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14 pages, 6 figures, supplementary information .-- Data availability. Simulation data from gridded impact models is available through https://esg.pik-potsdam.de/projects/isimip2a/ and citable using the following DOIs: https://doi.org/10.5880/PIK.2017.002 (terrestrial ecosystems); https://doi.org/10.5880/PIK.2017.006 (agriculture); https://doi.org/10.5880/PIK.2017.010 (hydrology); https://doi.org/10.5880/PIK.2018.004 (marine ecosystems, regional); https://doi.org/10.5880/PIK.2018.005 (marine ecosystems, global). The city-level mortality model data and country-level hydropower model data are available from the authors upon request, Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought, The work was supported within the framework of the Leibniz Competition (SAW-2013-PIK-5), the EU FP7 project HELIX (grant no. FP7–603864–2), the FP7 project IMPACT2C (grant agreement#282746) and by the German Federal Ministry of Education and Research (BMBF, grant no. 01LS1201A1)

Food security has long been a challenge for human societies and will become an increasingly pressing global issue over the coming decades (Fischer, 2018). Although global food production has kept pace with population growth, close to 750 million people (or 10% of the global population) were exposed to severe levels of food insecurity in 2019 (FAO/IFAD/ UNICEF/WFP/WHO, 2020). Unfortunately, this number has increased even further over the course of 2020 due to the COVID-19 pandemic and its economic impacts worldwide. In the 2030 Agenda for Sustainable Development, Sustainable Development Goal (SDG) 2 aims to “end hunger, achieve food security and improved nutrition and promote sustainable agriculture” (UNGA, 2015). The food system is almost entirely supported by water, and agriculture uses the major share of global freshwater resources. However, water use for food production is being questioned continually as intersectoral competition for water intensifies and water scarcity increases. Additionally, in many regions of the world, water for food production is used inefficiently (D’Odorico et al., 2020). This is a major driver of environmental degradation, including depletion of aquifers, reduction of river flows, degradation of wildlife habitats, and pollution (Willett et al., 2019). A fundamental transformation of how water is being managed in the food system is therefore necessary if most of the SDG 2 targets are to be achieved by 2030, without further degradation of water resources to concurrently achieve SDG 6 to “ensure availability and sustainable management of water and sanitation for all” (IFPRI, 2019).

With a growing population and economic development, it is expected that water demands will increase significantly in the future, especially in developing regions. At the same time, climate change is expected to alter spatial patterns of precipitation and temperature and will have regional to localized impacts on water availability. Thus, it is important to assess water demand, water supply and environmental needs over time to identify the populations and locations that will be most affected by these changes linked to water scarcity, droughts and floods. The Community Water Model will be designed for this purpose in that they include an accounting of how future water demands will evolve in response to socioeconomic change and how water availability will change in response to climate. CWatM will represent one of the new key elements of the WAT program going forward and increasing the innovative niche of work. We will use and develop the model to work at both global and regional (basin) level. The configuration of the model is open source and community-driven to promote our work amongst the wider water community and is flexible enough to introduce further planned developments such as water quality and hydro-economy. Our vision for short to medium term work of the group is to introduce water quality (i.e., salinization in deltas and eutrophication associated with mega cities) into the community model and to consider how to include a qualitative/quantitative measure of transboundary river and groundwater governance into a scenario and modelling framework.

In recent years, deteriorated concrete slabs have been renewed, and precast concrete slabs have been used to shorten the construction period because of the need to regulate roads in service. Further, ground granulated blast-furnace slag (GGBFS) concrete, and epoxy-coated reinforcing bars are used for the precast concrete slabs to enhance durability. However, few studies were conducted on the results of exposure test with GGBFS concrete, and there is a risk of deterioration of epoxy-coated reinforcing bars by ultraviolet rays when precast slabs are placed and the bars are temporarily exposed. In this paper, an exposure test was carried out in Okinawa to assess the performance of concrete incorporating GGBFS and epoxy-coated reinforcing bars. As a result, GGBFS has high durability even in the long-term exposure condition, and epoxy-coated reinforcing bars also satisfies the standard in the temporary placement.

Histone H3 lysine‐9 di‐methylation (H3K9me2) and lysine‐27 tri‐methylation (H3K27me3) are linked to repression of gene expression, but the functions of repressive histone methylation dynamics during inflammatory responses remain enigmatic. Here, we report that lysine demethylases 7A (KDM7A) and 6A (UTX) play crucial roles in tumor necrosis factor (TNF)‐α signaling in endothelial cells (ECs), where they are regulated by a novel TNF‐α‐responsive microRNA, miR‐3679‐5p. TNF‐α rapidly induces co‐occupancy of KDM7A and UTX at nuclear factor kappa‐B (NF‐κB)‐associated elements in human ECs. KDM7A and UTX demethylate H3K9me2 and H3K27me3, respectively, and are both required for activation of NF‐κB‐dependent inflammatory genes. Chromosome conformation capture‐based methods furthermore uncover increased interactions between TNF‐α‐induced super enhancers at NF‐κB‐relevant loci, coinciding with KDM7A and UTX recruitments. Simultaneous pharmacological inhibition of KDM7A and UTX significantly reduces leukocyte adhesion in mice, establishing the biological and potential translational relevance of this mechanism. Collectively, these findings suggest that rapid erasure of repressive histone marks by KDM7A and UTX is essential for NF‐κB‐dependent regulation of genes that control inflammatory responses of ECs.

Global hydrological models (GHMs) have become an established tool to simulate water resources worldwide. Most of the GHMs are however uncalibrated and typically use a set of basic hydrological parameters, that could potentially lead to unrealistic projections of the terrestrial water cycle. The calibration of hydrological models is usually performed by using and comparing modeled to observed discharge. Accurate station data and reliable time series data of discharge are, however, often not available for many parts of the world and classic calibration approaches are therefore not feasible. In this paper, we aim to develop a new calibration approach that requires no additional data, is easy to implement, and substantially improves model performance, especially in regions where uncalibrated model performance is rather poor. This is achieved by using the Budyko framework, which provides a conceptual representation of the long‐term water and energy balance. We use a state‐of‐the‐art GHM and calibrate the model within nine river catchments of different sizes and characteristics. Since observed river discharge is available for these catchments, we are able to compare the Budyko‐based calibration approach to a classic discharge‐based calibration scheme and the uncalibrated model version. In all catchments, the Budyko‐based calibration approach decreases biases and increases model performance compared to the uncalibrated model version although performance improvements obtained through a classic calibration approach are greater. Nonetheless, a Budyko‐based calibration is a valuable, intermediate approach between use of a basic set of a priori hydrological parameters and classical calibration against discharge data.