To anticipate impacts of climate change, science needs to better understand the interactions between climate, the biosphere, ecosystems and human activities. This research is supported by third-party-funded projects that are presented on this page.
Current research projects
The projects listed below are subprojects of joint projects funded by the German Research Foundation, the German Federal Ministry of Education and Research and the European Union.
Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, And Feedback Mechanisms
Funding: German Research Foundation
Period: 01.01.2020 – 31.12.2023
Planet earth has warmed on average by 0.87 K over the past 150 years. In the Arctic, the warming is much larger, which became most prominent over the last decades. Currently, the Arctic warming exceeds the increase of near-surface air temperature in the mid-latitudes by about 2 K. This phenomenon is commonly referred to as Arctic amplification.
-
Subproject D01: Large Scale Dynamical Mechanisms of Arctic amplification
Team: Prof. Dr. Johannes Quaas (PI), Prof. Dr. Christoph Jacobi (PI) -
Subproject D02: Modelling marine organic aerosol and its impact on clouds in the Arctic
Team: Dr. Jan Kretzschmar (PI), Iris Papakonstantinou-Presvelou, Fathima Cherichi Purayil - Subproject D04: Interaction of meridional ocean heat transports and regional processes in the Arctic Ocean
Team: Dr. Marc Salzmann (PI), Al Hajjar, Mohamad Khaled
- Subproject E01: Assessment of the Arctic lapse rate feedback using a multi-scale model hierarchy
Team: Prof. Dr. Johannes Quaas (PI) Olivia Linke, Sophie Vliegen - Subproject E06: Diagnosing moisture sources, transport and transformation with water vapor isotopes from satellites and in atmospheric modeling
Team: Prof. Dr. Johannes Quaas (PI), Hannah Marie Eichholz - Subproject Z04: Modeling infrastructure
Team: Prof. Dr. Johannes Quaas (PI)
Economics of Connected Natural Commons (ECO-N)
Funding: German Research Foundation
Air pollution, species loss, overfishing – the list of challenges to sustainable development is long. In most cases, it is people who have overexploited natural resources for economic gain: they have overfished the oceans, crowded out insects through unbalanced agricultural practices and polluted the air with industrial emissions. Some of these undesirable developments have already been partially reversed, but in some cases new problems have arisen. The new Research Training Group, Economics of Connected Natural Commons (ECO-N), will explore these complex interactions between economic demands, human behaviour and natural resources.
Revisiting the volcanic impact on atmosphere and climate – preparations for the next big volcanic eruption
Funding: German Research Foundation
The overarching goal of the DFG research unit VolImpact is to improve our understanding of how the climate system responds to volcanic eruptions. Due to new developments in observational and modelling capabilities we will now be able to answer questions that could not be addressed before. The project combines the expertise of world leading experts in complementary disciplines, which are all necessary to accomplish the selected research objectives. This includes skills in satellite remote sensing of atmospheric composition, stratospheric aerosol parameters and clouds as well as in modelling of aerosol microphysical and cloud processes, and in climate modelling.
Subproject: Science project 3: Cloud response to volcanic eruptions (VolCloud)
Period: 01.06.2019 – 31.05.2023 (part 1), 01.09.2022 – 31.08.2025 (part 2)
Team: Mahnoosh Haghighatnasab, Charlotte Lange, Prof. Dr. Johannes Quaas
Partner: Fatemeh Zarei, Prof. Dr. Corinna Hoose (Karlsruhe Institute of Technology)
VolCloud will treat the cloud response to volcanic eruptions due to aerosol-cloud interactions and cloud adjustments making use of a range of ICON simulations as well as of satellite data. Specific objectives are the qualititative and quantitative investigation of the following effects.
Learning about cloud-climate effects from machine-learning calibration of cloudparameters in climate models (LACCMACC)
Funding: German Research Foundation
Period: 01.11.2024 – 31.10.2027
Team: N.N., Prof. Dr. Johannes Quaas
LACCMACC addresses the representation of cloud- and precipitation mechanisms in atmospheric models with the aim to improve the understanding of their role for simulated cloud- climate effects. Specifically, both the cloud response to global warming, and the effective forcing due to aerosol-cloud interactions will be explored in revised simulations.
