bezug auf den Jahresgang und auf zwischenjährliche Zeitskalen

Due to the increasing data coverage of the Southern Ocean by programs like the Argo Float Program, an analysis for this area concerning seasonal timescales is possible (Sallee). During the last three decades observations show an increase of the Southern Hemisphere westerlies (Visbeck (2007)). In most of the climate projections this trend tends to continue (Böning et. al. (2008)). By now the reactions of the Antarctic Circumpolar Current (Antarctic Circumpolar Current) concerning these changes in wind stress are not sufficiently clarified as well as in what timescales theses reactions might occur. In this bachelor thesis it is examined whether correlations can be found between changes in wind stress, in the steepness of the sea surface and stratification using CERSAT- scatterometer, AVISO - altimeter and Argo float data. These studies concern seasonal and interannual timescales. Therefore the chronological sequence of the mean wind stress from 40◦S to 55◦S, as well as the variation in time of the height differences of the sea surface and depth differences of the sigma27.2 density surface between 40◦S and 55◦S are observed. As a conclusion the development of the density surface on seasonal timescales arises to 61% from the influence of the wind stress. There is a time lag of two months between the wind stress and the reaction in the isopycnal tilt. The strength of the influence of the sea surface steepness is still uncertain. It is not possible to state clear positions concerning correlations on interannual timescales, as the time series of the float-data is too short (five years) for exact calculations

Non-CO2 forcing changes will likely decrease the remaining carbon budget for 1.5°C

One key contribution to the wide range of 1.5 degrees C carbon budgets among recent studies is the non-CO2 climate forcing scenario uncertainty. Based on a partitioning of historical non-CO2 forcing, we show that currently there is a net negative non-CO2 forcing from fossil fuel combustion (FFC), and a net positive non-CO2 climate forcing from land-use change (LUC) and agricultural activities. We perform a set of future simulations in which we prescribed a 1.5 degrees C temperature stabilisation trajectory, and diagnosed the resulting 1.5 degrees C carbon budgets. Using the historical partitioning, we then prescribed adjusted non-CO2 forcing scenarios consistent with our model's simulated decrease in FFC CO2 emissions. We compared the diagnosed carbon budgets from these adjusted scenarios to those resulting from the default RCP scenario's non-CO2 forcing, and to a scenario in which proportionality between future CO2 and non-CO2 forcing is assumed. We find a wide range of carbon budget estimates across scenarios, with the largest budget emerging from the scenario with assumed proportionality of CO2 and non-CO2 forcing. Furthermore, our adjusted-RCP scenarios produce carbon budgets that are smaller than the corresponding default RCP scenarios. Our results suggest that ambitious mitigation scenarios will likely be characterised by an increasing contribution of non-CO2 forcing, and that an assumption of continued proportionality between CO2 and non-CO2 forcing would lead to an overestimate of the remaining carbon budget. Maintaining such proportionality under ambitious fossil fuel mitigation would require mitigation of non-CO2 emissions at a rate that is substantially faster than found in the standard RCP scenarios

Systematic Correlation Matrix Evaluation (SCoMaE) – a bottom–up, science-led approach to identifying indicators

This study introduces the Systematic Correlation Matrix Evaluation (SCoMaE) method, a bottom–up approach which combines expert judgment and statistical information to systematically select transparent, nonredundant indicators for a comprehensive assessment of the state of the Earth system. The methods consists of two basic steps: (1) the calculation of a correlation matrix among variables relevant for a given research question and (2) the systematic evaluation of the matrix, to identify clusters of variables with similar behavior and respective mutually independent indicators. Optional further analysis steps include (3) the interpretation of the identified clusters, enabling a learning effect from the selection of indicators, (4) testing the robustness of identified clusters with respect to changes in forcing or boundary conditions, (5) enabling a comparative assessment of varying scenarios by constructing and evaluating a common correlation matrix, and (6) the inclusion of expert judgment, for example, to prescribe indicators, to allow for considerations other than statistical consistency. The example application of the SCoMaE method to Earth system model output forced by different CO2 emission scenarios reveals the necessity of reevaluating indicators identified in a historical scenario simulation for an accurate assessment of an intermediate–high, as well as a business-as-usual, climate change scenario simulation. This necessity arises from changes in prevailing correlations in the Earth system under varying climate forcing. For a comparative assessment of the three climate change scenarios, we construct and evaluate a common correlation matrix, in which we identify robust correlations between variables across the three considered scenarios

