ALBERT

Description: At regional to local scales internal variability is expected to be a dominant source of uncertainty in analyzing precipitation extremes and mean precipitation even far into the 21st century. A debated topic is whether a faster increase in subdaily precipitation extremes can be expected. Here we analyzed seasonal maximum precipitation in various time steps (3 hr, days, and 5 days) from a high-resolution 50-member large-ensemble (CRCM5-LE) and compared them to changes in mean precipitation over Europe. Our results show that the magnitude of change in extreme precipitation varies for season and duration. Subdaily extremes increase at higher rates than daily extremes and show higher scaling with temperature. Northern Europe shows widespread scaling above Clausius-Clapeyron of subdaily extremes in all seasons and for daily extremes in winter/spring. Scaling above Clausius-Clapeyron is also visible over Eastern Europe in winter/spring. For most regions and seasons the forced response emerges from the internal variability by midcentury.

Description: A diverse collection of models are used to simulate the marine boundary layer in the southeast Pacific region during the period of the October–November 2008 VOCALS REx (VAMOS Ocean Cloud Atmosphere Land Study Regional Experiment) field campaign. Regional models simulate the period continuously in boundary-forced free-running mode, while global forecast models and GCMs (general circulation models) are run in forecast mode. The models are compared to extensive observations along a line at 20° S extending westward from the South American coast. Most of the models simulate cloud and aerosol characteristics and gradients across the region that are recognizably similar to observations, despite the complex interaction of processes involved in the problem, many of which are parameterized or poorly resolved. Some models simulate the regional low cloud cover well, though many models underestimate MBL (marine boundary layer) depth near the coast. Most models qualitatively simulate the observed offshore gradients of SO2, sulfate aerosol, CCN (cloud condensation nuclei) concentration in the MBL as well as differences in concentration between the MBL and the free troposphere. Most models also qualitatively capture the decrease in cloud droplet number away from the coast. However, there are large quantitative intermodel differences in both means and gradients of these quantities. Many models are able to represent episodic offshore increases in cloud droplet number and aerosol concentrations associated with periods of offshore flow. Most models underestimate CCN (at 0.1% supersaturation) in the MBL and free troposphere. The GCMs also have difficulty simulating coastal gradients in CCN and cloud droplet number concentration near the coast. The overall performance of the models demonstrates their potential utility in simulating aerosol–cloud interactions in the MBL, though quantitative estimation of aerosol–cloud interactions and aerosol indirect effects of MBL clouds with these models remains uncertain.

Description: Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics. Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated toward larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses. In this paper, we describe the Sedimentary Geochemistry and Paleoenvironments Project (SGP; Figure 1), which is an open, community-oriented, database-driven research consortium. The goals of SGP are to (1) create a relational database tailored to the needs of the deep-time (millions to billions of years) sedimentary geochemical research community, including assembling and curating published and associated unpublished data; (2) create a website where data can be retrieved in a flexible way; and (3) build a collaborative consortium where researchers are incentivized to contribute data by giving them priority access and the opportunity to work on exciting questions in group papers. Finally, and more idealistically, the goal was to establish a culture of modern data management and data analysis in sedimentary geochemistry. Relative to many other fields, the main emphasis in our field has been on instrument measurement of sedimentary geochemical data rather than data analysis (compared with fields like ecology, for instance, where the post-experiment ANOVA (analysis of variance) is customary). Thus, the longer-term goal was to build a collaborative environment where geobiologists and geologists can work and learn together to assess changes in geochemical signatures through Earth history. With respect to the data product, SGP is focused on assembling a well-vetted and comprehensive dataset that is tractable to multivariate statistical analyses accounting for multiple geological and methodological biases. Phase 1 of the project, which focused on the Neoproterozoic and Paleozoic, has been completed. Future phases will capture a broader range of geologic time, data types, and geography. The database contains tens of thousands of unpublished data points provided by consortium members, as well as detailed metadata that go beyond what is contained in papers. In many cases, these represent measurements that are tangential to a given published study but still of high utility to database studies; these allow the community to address questions that would be impossible to answer solely with the published data. For instance, in order to use a proxy such as Mo/TOC (total organic carbon) ratios in mudrocks deposited under a euxinic water column, the full suite of trace metal, iron speciation, and total organic carbon data is needed. Likewise, geospatial information is required to account for sampling biases, and many statistical learning approaches cannot accept, or have difficulty with, incomplete geological predictor variables. Ultimately, it is this complete data matrix that will allow for SGP’s most insightful analyses.