The key idea is that new machine-learning-based approaches allow for an objective „tuning“ of the empirical parameters in the process representations. LACCMACC will adapt and apply such a tool, the „HighTune“ method, in cooperation with its developers at the Laboratoire de Météorologie Dynamique in Paris, France (Frédéric Hourdin). HighTune will be applied to the ICON atmospheric model in kilometre-resolution configuration in regional and subsequently global setting. As a reference to the parameter choices this scheme will determine, LACCMACC will make use of process-oriented parameterisation evaluation approaches developed by the proposing team in the past. The final key step is to analyse parameter choices in their regional and spatial variation. The hypothesis is that inconsistencies, discrepancies and implausibilities of the choices as found by the machine-learning scheme in comparison to default values and to process-oriented evaluation will allow to conclude about systematic problems in parameterisations and possibly remedy these. A revised, optimal, set of parameters will be compared to default and process-evaluation-based settings in terms of simulated cloud-climate feedbacks and aerosol-cloud effective forcings.
CleanCloud
Funding: European Union
Period: 01.01.2024 – 31.12.2027
Team: Prof. Dr. Johannes Quaas, Dr. Alice Henkes
The European Union (EU) aims to be climate-neutral by 2050. This objective is at the heart of the European Green Deal (EGD) and in line with the EU’s commitment to global climate action under the Paris Agreement. Our ability to predict to what extent the Paris Agreement will be able to limit global warming is hampered by large uncertainties associated with our current understanding of the Earth system and its response to our actions. According to the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6), the interactions between aerosols and clouds still represent the largest uncertainty of past, present, and future radiative forcing and thus hamper the credibility of climate projections. Therefore, enhanced knowledge on aerosol-cloud interactions (ACI) is now more crucial to reduce uncertainties in short- and long-term climate projections and to plan mitigation and adaptation strategies for a climate-neutral future. At the heart of CleanCloud, there is the awareness that there will be no return to the preindustrial state, despite the continuous reductions of anthropogenic pollutants in the atmosphere, due to climate feedbacks and changes in land use, and that we are entering a new aerosol regime, which we call post-fossil. The post-fossil regime is characterized by strong reductions in fossil fuel combustion and a relatively larger role of natural aerosols, which also have a climate change driven component in sources and distribution, with respect to anthropogenic aerosols. In this state, we expect cleaner clouds compared to today, with consequences for precipitation - including thunderstorms and precipitation extremes - and climate forcing and its consequences. The overall objective of CleanCloud is to enhance our knowledge on ACI-related aerosol and cloud properties and processes, their regional and temporal differences, how they will evolve in the transition to the post-fossil regime, and in this way improve their representation in climate models, quantifying their impacts on weather and climate, and thus societies.
WarmWorld
Funding: Federal Ministry of Education and Research (BMBF)
Period: 01.03.2023 – 28.02.2027
Subproject: Calibrating liquid water cloud microphysics in ICON
Team: Dr. Karoline Block, Prof. Dr. Johannes Quaas
The aim of the project is to improve the depiction of energy fluxes, especially at the ocean surface. For this purpose, an improvement of the simulation of cloud and precipitation processes is to be achieved, which will be demonstrated with the evaluation of radiative fluxes at the upper edge of the atmosphere and at the ocean surface in comparison to satellite observations. Specifically, the microphysics will be improved by
(1) replacing the prescribed cloud condensation nuclei or cloud droplet number concentrations with improved boundary conditions,
(2) experimentally investigating the potential for improvement that can be achieved by taking subscale variability into account and
(3) systematically calibrating the empirical parameters concretely in autoconversion.
This is first achieved in concrete test simulations and then generalised to the global simulation. The project is planned in close cooperation in the action group "ICON" in the module "Better" and here in particular in direct cooperation with the project WarmWorld_Better_KIT.
Cloudiness change with aerosol trend reversal over China: data-model synergy from regional to large scale (Cloudtrend)
Funding: German Research Foundation
Period: 01.04.2021 – 31.03.2024
Team: Dr. Dipu Soudhakar, Prof. Dr. Johannes Quaas
The response of clouds to anthropogenic changes in atmospheric composition constitutes a large uncertainty when quantifying the effective forcing of global climate change. One key element is the response of clouds to aerosol emissions. In these aerosol-cloud interactions, it emerges currently as the key question how cloud horizontal extent, or cloud fraction, changes in adjustment to cloud droplet number concentration changes. Cloudtrend will substantially improve the understanding and quantification for this problem by building on three key ideas: (i) the very strong increasing then decreasing trends in anthropogenic aerosol emissions over China in the 21st Century provide a unique opportunity for a detection and attribution of aerosolinduced cloudiness changes in the high-quality data available from the surface and from satellites; (ii) new modelling and data analysis tools are available, including better satellite retrievals of cloud microphysics and new regime definitions, as well as the new CMIP6 multi-model data; and (iii) the large-scale data analysis and global climate modelling is proposed to systematically learn from the regional, high-quality data and modelling. The project is possible thanks to the synergy between the expertise in the teams at the Nanjing University of Information Science and Technology (regional focus) and the University of Leipzig (large-scale focus).
