Topic 1: The Atmosphere in Global Change

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About Topic 1

Mission:

Topic 1 addresses three research areas of societal relevance for the Atmosphere in Global Change: Air Quality, Climate Feedbacks, and Future Weather and Extremes. Knowledge in these areas provides guidance to assess adaptation and mitigation measures as we approach the 1.5°C global warming limit. We will develop observational and modeling solutions for improved atmospheric predictions and regional climate projections at unprecedented resolution, in a ‘whole atmosphere’ approach, to address entire process- and event chains from the drivers of global change or extreme events to their ramifications for air quality, water resources, greenhouse gas budgets, land use change, ecosystem viability, and the risk of more extreme weather in a warmer world.

Our focus:

The common goal of all work in Topic is to establish the scientific foundation for global change mitigation and adaptation measures that are regionally explicit, effective, and applicable. This requires the reliable modeling of coupling processes and interactions between all Earth system compartments relevant for climate change (atmosphere, ocean, cryosphere, land surface and biosphere, socio-economics), particularly on decadal temporal and regional spatial scales. To reach this long-term goal, we will further develop modeling components of compartment-crossing processes, in conjunction with integrated observation programs, and synthesize them into coupled regional modeling systems.

In detail we focus on the following objectives:

Assessment of future air quality and implications for human and environmental health in conjunction with climate change. To achieve this objective, we will determine consequences of global change for sources, sinks and transformation processes that affect air quality and atmospheric composition (incl. GHG), as well as their impacts on health, economy, and quality of life.

Reliable projections and predictions on the interconnected future developments of climate, atmosphere, and land use at global to regional scales, to assess future living conditions and options for the sustainable use of resources. For this objective, we will explore and quantify the feedback-web between physical, chemical, biological, and socio-economic processes and mechanisms in the Earth system, through the development of scale-crossing observation and modeling methodologies.

Improved predictive skill of natural hazards, like floods and droughts, with a strong application focus on adaptation to extreme weather and climate change, as well as disaster management. Towards this goal, we will assess extreme weather events in terms of their predictability and trends in frequency and magnitude with climate change, through in-depth knowledge of atmospheric processes gained in observational programs (e.g., MOSES), new observational techniques and complex numerical modeling at unprecedented resolution.

Integration and enhancement of multi-purpose and modular observational infrastructure toward a concerted ‘system of systems’ for atmospheric and climate research (ATMOsense, planned). Implementation of novel techniques for data assimilation will facilitate future approaches in model-data fusion.

To build up both IT infrastructure and expertise in the emerging field of environmental data science to an internationally leading level in atmospheric and climate research, following a coordinated strategy across the Program.

To assume an internationally leading role in regional Earth system modeling, and a formative role in the emerging national strategy on Earth system modeling, together with partners within the Program and the German research community at large. The planned new ATMOsense infrastructure will provide data for model evaluation across scales.

Establishment of an internationally leading structured qualification and talent management program in atmospheric and climate sciences, including all levels from students, graduate students to junior group leaders. Building blocks of such a program (specific to T1 needs) already exist in the participating centers.

Recent Highlights | Structure | Subtopics | Participating Centers | Contact

Recent Highlights

New utilization of GNSS data

A novel neural network model of Earth’s topside ionosphere

The Earth’s ionosphere affects the propagation of signals from the Global Navigation Satellite Systems (GNSS). The future appearance of the autonomous vehicles requires now more accurate GNSS navigation tools. The development of accurate models of the ionosphere has been a long-standing challenge. A new study presents a Neural network-based model of Electron density in the topside ionosphere (NET), which is constructed using 19 years of GNSS data.

Trace gas measurements in the stratosphere near Beaufort West

Jülich weather balloons over South Africa

Impact of submarine volcano eruption in January 2022

Global perturbation of stratospheric water and aerosol burden by Hunga eruption

Structure

Graphic Representation of Subtopics

Recent Highlights | Structure | Subtopics | Participating Centers | Contact

Subtopics in detail

The scientific goals of ST1.1 are to quantify the distribution of secondary pollutants in current atmospheric chemistry regimes and to project future changes in atmospheric composition with emphasis on climate-induced changes.