Description: Southern Germany was subject to considerably adverse effects on water supply during recent hot and dry (compound) summers like 2022, 2018 or 2015. They included, but were not limited to drinking water scarcity, transport shortages, forest damages, and crop yield failures. Major rivers experienced extreme low flows which in parts caused or aggravated these effects. In order to categorize these (hydrological) drought events, we investigate the occurrence and extremeness of alike events in observational data and hydrological simulations in 98 southern German, Austrian and Swiss river catchments under current and climate change conditions. Low flow events correspond to days below a variable percentile threshold with respect to 1991-2020. Recently observed events serve as analogue for event type definition. Event type (e.g., 2018-type) specific characteristics include volume deficit, event duration, and spatial coverage. With this, we also address limitations and uncertainties related to event type definition. Since we aim at robustly quantifying these event types, their characteristics and implications, the sample size of observational records alone is insufficient. Therefore, we employ a large single model initial condition ensemble of a regional climate model (the Canadian Regional Climate Model, version 5; CRCM5-LE) to produce 50 instances of hydrological simulations (1960-2099) in the Water balance Simulation Model (WaSiM). This allows to also investigate currently extremely unlikely or newly emerging events. We further use the comprehensive sample of typified events in the ensemble to assess preceding meteorological and hydrological conditions to create a basis of potential drought predictors on catchment scale.

Description: Future projections indicate the Atlantic Meridional Overturning Circulation (AMOC) will weaken and shoal in response to global warming, but models disagree widely over the amount of weakening. We analyse the overturning pathways in 27 CMIP6 models to assess their impact on this weakening. Models with a larger pathway of North Atlantic Deep Water into the Indo-Pacific Ocean that is upwelled by diffusion, but does not later upwell in the Southern Ocean, weaken most in response to warming. The historical magnitude of this Indo-Pacific pathway is a stronger predictor of AMOC weakening than the historical AMOC strength. The strong relationship between this pathway and AMOC weakening is due, in part, to the historical magnitude of this pathway acting as an upper limit on the magnitude of its reduction. Decreases in this pathway are related to decreases in the Atlantic diffusive upwelling pathway, whereas the pathway that upwells via the Southern Ocean winds remains relatively steady. An emergent constraint relationship constrained by the Indo-Pacific pathway inferred from four observation-based estimates implies a wide range of AMOC weakening under a high greenhouse gas emission scenario of 29% to 61% by 2100. Our results suggest that improved observational constraints on this pathway could substantially reduce uncertainty in future AMOC decline.

Description: High impact low likelihood events such as a major slowdown of the Atlantic Meridional Overturning Circulation (AMOC) remain an area of uncertainty in the climate modelling, impacts, adaptation and policy making communities. In order to avoid policy lock-ins and maladaptation, it is important to explore the possible impacts of AMOC slowdown to inform adaptation and policy measures in the UK and Europe. Previous studies have demonstrated key impacts of AMOC slowdown on the UK and Europe such as changes in extreme events, temperature and precipitation patterns. However, the third UK Climate Change Risk Assessment identified AMOC strength and associated societal impacts as a key gap in understanding and a need for assessing related future climate risks and opportunities. Using approaches that include climate storylines, we use model runs with diverging AMOC responses to explore the potential impacts of an AMOC slowdown on the energy sector. As climate policy focuses on both mitigation (Net Zero) and adaptation to the impacts of climate change, this work is particularly relevant to renewable generation and changing energy demands.

Description: Climate change poses major challenges globally and is likely to exacerbate competition for water, land, and energy resources. In our study region, the Main River Basin (Germany), this will have considerable consequences affecting the water-environment-energy-food nexus. At present, most adaptation measures are sector-focused, but the challenges are interconnected. The region is at risk for being pushed beyond its resilience threshold and therefore, the future of water resources management must include holistic and multi-sectoral strategies to efficiently cope with climate change negative impacts. The co-design and co-production of science-driven technical, social, and cross-sectoral innovations and governance is required to build new and climate resilient transformation pathways. A systemic transformation of the region requires time and broad societal support, which must be considered when formulating development paths. To address these challenges, we implement Systems Innovation Approach (SIA), a method that facilitates going beyond the immediate problems to achieve a better understanding of the underlying patterns, and how we can learn and adapt to a continuously changing system. Among the pilot areas of the EU funded ARSINOE project (Climate-resilient regions through systemic solutions and innovation), the Main River Basin case study tackles water related challenges by implementing innovative technological approaches. To ensure stakeholders’ engagement a series of Workshops are held to explore the focal water-related issues, the future common vision and the innovative pathways that will solve the needs of the key actors. This contribution presents a successful experience turning research into practice, compiling lessons learnt and main challenges.

Description: The frequency of precipitation extremes is set to change in response to a warming climate. Thereby, the change in precipitation extreme event occurrence is influenced by both a shift in the mean and a change in variability. How large the individual contributions from either of them (mean or variability) to the change in precipitation extremes are, is largely unknown. This is however relevant for a better understanding of how and why climate extremes change. For this study, two sets of forcing experiments from the regional CRCM5 initial-condition large ensemble are used. A set of 50 members with historical and RCP8.5 forcing as well as a 35-member (700 year) ensemble of pre-industrial natural forcing. The concept of the probability risk ratio is used to partition the change in extreme event occurrence into contributions from a change in mean climate or a change in variability. The results show that the contributions from a change in variability are in parts equally important to changes in the mean, and can even exceed them. The level of contributions shows high spatial variation which underlines the importance of regional processes for changes in extremes. Further, the results reveal a smaller influence of the level of warming and level of extremeness on the individual contributions then the seasonality or temporal aggregation (3h, 24h, 72h).