Cloud droplet number concentration from satellite observations enhanced with atmospheric modeling for aerosol-cloud interaction analysis.
Funding: German Research Foundation
Laufzeit: 01.03.2021 – 31.12.2024
Team: Dr. Tom Goren, Prof. Dr. Johannes Quaas
Aerosol-cloud interactions imply an effective radiative forcing that is a key uncertainty when understanding and interpreting observed climate change. Global data are needed to better quantify the relevant processes, but a key quantity – the cloud droplet number concentration (CDNC, Nd) - is not available from operational products. Building on preliminary work, CDNC4aci will work towards reliable retrievals of Nd from satellites in close observations – model interaction: newly-available cloud-resolving simulations will inform the retrieval development and refinement, and the data, in turn, will be used to improve understanding and quantificationaerosol-cloud interactions in the model and from statistical analysis. Specifically, the project will include multi-angle and polarimetric observations for better Nd data, it will revise retrieval approaches using model-informed cloud vertical stratification conditioned on cloud regime and thoroughly quantify and correct retrieval errors and biases and assess aerosol-cloud interaction processes from data. The project will assess the cloud-process information in the retrieved data using model sensitivity analyses, it will make model and data comparable by forward-simulating measured polarized radiances and retrieval products, and assess aerosol-cloud interactions inglobal model evaluated using the data and the process understanding in model-data assessment. The final goal is a consistent quantification of the aerosol-cloud forcing between model and data analysis.
Finished research projects
The projects listed below are finished subprojects of joint projects funded by the German Research Foundation, the German Federal Ministry of Education and Research and the European Union.
innovative MachIne leaRning to constrain Aerosol-cloud CLimate Impacts
Funding: This project receives funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No 860100.
Partner:
- University of Oxford
- Stockholm University,
- ETH Zurich,
- University of Edinburg,
- University of Valencia,
- Alan Touring Institute,
- DLR of Data Science,
- University College London
Science background
Anthropogenic climate change is one of the most urgent problems facing mankind. To avoid dangerous levels of global warming, the UN Conference of Parties 2015 in Paris reached a historic agreement to keep global mean temperature rise “well below” 2°C above pre-industrial levels. Anthropogenic aerosols have most likely offset some of the greenhouse warming to date, particularly through their interaction with clouds, however, despite decades of intensive research, significant uncertainties in the magnitude of this cooling still persist.
Innovative approach
Even though big datasets have been widely analysed to advance our understanding of aerosol-cloud climate interactions, many uncertainties remain and current methods are often inadequate, Artificial intelligence (AI) and machine learning, which are already revolutionising many areas of research, have not yet been fully applied in climate science – and scientists are not trained adequately. iMIRACLI proposes that merging of AI, machine learning and climate science will deliver a breakthrough in our understanding of the impact of aerosol-cloud interactions on climate.
Subproject: Detection of aerosol-cloud interactions in observations space
Period: 01.04.2020 – 31.12.2023
Team: Jessenia González Villareal, Prof. Dr. Johannes Quaas
A key problem in satellite-based analysis of aerosol-cloud interactions is the large and sometimes systematic uncertainty in the retrievals. ESR1 will perform the analysis in observations space (satellite-measured radiances) to assess signatures of aerosol-cloud-interactions without the need for retrievals in three steps: (1) information content analysis on the basis of simulations of aerosols and clouds and forward-simulated radiances; (2) optimisation of the detectability of aerosol-cloud co-variation in observations space through emulation based on large-scale Gaussian processes; (3) application of the emulator derivative for an assessment of the sensitivity of diverse observations signals to infer aerosol-induced perturbations to clouds.
Read More
Subproject: Identification of cloud regimes relevant for aerosol-cloud interactions
Period 01.04.2020 – 31.12.2023
Team: Julien Lenhardt, Prof. Dr. Johannes Quaas
Cloud are classified into types, classes, or regimes. The World Meteorological Organisation distinguishes stratus and cumulus clouds and three altitude layers. However, it has proven very difficult to define cloud regimes objectively. This will be achieved by (1) using high-spatially-, high-spectrally resolved satellite imagery combined with image processing and convolutional neural networks; by (2) combination with available high-resolved simulations for learning cloud types as a function of dynamics and thermodynamics using convolutional neural networks; and by (3) assessing the statistical relationships between cloud properties relevant to quantify and assess cloud adjustments to aerosol cloud interactions.
