Talks

Thursday, 29.05.

Stefan Bühler

Atmospheric Science in Hamburg and Insights into Shortwave Water Vapor Feedback

The talk will start with a brief overview of atmospheric science research at the University of Hamburg, highlighting key areas of focus and recent developments. I will then delve into a specific research topic from my group, exploring the findings of a recent paper by former PhD student Florian Römer. This work advances our fundamental understanding of the shortwave clear-sky water vapor feedback in climate physics. In a warmer world, atmospheric humidity increases. While most studies have focused on the longwave effects - where water vapor acts as a potent greenhouse gas, reinforcing warming - our research demonstrates that the shortwave impact is also positive. Using a simple yet powerful conceptual model, we quantify and explain this effect, shedding light on a somewhat neglected climate feedback mechanism.

Volker Matthias

Shipping emissions and their impact on air quality in coastal regions

Ships are large emitters of air pollutants, particularly NOx, SOx, and aerosol particles. Because shipping lanes are often close to the coast, these emissions have a significant impact on the air quality in populated areas. In addition, they may interact with other land-based emissions, e.g. ammonia from agricultural activities, and form new aerosol particles. The presentation shows how state-of-the-art ship emission models work and how large the impact of these emissions on air quality in coastal regions and harbor cities is. The chemistry transport model application that is applied also allows to investigate mitigation options and to study the consequences of tightened regulations. Finally, I will briefly discuss the interaction of ship emissions with clouds and the effects on climate.

Nedjeljka Žagar

On the memory of observations in numerical model predictions

The accuracy of weather forecasts depends on the quality of the numerical model and the observations that define the initial state for forecasts. During the forecasting process, initially small errors grow, and eventually, the effect of observations is lost. This growth process of forecast errors is scale-dependent, and the scale dependency varies across the globe, exhibiting different characteristics in the tropics, middle latitudes, and polar regions. In this talk, I will discuss how we evaluate the memory of observations in numerical weather prediction and estimate the potential benefits of future observing systems that require significant investments, such as future satellites.

Markus Dressel

Follow the science? The contested role of science in policymaking

The role of science in politics remains a contentious issue. Numerous attempts have been made to define the “right” way for science to engage with policymaking - whether through neutral expertise, scientific advocacy, or participatory co-creation. However, this talk argues that no single definition can fully capture the complexity of the science-policy interface. The appropriate relationship between science and politics depends on a range of fundamental philosophical questions, including the role of social values in science, the nature of epistemic uncertainty, the epistemic and moral status of expert advice, and the conditions under which science can or should influence political decisions. These questions are not only widely debated among scholars of science and society but are also interpreted differently by scientists, policymakers, and the public. This talk will explore key philosophical perspectives that shape our understanding of the science-policy relationship and illustrate how different assumptions lead to competing models of interaction. By examining these foundational issues, it aims to provide a framework for critically reflecting on the diversity of possible science-policy arrangements and their normative implications.

Felix Ament

Meteorological basics reloaded - educational short stories from Hamburg Wettermast

Meteorological basics can not only be understood by theory or simulated on the computer, nature shows us a lot every day. You just have to go outside and take some measurements. Fortunately, the 300m high Hamburg Wettermast has been doing this job continuously for the last 30 years. This data set contains an incredible amount of exciting “everyday meteorology”! We’ll present you a couple of short stories that reflect the beauty of meteorological theory out in nature.

Saturday, 31.05.

Raphaela Vogel

How the evaporation of tiny rain drops influences weather and climate

Warm rain processes such as rain evaporation, downdrafts, and cold pools have an important but poorly understood influence on cloud cover in trade wind regions. Cold pools created by rain evaporation increase cloud cover by triggering arcs of new clouds at the gust front. At the same time, they reduce cloudiness within the cloud arcs by suppressing convection. High-resolution modeling studies have also shown that cold pools can both organize and disorganize shallow convection. Unfortunately, we do not know which of these opposing effects of cold pools on the coverage and organization of cloudiness dominates. These knowledge gaps are closely related to the lack of robust observations of the rain processes and the uncertain skill of high- resolution models in simulating them. In this talk, I describe my group’s approach to closing these knowledge gaps by creating a multi-year dataset of rain evaporation, downdrafts, and cold pools, and calculating and evaluating large-eddy simulations using Lagrangian super-droplet microphysics.

