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Dr. Lisa Bock, German Aerospace Centre (DLR)

Evaluation of a new generation of global climate models (CMIP6)

Global climate models are the primary tools available for investigating the response of the climate system to various forcings, and for making projections of future climate. The climate simulations considered in reports informing policy makers, e.g. Intergovernmental Panel on Climate Change (IPCC),  are mostly based on Earth system model (ESM) experiments defined and internationally coordinated as part of the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project (CMIP). More than 40 model groups worldwide are participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6), providing a new and rich source of information to better understand past, present, and future climate and its changes in a multi-model context. Climate models have continuously been developed and improved over the last decades, and many models have been extended now by including more processes and couplings, primarily aimed at being able to better simulate future feedbacks (e.g. nitrogen effects of terrestrial carbon uptake or permafrost processes). To assess the credibility of future climate projections it is important to understand how well ESMs reproduce the historical climate and to systematically analyse, evaluate, understand, and document their simulated behaviour. Because of the increasing complexity of the models and rapidly growing data volumes, specialized evaluation tools are needed for a comprehensive, rapid, and reproducible performance assessment of the large number of models participating in CMIP. The first evaluation results of CMIP6 simulations show improvements compared to previous CMIP generations, and reveal significant reductions in long-standing biases of individual models and high-resolution versions of the models.

Dr. Daniel Huppmann, International Institute for Applied Systems Analysis (IIASA)

Climate change mitigation & sustainable development – Qualitative and quantitative analysis in the IPCC SR15

The IPCC’s Special Report on 1.5°C (SR15 [1]) assessed the possible impacts and mitigation options of global warming in the context of the UN’s Sustainable Developments Goals (SDGs). This talk illustrates how the SR15 tackled these questions from both a qualitative and a quantitative angle.

In a systematic review, Chapter 5 summarised the synergies and trade-offs of climate action (SDG13) with the other dimensions of sustainable development. It showed that demand-side climate policy measures generally have more positive co-benefits and less negative side-effects than decarbonisation efforts on the (energy) supply side.Complementing this qualitative analysis, Chapter 2 compiled and assessed an ensemble of quantitative, model-based emissions pathways to evaluate system transformation alternatives for reaching the Paris Agreement. Many of the headline statements widely reported in the media, like the imperative to reduce greenhouse gas emissions by 50% in a decade, are based on this scenario resource [2].

The talk also provides an overview of the suite of open tools to facilitate exploration of the scenario ensemble and increase transparency and reproducibility of the assessment. It highlights how the tools were implemented following the FAIR principles for open, collaborative research [3].

Links & Resources:

  1. IPCC SR15, 2018 – http://ipcc.ch/sr15/
  2. IAMC 1.5°C Scenario Explorer – https://data.ene.iiasa.ac.at/iamc-1.5c-explorer
  3. Huppmann et al., Nature Climate Change 8:1027-1030 (2018) doi: 10.1038/s41558-018-0317-4, open-access version: https://rdcu.be/9i8a

Dr. Lynn Kaack, ETH Zurich

Tackling climate change with machine learning

This talk aims to provide an overview of where machine learning (ML) can be applied with high impact to address climate change, through either effective engineering or innovative research. It looks at strategies both for mitigation (reducing greenhouse gas emissions) and for adaptation (preparing for unavoidable consequences). It will introduce several overarching ways in which ML can be helpful, including monitoring through remote sensing, accelerating scientific discovery, optimizing systems to improve efficiency, and accelerating physical simulations. [Many of the problems discussed highlight cutting-edge areas of ML, such as interpretability, causality, and uncertainty quantification. Moreover, meaningful action on climate problems can lead to interdisciplinary innovations, such as better physics-constrained ML techniques.] The talk will also take a deeper dive into applications relevant to policy analysis in the area of climate change mitigation.

Prof. Joanna Kargul, Centre of New Technologies, University of Warsaw (CeNT UW)

Biosolar technologies for production of  fuels and chemicals

Biosolar technologies form a relatively young and dynamic field of green nanotechnology which utilises photosynthetic organisms, such as cyanobacteria and algae, their photosynthetically active biological membranes or the components of the photosynthetic apparatus to harness solar energy and convert it into electricity and fuel. The attractiveness of this approach stems from the use of “living solar cells” or their photochemically active components which are capable of self-assembly and self-renewing, and which have been optimised for efficient solar energy conversion during over 3.5 billion years of evolution. 

For efficient “green” solar energy conversion, it is essential to develop new approaches for the rational design of highly efficient and viable (TRL 8 or higher) artificial photosynthetic devices by utilising state-of-the-art synthetic and biological photo-converting materials, as well as devising highly organised nanoarchitectures in order to make large gains in efficient solar energy conversion compared to the present-day technologies. Only by combining fundamental mechanistic studies of charge transfer within such biophotodevices with optimisation of the conductive molecular interface between the robust working modules operating at high quantum efficiencies can we tap the “holy grail” of a viable biohybrid solar-to-fuel technologies. 

I will overview recent advances in the field which show that biosolar technologies, when optimised, will provide a viable technological alternative to costly synthetic direct solar conversion technologies such as classical photovoltaics. 

Prof. Sean O’Donnell, Drexel University

Connecting climate change with the nervous system – mechanisms, evolution and attitudes

Directional climate change (global warming) is causing rapid alterations in animals’ environments. The central nervous system (CNS, especially the brain) is at the forefront of animals’ interactions with the environment. Neurobiological implications of climate change are central to understanding how individuals, and ultimately populations, will respond to global warming. There are individual level, mechanistic effects of climate change on nervous system development and performance. Climate change can also alter sensory stimuli, changing the effectiveness of sensory and cognitive systems. Comparative data show that brains evolve in response to environmental conditions, and natural selection imposed by directional climate change may drive rapid evolutionary changes in nervous system structure and function.

Prof. Rupert Seidl, Technical University Munich (TUM)

Climate change and forest ecosystems: Challenges and solutions

The unabated continuation of climate change is drastically altering the biosphere. Forest ecosystems are particularly affected by ongoing changes in the climate system because they are dominated by sessile and long-lived organisms, limiting their ability to adapt to the rapidly emerging novel environmental conditions. The resultant impacts of climate change on forests can have profound consequences for biodiversity and the supply of ecosystem services to society, and thus pose a considerable challenge for ecosystem management. Here I will synthesize the effects of climate change on forest dynamics. Specifically, I will focus on the effects of climate change on forest disturbances (i.e., large pulses of tree mortality) to illustrate how altered climate can influence important processes in forest ecosystems. I will conclude by illustrating possible pathways for addressing the impacts of climate change in forest management, highlighting the need to foster the climate resilience of forest ecosystems.

Prof. Linda Steg, University of Groningen

What motivates consumers to act sustainably

Many environmental problems are caused by human behaviour and can be altered when people would more consistently act sustainably. Common approaches to encourage pro-environmental behaviour typically target extrinsic motivation, by offering incentives that change personal costs and benefits of behaviour. I will explain why such approaches are not always as effective as assumed. Moreover, I will discuss factors and strategies that can foster and secure intrinsic motivation to engage in pro-environmental behaviour.Intrinsically motivated people behave without being coerced or incentivised, even when pro-environmental behaviour is somewhat costly, as doing so is meaningful and makes them feel good.