Read more
Constraining uncertainty of multi decadal climate projections
Funding This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 820829
Participants:
- German Aerospace Center
- CICERO - Senter for klimaforskning stiftelse
- The University of Reading
- Universität Wien
- Eidgenössische Technische Hochschule Zürich
- Universität Leipzig
- Technische Universiteit Delft
- Forschungszentrum Jülich GmbH
- Centre National de la Recherche Scientifique
- Zürcher Hochschule für angewandte Wissenschaften
Work Package 1: Advancing our knowledge on indirect aerosol effects
Period: 01.07.2019 – 31.03.2024
Team: Dr. Karoline Block, Dr. Alice Henkes, Olivia Linke, Prof. Dr. Johannes Quaas
Partner: CICERO - Senter for klimaforskning stiftelse
WP1 looks at why climate model simulations of effective radiative forcing (ERF) differ, and aims to quantify errors in the models. This is important for constraining climate sensitivity. There will be a focus on aerosol-cloud interactions and rapid adjustment mechanisms in order to understand both the processes and their uncertainties, and to make major improvements in model estimates of ERF as a result.
Advancing the Science for Aviation and Climate
Funding: This project receives funding from the European Union’s Horizon 2020 research and innovation programme grant agreement No 875036.
Participants:
- German Aerospace Center
- CICERO - Senter for klimaforskning stiftelse
- The University of Reading
- Universität Wien
- Eidgenössische Technische Hochschule Zürich
- Universität Leipzig
- TU Delft
- Forschungszentrum Jülich GmbH
- Centre National de la Recherche Scientifique
- Zürcher Hochschule für angewandte Wissenschaften
Subproject: Advancing our knowledge on indirect aerosol effects
Period: 01.01.2020 – 28.02.2024
Team: Sajedeh Marjani, Prof. Dr. Johannes Quaas
Constrained aerosol forcing for improved climate projections
Funding: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821205
The 2015 Paris Agreement adopted within the United Nations Framework Convention on Climate Change (UNFCCC) in December 2015, requires the majority of the world’s countries to limit global warming from anthropogenic activities within 2°C above pre-industrial levels. The actions needed to reach this goal, and the urgency and effectiveness of their implementation, rely crucially on accurately predicting the time-evolution of radiative forcing and the resulting climate response . Uncertainty in simulating the components of the atmosphere, especially those related to aerosol, clouds and their interactions severely hampers our ability to understand the past and project future climate change. This is because anthropogenic aerosols exert a net cooling impact on climate that offsets – but with large uncertainty – part of the warming effect from greenhouse gas emissions. As a result, the time left for achieving the necessary greenhouse gas reductions to achieve the PA target, and our understanding of the expected regional impacts of climate change, are hampered by the inability to robustly quantify the anthropogenic climate forcing associated with aerosols. In particular, the anticipated large reductions in aerosol emissions in the coming decades will result in a warming effect that is currently very poorly quantified. It is therefore crucial to establish the extent to which aerosol changes, whether due to anthropogenic emissions or as a feedback induced by warming, offset greenhouse gas warming.
Teilnehmer:
- Coordinator: Stockholm University
- ETH Zürich
- Karlsruhe Institute of Technology (KIT)
- Foundation for Research and Technology - Hellas - Institute of Chemical Engineering Sciences (FORTH)
- Royal Netherlands Meteorological Institute (KNMI)
- Universität Leipzig
- University of Helsinki
- National Research Council of Italy, Institute of Atmospheric Sciences and Climate
- Barcelona Supercomputing Center
- Norwegian Meteorological Institute
- University of Eastern Finland
- University of Leeds
- University of Oslo
- Forschungszentrum Jülich
- University of Oxford
- Finnish Meteorological Institute
- Swedish Meteorological and Hydrological Institute
- French National Institute for Industrial Environment and Risks
- International Institute for Applied Systems Analysis
- University of Exeter
- Sheffield Hallam University
- École Polytechnique Fédérale de Lausanne
Subproject: Understanding of cloud processes and aerosol-cloud interactions
Period: 01.10.2019 – 30.09.2023
Team: Dr. Dipu Soudhakar, Dr. Enrico Metzner, Iris Papakonstantinou-Presvelou, Prof. Dr. Johannes Quaas
Partner: Annele Virtanen (UEF)
This work package aims to improve the representation of cloud-, precipitation- and aerosol processes in earth system models, targeting a qualitatively more reliable simulation of effective radiative forcing due to aerosol–climate interactions.