Leonard Borchert

Predicting Climate Extremes: a Multifaceted Research Problem

Prediction of near-term climate variability, on the order of months to years, is crucial for decision making. In particular, knowledge about future climate extremes is important. However, there are multiple challenges involved in producing actionable climate information on these time scales. On the social science end of the problem, the production and communication of climate information that is actually useful for decision makers requires co-design of climate prediction products with end users. Among other things, these activities can give insights into how information is taken up and processed in society. On the physical science end, the monthly-to-interannual time scale is challenging because both boundary forcing and initial value memory overlap, posing a particular challenge to climate models. In this talk, I outline some of the main challenges in predicting climate extremes and making those predictions actionable, discussing potential solutions to these challenges.

Peter Lemke

And yet the Earth is warming! - Remarks on climate research: from the first steps to the Nobel Prize in Physics

Discussions about climate started centuries ago. The first to suggest in the 1820s that the atmosphere acts as a blanket to keep Earth’s surface warmer than it should be, was Joseph Fourier. He described what we today call the Greenhouse Effect. An experimental investigation of the radiative absorption of CO2 was first undertaken by Eunice Foote in 1856. In 1896 Svante Arrhenius calculated the effect of doubling CO2 on the surface air temperature to be 5-6°C. In his calculations in 1931, Hurlburt reduced this increase to 4°C. The first comprehensive radiative-convective model for the atmosphere was presented by Manabe and Wetherald in 1967. They showed that an increase of CO2 in the atmosphere resulted in a warming in the troposphere and a cooling in the stratosphere, as observations show. Manabe was the driving force to develop comprehensive models of the climate and Earth systems in the coming decades. For his contributions to the understanding of the climate system he was awarded a quarter of the Nobel Prize in Physics in 2021. For a long time, it was not clear how to find the signal of rising CO2 in the temperature records of the noisy environment of weather and climate variability. In 1976, Hasselmann suggested that changes of the slow climate variables are generated by the white noise forcing of the atmospheric weather. He also developed in the 1990s methods to find the “fingerprints” of human impacts on climate variability. These methods have been intensively applied to recent climate integrations describing various futures of Earth’s climate. On the basis of these applications, we can now state that the Earth is warming – and we are to blame. For his contributions to the understanding of the stochastic nature of the climate system and the human fingerprint on climate warming, Klaus Hasselmann was awarded a quarter of the 2021 Nobel Prize in Physics.

Chris Kadow

The technology deleting photo bombs can do climate research? The chat bot writing poems can do real climate analysis?

Climate change research today relies on climate information from the past. Historical climate records of temperature observations form global gridded datasets that are examined, for example, in IPCC reports. However, the datasets combining measurement records are sparse in the past. Even today, they contain missing values. We found that recently successful image inpainting technologies, such as those found on smartphones to get rid of unwanted objects or people in photos, are useful here. The derived AI networks are able to reconstruct artificially cropped versions in the grid space for any given month using the missing values observation mask. So herewith we have found with AI a technique that gives us data from the past that we never measured with instruments. Other important datasets used in the Assessment Report 6 of the IPCC to study climate change, as well as advanced applications such as downscaling in atmosphere and ocean, a hybrid (AI&ESM) data assimilation approach within the German Earth system model ICON, or precipitation in broken radar fields are shown in this presentation. Climate research, including the study mentioned in the previous paragraph, often requires substantial technical expertise. This involves managing data standards, various file formats, software engineering, and high-performance computing. Translating scientific questions into code that can answer them demands significant effort. The question is, why? Data analysis platforms like Freva (Kadow et al. 2021, e.g., gems.dkrz.de) aim to enhance user convenience, yet programming expertise is still required. In this context, we introduce statistical applications chat bot interface with a large language model (LLM) setup as GPT-4/ChatGPT, LLAMA or DeepSeek at its core, which enables climate analysis without technical obstacles, including language barriers. This approach is tailored to the needs of the broader climate community, which deals with massive data sets from kilometer-scale modeling and requires a processing environment utilizing modern technologies, but addressing society after all - such as those in the Earth Virtualization Engines (EVE eve4climate.org).