To predict future air quality, we need to understand emissions and their changes in the context of climate change, an evolving energy and transport system, urbanization and land use change, interactions of anthropogenic and biogenic emissions in atmospheric chemistry, and the spatial and temporal scales of atmospheric chemistry-climate interactions (linking all STs).

Spokesperson: Hendrik Fuchs (FZJ)
Deputy: Thomas Leisner (KIT)

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The main objective of ST1.2 is to unravel and quantify these feedbacks and interactions, in more detail and with improved temporal and spatial resolution, to significantly enhance the predictive power of future climate projections. This requires a concerted approach reaching from laboratory studies via field observation and utilization of satellite observations to high-resolution modeling.

ST1.2 research is closely aligned with international institutions, programs and initiatives such as the World Meteorological Organization (WMO), Stratospheric and Tropospheric Processes And their Role in Climate (WCRPSPARC), the International Space Science Institute (ISSI), Future Earth, COSPAR, SCOSTEP, IPCC, and IPBES. The international orientation of the Subtopic further benefits from long-standing collaborations with other leading international research organizations and universities.

Specific scientific objectives are:

Quantification of impacts of land use change and climate change on water availability and terrestrial GHG emissions, associated with diverse land use sectors, identification of related feedback mechanisms, and development of concepts for environmentally sound management of natural resources under conditions of global change.

Quantification of changes in atmospheric composition (including clouds) and circulation patterns (including Monsoon systems and Brewer-Dobson circulation) in a changing climate and improved representation of underlying processes in Earth system models.

Quantification of process chains that involve the stratosphere and the ocean, to improve our understanding of decadal variability down to seasonal and sub-seasonal predictability and to enhance the quality of regional climate change projections in Earth system models.

Quantification of forcing from below (atmosphere) and above (solar, magnetosphere) of the dynamics and composition in near-Earth space, and investigation of feedback mechanisms with the lower atmosphere.

Spokesperson: Peter Braesicke (KIT)
Deputy: Martin Riese (FZJ)

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The following objectives are stepping stones in a strategy to meet the challenges detailed above:

Develop and apply new observational systems on convective and synoptic weather systems and foster cross-platform integration. Atmospheric observation capabilities across scales and observation techniques are combined with modeling studies towards a better understanding of microphysical processes (AIDA) and mesoscale processes (KITcube). High-resolution models will allow us to bridge multiple spatial and time scales and to closely link with high-resolution observations, both from space and ground based.

Advance our atmospheric and Earth system modeling systems ICON/ICON-ART at the regional scale, with appropriate assimilation techniques and confronting the models with integrated observations. The focus is on enhanced spatial and time resolution (towards the km scale) and on aerosol and gas-phase processes not yet included in the modeling system.

Push the practical limits of predictability based on new modeling capabilities towards the provision of improved quantitative seamless forecasts of weather, composition, and extremes across scales, including those not yet covered by operational DWD services, e.g., sub-seasonal and decadal prediction. The focus ranges from local and regional weather forecasts of individual high-impact weather events to shifts in the occurrence frequency of extremes on climatic time scales.

Transfer the advances in weather and climate modeling for quantitative impact predictions towards tailored information for climate change adaptation. Special attention will be given to regions of high vulnerability and climate change hot spots (e.g., southern Europe, West Africa) and quantification of impacts associated with extreme weather.

Research in ST1.3 makes substantial contributions to internationally organized research agendas of WCRP and WWRP. This includes projects such as the High Impact Weather Project (HI-Weather), the sub-seasonal to seasonal (S2S) project, and CORDEX Flagship activities, which are closely linked to and strongly supported by ST1.3 researchers. Research is conducted in co-operation with our associated partner DWD and the European Center for Medium-Range Weather Forecasts (ECMWF) and is linked to the COPERNICUS climate service.

Spokesperson: Peter Knippertz (KIT)
Deputy: Jens Wickert (GFZ)

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