Read More
ClimXtreme: Climate change and extreme weather events
Funding: Federal Ministry of Education and Research (BMBF)
The BMBF is supporting the first phase of the funding initiative, which will run from fall 2019 to early 2023, with €14 million for 40 individual projects. On behalf of the BMBF, the DLR Project Management Agency's Environment and Sustainability Division is providing technical and administrative support for the funding initiative.
Period: 01.03.2020 – 28.02.2023
Climate change may impact societies in particular by extreme events; extreme precipitation and lightning from deep convection (thunderstorms) are a particular threat. Anthropogenic modification of the atmospheric composition may drive changes in these events. Different from greenhouse gases and global warming, aerosol particle emissions may directly impact deep convection. This project will (i) assess the impact of aerosols on deep convection as simulated by the ICON regional model with existing large-domain large-eddy simulations, a multi-model ensemble, and ground-based observations as reference, and (ii) investigate in a probabilistic attribution framework (ensemble modelling of factual and counterfactual conditions) the impact of aerosols on extreme rain and lightning. Possible work in a second phase will investigate these in a long-term and global framework.
Subproject: Modul B - Statistics, Subproject 3, Probabilistic assignment of extreme precipitation to aerosol disturbances (PATTERA)
Team: Dr. Ribu Cherian, Prof. Dr. Johannes Quaas
The PATTERA project examines the contribution of anthropogenic aerosol emissions to the strength of precipitation events.
CHANCE difference between hemispheres in aerosol influence on cloud dissipation.
Funding: Federal Ministry of Education and Research (BMBF)
Period: 01.04.2020 – 31.12.2022
The aim of CHANCE is to better understand and quantify the adjustment of clouds in response to anthropogenic aerosol emissions. The focus is on the cloud regime most important for the resulting effective radiative forcing due to aerosol-cloud interactions, namely stratocumulus clouds; and the specific processes targeted are the cloud erosion, or sink terms which lead to the destabilisation and break-up of stratocumulus clouds. The way CHANCE will make progress on this is by analysing the hemispheric contrast, i.e. the differing responses to vastly different aerosol concentrations and large-scale environments. CHANCE will leverage the complementary expertise in modelling clouds and aerosol-cloud interactions at the contributing teams in Auckland and Leipzig.
Subproject: Aereosol Research
Team: Dr. Alice Henkes, Samuel Kwakye, Prof. Dr. Johannes Quaas
Partner: Dr. Gilles Bellon (University of Auckland)
Fusion of Radar Polarimetry and Numerical Atmospheric Modelling Towards an Improved Understanding of Cloud and Precipitation Processes
Funding: German Reserach Foundation
Cloud and precipitation processes are the main source of uncertainties in weather prediction and climate change projections since decades. A major part of these uncertainties can be attributed to missing observations suitable to challenge the representation of cloud and precipitation processes in atmospheric models. The whole atmosphere over Germany is since recently monitored by 17 state-of-the-art polarimetric Doppler weather radars, which provide every five minutes 3D information on the liquid and frozen precipitating particles and their movements on a sub-kilometer resolution, which is also approached by the atmospheric models for weather prediction and climate studies. Data assimilation merges observations and models for state estimation as a requisite for prediction and can be considered as a smart interpolation between observations while exploiting the physical consistency of atmospheric models as mathematical constraints. However, considerable knowledge gaps exist both in radar polarimetry and atmospheric models, which impede the full exploitation of the triangle radar polarimetry – atmospheric models – data assimilation and call for a coordinated interdisciplinary effort. The priority programme will exploit the synergy of the new observations and state-of-the-art atmospheric models to better understand moist processes in the atmosphere, and to improve their representation in climate- and weather prediction models. The programme will extend our scientific understanding at the verges of the three disciplines for better predictions of precipitating cloud systems by addressing the following objectives.
Subproject: Climate model PArameterizations informed by RAdar (PARA)
Period: 01.01.2019 – 30.06.2022
Team: Sabine Doktorowski, Prof. Dr. Johannes Quaas
Partner: Nikolaos Papaevangelou, Silke Trömel (Universität Bonn)
A first goal of the Univ. Leipzig contribution to PARA was the evaluation of the subgrid-scale variability of cloud ice (Fig. 1, top). In the ICON general circulation model (Giorgetta et al., 2018), the cloud horizontal subgrid-scale variability is represented in terms of a “critical relative humidity” framework (Sundqvist et al., 1989) that corresponds to a uniform distribution of total-water specific humidity around its grid-box mean value (Quaas, 2012). In the present study, only ice clouds are considered, and the cloudy part of each grid box is isolated, i.e. the total-water amount that is beyond the saturation specific humidity with respect to ice.