Calcifying Phytoplankton Demonstrate an Enhanced Role in Greenhouse Atmospheric CO2 Regulation

The impact of calcifying phytoplankton on atmospheric CO2 concentration is determined by a number of factors, including their degree of ecological success as well as the buffering capacity of the ocean/marine sediment system. The relative importance of these factors has changed over Earth's history and this has implications for atmospheric CO2 and climate regulation. We explore some of these implications with four “Strangelove” experiments: two in which soft-tissue production and calcification is stopped, and two in which only calcite production is forced to stop, in idealized icehouse and greenhouse climates. We find that in the icehouse climate the loss of calcifiers compensates the atmospheric CO2 impact of the loss of all phytoplankton by roughly one-sixth. But in the greenhouse climate the loss of calcifiers compensates the loss of all phytoplankton by about half. This increased impact on atmospheric CO2 concentration is due to the combination of higher rates of pelagic calcification due to warmer temperatures and weaker buffering due to widespread acidification in the greenhouse ocean. However, the greenhouse atmospheric temperature response per unit of CO2 change to removing ocean soft-tissue production and calcification is only one-fourth that in an icehouse climate, owing to the logarithmic radiative forcing dependency on atmospheric CO2 thereby reducing the climate feedback of mass extinction. This decoupling of carbon cycle and temperature sensitivities offers a mechanism to explain the dichotomy of both enhanced climate stability and destabilization of the carbonate compensation depth in greenhouse climates

Uncertainty in the response of transpiration to CO2 and implications for climate change

While terrestrial precipitation is a societally highly relevant climate variable, there is little consensus among climate models about its projected 21st century changes. An important source of precipitable water over land is plant transpiration. Plants control transpiration by opening and closing their stomata. The sensitivity of this process to increasing CO2 concentrations is uncertain. To assess the impact of this uncertainty on future climate, we perform experiments with an intermediate complexity Earth System Climate Model (UVic ESCM) for a range of model-imposed transpiration-sensitivities to CO2. Changing the sensitivity of transpiration to CO2 causes simulated terrestrial precipitation to change by −10% to +27% by 2100 under a high emission scenario. This study emphasises the importance of an improved assessment of the dynamics of environmental impact on vegetation to better predict future changes of the terrestrial hydrological and carbon cycles

Assessing climate impacts and risks of ocean albedo modification in the Arctic

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

1.5 °C carbon budget dependent on carbon cycle uncertainty and future non-CO2 forcing

Estimates of the 1.5 °C carbon budget vary widely among recent studies, emphasizing the need to better understand and quantify key sources of uncertainty. Here we quantify the impact of carbon cycle uncertainty and non-CO2 forcing on the 1.5 °C carbon budget in the context of a prescribed 1.5 °C temperature stabilization scenario. We use Bayes theorem to weight members of a perturbed parameter ensemble with varying land and ocean carbon uptake, to derive an estimate for the fossil fuel (FF) carbon budget of 469 PgC since 1850, with a 95% likelihood range of (411,528) PgC. CO2 emissions from land-use change (LUC) add about 230 PgC. Our best estimate of the total (FF + LUC) carbon budget for 1.5 °C is therefore 699 PgC, which corresponds to about 11 years of current emissions. Non-CO2 greenhouse gas and aerosol emissions represent equivalent cumulative CO2 emissions of about 510 PgC and −180 PgC for 1.5 °C, respectively. The increased LUC, high non-CO2 emissions and decreased aerosols in our scenario, cause the long-term FF carbon budget to decrease following temperature stabilization. In this scenario, negative emissions would be required to compensate not only for the increasing non-CO2 climate forcing, but also for the declining natural carbon sinks

Project Briefing #4 Defining the scenario approach

The aim of this Project Briefing is a clear definition of the various dimensions of our scenario approach in Net-Zero-2050. Starting from the overarching framework, we then describe, how scenarios are applied in the various projects. We define the scope and focus of the energy scenarios and the scenarios for Carbon Dioxide Removal measures, as well as the interface between both approaches