Atmospheric Model Data: Data quality, curation criteria, and DOI branding.
Funding: Federal Ministry of Education and Research (BMBF)
Period: 01.06.2019 – 31.05.2022
Partner:
- German Climate Computing Center (Deutsches Klimarechenzentrum, DKRZ)
- Leibniz Information Centre for Science and Technology University Library (Technische Informationsbibliothek, TIB)
- University of Hamburg, Meteorological Institute
The exchange and interpretation of climate model data is of importance far beyond the climate research community, but is currently hampered by the lack of comprehensive quality assurance measures and coordinated curation criteria. In meteorology and climate research, data quality and data curation standards are primarily established and applied in large, internationally coordinated model intercomparison studies (MIPs, e.g. Coupled Model Intercomparison Project - CMIP) in order to ensure effective partial and subsequent usability of research data.
Subproject of the working group Clouds and Global Climate
Atmosphere Monitoring Service (CAMS)
Förderung: CAMS is one of six services that form Copernicus, the European Union's Earth observation programme which looks at our planet and its environment for the ultimate benefit of all European citizens. Copernicus offers information services based on satellite Earth observation, in situ (non-satellite) data and modelling.
Subproject: Quantification of the radiative forcing by aerosol-cloud interactions based on CAMS reanalysis
Period: 01.07 2019 – 30.06.2020
Team: Dr. Karoline Block, Prof Dr. Johannes Quaas
Atmospheric and Earth system research with the "High Altitude and Long Range research Aircraft " (HALO)
Funding: German Research Foundation (DFG)
Period: 01.08 2016 – 31.07.2020
Project: A contribution to analysis and synthesis of HALO observations for satellite data- and modelevaluation and for radiative forcing assessment
The radiative forcing by anthropogenic aerosols via aerosol-cloud interactions is the main uncertainty in quantifying current forcing of climate change. While some progress has been achieved for liquid water clouds that dominate the forcing in the short-wave (solar) part of the electromagnetic spectrum, for the forcing in the long-wave (terrestrial) spectrum only crude estimates from general circulation models exist. In preliminary work, we have developed methods how active satellite remote sensing might be used to characterise ice crystal number concentrations and co-incident aerosol concentrations, and thus might allow for an assessment of the aerosol forcing in the solar, but especially also in the terrestrial spectrum. However, the satellite remote sensing data are highly uncertain and need to be validated using reference data. In FLASH, we propose to (i) validate the satellite ice crystal concentration and its sensitivity to temperature, vertical wind, and aerosol conditions using the observations now available from HALO (ACRIDICON and ML-CIRRUS campaigns), (ii) verify the spaceborne retrievals with airborne retrievals using the lidar and radar onboard HALO (NARVAL, NARVAL-II, and NAWDEX campaigns) that have better spatiotemporal resolution, (iii) evaluate and make use of climate model simulations for interpretation of the statistical relationships and (iv) work towards an estimate and uncertainty characterisation of the aerosol radiative forcing in the long-wave spectrum. Within SPP 1294, FLASH is intends to exploit the exiting data and work with upcoming data from multiple campaigns in an integrative way, towards the goals of achieving a better quantification of the aerosol-climate forcing, a validation of innovative and crucial satellite retrievals, as well as an evaluation and improvement of essential parameterisations in climate models.
Joint project: High Definition Clouds and Climate for Advancing Climate Prediction (HD(CP)²)
Funding: HD(CP)² is a Federal Ministry of Education and Research (BMBF) funded Germany-wide research initiative to improve our understanding of cloud and precipitation processes and their implications for climate prediction.
Period: 01.01.2016 – 31.12.2019
Cooperations:
- Max Planck Institute for Meteorology, Hamburg
- Institute of Geophysics and Meteorology, University of Cologne;
- Meteorologisches Institut, Universität Bonn;
- Institut für Weltraumwissenschaften, Freie Universität Berlin;
- Leibniz Institute of Tropospheric Research, Leipzig
HD(CP)² brought together more than 100 scientists from 19 different institutes all over Germany. Altogether there were 46 PhD student and Postdoc positions associated with the project, making HD(CP)² a vivid example for the scientific leadership of young researchers. In its second funding period the project's core elements were science teams consisting of people from many different institutes in order to answer these striking meteorological questions:
- How do clouds respond to pertubations in their aerosol environment?
- What are controlling factors for boundary layer clouds?
- What are controlling factors for anvil cloud development?
- To what extent does land-surface heterogeneity control clouds and precipitation?
- To what extent is convective organization important for climate?
- How do clouds and convection influence the development of the storm tracks?
Subprojects:
- SP 9: Active remote sensing of ice clouds for model evaluation (phase 1)
- SP 12: Overarching model evaluation (phase 2)
- SP 3: Evaluation of parameterizations of evaporation of precipitation using supersite observations (TP6: Rapid adjustment I: simulation of elevated CO2) (phase 2)
- SP 8: Detectability in observations (Phase 2)
Quantifying aerosol-cloud-climate effects by regime
Funding: Europaen Union (Grant agreement ID: 306284)
Period: 01.10 2012 -– 30.09.2017
Predictions of anthropogenic climate change are highly uncertain. They are hampered by the huge uncertainty of climate forcing, which is dominated by the uncertainty in anthropogenic aerosol-cloud-climate effects. QUAERERE (Latin for researching) aimed at a reliable, observations-based, global quantification of these effects. The approach was to develop new satellite data and analyse these statistically, in combination with climate modelling across scales. To do so, the problem was decomposed into individual processes on the one hand, and the analysis was performed for specific cloud regimes. We found that a new way is necessary to define cloud regimes - previous, widely-used approaches are mis-leading. For this, a new satellite product needed to be created, namely the cloud-base height. A new climatology of cloud condensation nuclei concentrations allowed to better quantify the aerosol-cloud forcing. A particular achievement was the first retrieval of ice crystal number concentrations from satellite data. This is sensitive to aerosol perturbations for cold clouds under strong updraught conditions. QUAERERE further examined how cloud fraction and cloud water content responds to perturbations in cloud droplet concentrations. Cloud fraction increases, implying more than a doubling of the initial effect. Overall, the project contributed substantially to clarify the role of aerosol forcing in climate change, correcting a mis-perception in the scientific debate that it might be very small. This was achieved by the satellite assessments, but also by a combination of observations and modelling, including a constraint on the simulated forcing exploiting the strong aerosol trends since the 1990s over Europe.
DFG-priority programme 1689: Climate Engineering: Risks, Challenges, Opportunities?
Funding: German Research Foundation (DFG)
Period: 01.01.2013 – 31.12.2018
Launched in May 2013, the German Research Foundation (DFG) Priority Programme (SPP) 1689 examines the risks and side effects of "Climate Engineering". The term Climate Engineering (CE) describes technological methods that could be used to mitigate or compensate for anthropogenic climate change by either reducing the atmospheric CO2 concentration or by directly changing the Earth’s radiation balance.
The main objectives of the Priority Programme 1689 are:
- Investigation of the climatic, ecological and social risks and potential effectiveness of different Climate Engineering methods
- Evaluation of the scientific and public perception of Climate Engineering
- Assessment – not development! – of Climate Engineering, including scientific, social, political, legal and ethical aspects
Project: LEarning About Cloud modification under risk and uncertainty: Investigation of feasibility, traceability, Incentives and decentralised governance of limited-area climate engineering
Partner: University of Kiel
Subprojects:
- LEAC-I: Analysis of satellite data and model results to assess how large in space and time a field experiment would have to be to determine with statistical significance the effectiveness of cloud seeting to mitigare climate change.
- LEAC-II contributes in particular to the cross-cutting themes "Metrics in view of decision under uncertainty" and "Liability, detection and attribution". Collaborations are particularly intense with the projects CELARIT, CEMICS2, ComparCE-2 and AWICIT.
Marine Stratocumulus Cloud Cover and Climate
Funding: This project receives funding from the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement No 703880.
Period: 2018
Global climate change is forced by the balance of the warming due to anthropogenic greenhouse gases and the cooling due to anthropogenic aerosol pollution particles. Among these, the cloud-mediated aerosol radiative forcing is by far the main component of the uncertainty. Marine stratocumulus clouds in particular play a decisive role due to their very large net effect on the Earth's radiative energy budget. Stratocumulus clouds occur in the two main regimes of open and closed cells that differ significantly by their cloud cover, and thus by their radiative effect. The main hypothesis of this proposal is that anthropogenic aerosols exert a substantial radiative forcing via their potential to impede or delay the transition from closed to open cells marine stratocumulus, and that this presumably un-buffered effect is not accounted for in forcing estimates by current climate models.
The Marine Stratocumulus Cloud Cover and Climate (MSCCC) project aimed to improve the quantification, at a global, multiyear scale, of the radiative forcing on climate that anthropogenic aerosols exert by affecting stratocumulus cloud cover. To achieve this goal an inter-disciplinary approach that involves both observations and climate modelling was required. I developes novel satellite observation methodologies in order to retrieve an in-depth understanding of the processes relevant for the transitions between closed and open stratocumulus regimes, and based on these I will evaluate and improve the relevant climate model parameterizations to realistically represent the forcing by aerosols due to stratocumulus transitions in climate models. This allowed to significantly reduce the uncertainty in simulated aerosol-cloud radiative forcing, and subsequently also in simulated climate sensitivity and projections of future climate change.
Monitoring Atmospheric Composition and Climate - Interim Implementation (MACC-II)
Funding: This project received funding from the FP7 funding programme for 2007 – 2013 under grant agreement No283576.
Period: 01.12.2012 – 31.12.2014
Partner:
- European Centre for Medium-Range Weather Forecasts - CMWF,
- University of Reading, Großbritannien
- Laboratoire de Météorologie Dynamique (LMD/CNRS), Frankreich
Subproject: Ermittlung des Strahlungsantriebs durch direkte und indirekte Aerosol-Effekte auf der Basis der assimilierten Aerosol-Verteilungen im IFS-Modell des EZMW.
Evaluating the CLimate and Air Quality ImPacts of Short-livEd Pollutants
Funding: This project received funding from the FP7 funding programme for 2007 – 2013 under grant agreement No282688.
Period: 01.11.2011 – 30.04.2013
Partners:
- Norwegian Institute for Air Research
- Center for International Climate and Environmental Research – Oslo
- Norwegian Meteorological Institute
- International Institute for Applied Systems Analysis
- Met Office
- Department of Meteorology, University of Reading
- Université Pierre et Marie Curie, Paris
- Institute of Chemical Engineering and High Temperature
- Chemical Processes (ICE-HT) of the Foundation for Research and Technology Hellas
- Institute for Meteorology, University of Leipzig
- College of Environmental Sciences and Engineering, Peking University
- Tsinghua University
ECLIPSE aims to develop and assess effective emission abatement strategies for short-lived climate agents in order to provide sound scientific advice on how to mitigate climate change while improving the quality of air. Current climate policy does not consider a range of short-lived gases and aerosols, and their precursors (including nitrogen oxides, volatile organic compounds, sulphate, and black carbon). These nevertheless make a significant contribution to climate change and directly influence air quality.
Subproject 6: Climate Responses
Partner: UK Met Office, Exeter, Großbritannien;
This WP will use climate integrations from models coupled to a full ocean representation in order to capturechanges in climate from short-lived climate forcers beyond the simple global surface temperature. Unlikeconfigurations with no ocean or a mixed-layer ocean, these coupled simulations will not be run to equilibrium.Instead comparisons between transient runs will be analysed. This will deliver a time dependent result which willbe more policy relevant than running to equilibrium.The experimental design will set up a number of parallel transient runs with a control and several experiments(with perturbed species). The difference between the experiments and the control will be quantified as a decadalaverage after 50 years of integration. Previous experience suggests that this length of integration is necessary toidentify a signal.
Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models
Funding:
Period: 2010 – 2014
Current numerical models of the atmosphere, both for numerical weather prediction (NWP) and for climate projection, have difficulties in accounting for unresolved variability, most notably, the variability associated with convection. Convection is a crucial driver of the atmospheric general circulation and is a key process for the vertical distribution of energy. It is responsible for the bulk of global precipitation. Among other known deficiencies of climate projections, global forecast models produce too early an onset of afternoon convection and fail to represent the 20-60 day planetary-scale tropical oscillation.
Current operational parameterizations use various ad hoc assumptions that often lack robust physical basis. The most notorious example is a closure that is required in order to define the total strength of convection produced by a parameterization. One more example is the rate of entrainment and detrainment characterizing the lateral exchange of air between a convective plume (convective tower) and environment. In spite of their critical importance in defining the vertical extent of deep convection, these parameters are currently simply tuned often in physically unreasonable way. More fundamentally, current parameterizations are designed to represent particular elements of the model physics (e.g., deep convection, boundary layer turbulence, radiation), whereas coupling between different physical processes (modules), that is crucial in view of the overall model performance, is to a large extend missing.
An increasing resolution poses new problems and requires a new generation of physical parameterizations. This is a challenge that urgently needs a strong action. Therefore, a core group focusing on Theoretical Studies of the Convection Parameterization Problem, a critical missing element, is implemented as COST Activity ES0905.