39 research outputs found

    Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

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    Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We find a negative relationship between these controls that weakens the forecast skills, nevertheless there is a middle ground between both controls in several catchments, as shown by our results

    Sustainable corporate development measured by intangible and tangible resources as well as targeted by safeguard subjects

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    The needed shift towards sustainable development in existing business processes can be achieved through the combination of the capital based approach and the life cycle sustainability assessment. This contribution performs an analysis and selection of assessment tools and indicators regarding the resources used in organisational processes and the life cycle of the products or services to measure the potential impacts on the environment and society. The relevance of intangible capital to improve the organisational sustainability performance as well as the expansion of the traditional dimensions of sustainability with the target of the six safeguard subjects: human health, social justice, ecosystem quality, financial stability, resource availability and man-made environment are integrated into a conceptual framework. This approach allows the development and implementation of strategies towards sustainable corporate development through a recommendation-based framework

    Structural activation of the transcriptional repressor EthR from Mycobacterium tuberculosis by single amino acid change mimicking natural and synthetic ligands

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    Ethionamide is an antituberculous drug for the treatment of multidrug-resistant Mycobacterium tuberculosis. This antibiotic requires activation by the monooxygenase EthA to exert its activity. Production of EthA is controlled by the transcriptional repressor EthR, a member of the TetR family. The sensitivity of M. tuberculosis to ethionamide can be artificially enhanced using synthetic ligands of EthR that allosterically inactivate its DNA-binding activity. Comparison of several structures of EthR co-crystallized with various ligands suggested that the structural reorganization of EthR resulting in its inactivation is controlled by a limited portion of the ligand-binding-pocket. In silico simulation predicted that mutation G106W may mimic ligands. X-ray crystallography of variant G106W indeed revealed a protein structurally similar to ligand-bound EthR. Surface plasmon resonance experiments established that this variant is unable to bind DNA, while thermal shift studies demonstrated that mutation G106W stabilizes EthR as strongly as ligands. Proton NMR of the methyl regions showed a lesser contribution of exchange broadening upon ligand binding, and the same quenched dynamics was observed in apo-variant G106W. Altogether, we here show that the area surrounding Gly106 constitutes the molecular switch involved in the conformational reorganization of EthR. These results also shed light on the mechanistic of ligand-induced allosterism controlling the DNA binding properties of TetR family repressors

    Evaluation of the HadGEM3-A simulations in view of detection and attribution of human influence on extreme events in Europe

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    A detailed analysis is carried out to assess the HadGEM3-A global atmospheric model skill in simulating extreme temperatures, precipitation and storm surges in Europe in the view of their attribution to human influence. The analysis is performed based on an ensemble of 15 atmospheric simulations forced with observed Sea Surface Temperature of the 54 year period 1960-2013. These simulations, together with dual simulations without human influence in the forcing, are intended to be used in weather and climate event attribution. The analysis investigates the main processes leading to extreme events, including atmospheric circulation patterns, their links with temperature extremes, land-atmosphere and troposphere-stratosphere interactions. It also compares observed and simulated variability, trends and generalized extreme value theory parameters for temperature and precipitation. One of the most striking findings is the ability of the model to capture North Atlantic atmospheric weather regimes as obtained from a cluster analysis of sea level pressure fields. The model also reproduces the main observed weather patterns responsible for temperature and precipitation extreme events. However, biases are found in many physical processes. Slightly excessive drying may be the cause of an overestimated summer interannual variability and too intense heat waves, especially in central/northern Europe. However, this does not seem to hinder proper simulation of summer temperature trends. Cold extremes appear well simulated, as well as the underlying blocking frequency and stratosphere-troposphere interactions. Extreme precipitation amounts are overestimated and too variable. The atmospheric conditions leading to storm surges were also examined in the Baltics region. There, simulated weather conditions appear not to be leading to strong enough storm surges, but winds were found in very good agreement with reanalyses. The performance in reproducing atmospheric weather patterns indicates that biases mainly originate from local and regional physical processes. This makes local bias adjustment meaningful for climate change attribution

    A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset

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    The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1), while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. The DOI for the data is https://doi.org/10.1016/10.5281/zenodo.167070

    D1.2 Handbook of multi-hazard, multi-risk definitions and concepts

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    This report is the first output of Work Package 1: Diagnosis of the MYRIAD-EU project: Handbook of Multi-hazard, Multi-Risk Definitions and Concepts. The aim of the task was to (i) acknowledge the differences and promote consistency in understanding across subsequent work packages in the MYRIAD-EU project, (ii) improve the accessibility of our work to a broad array of stakeholders and (iii) strengthen consensus across the hazard and risk community through a common understanding of multi-hazard, multi-risk terminology and concepts. The work encompassed a mixed-methods approach, including internal consultations and data-generating exercises; literature reviews; external stakeholder engagement; adopting and building on a rich existing body of established glossaries. 140 terms are included in the glossary, 102 related to multi-hazard, multi-risk, disaster risk management and an additional 38 due to their relevance to the project, acknowledging the need for a common understanding amongst an interdisciplinary project consortium. We also include extended definitions related to concepts particularly of relevance to this project deliverable, including ‘multi-hazard’, ‘hazard interrelationships’, ‘multi-risk’ and ‘direct and indirect loss and risk’. Underpinned by a literature review and internal consultation, we include a specific section on indicators, how these might be applied within a multi-hazard and multi-risk context, and how existing indicators could be adapted to consider multi-risk management. We emphasise that there are a number of established glossaries that the project (and risk community) should make use of to strengthen the impact of the work we do, noting in our literature review a tendency in papers and reports to define words afresh. We conclude the report with a selection of key observations, including terminology matters – for all aspects of disaster risk management, for example communication, data collection, measuring progress and reporting against Sendai Framework targets. At the same time, we discuss when is it helpful to include ‘multi-‘ as a prefix, questioning whether part of the paradigm shift needed to successfully address complex challenges facing an interconnected world is through inherently seeing vulnerability, exposure and disaster risk through the lens of multiple, interrelated hazards. We emphasise that there is likely to be an evolution of the terminology throughout the project lifetime as terms are emerge or shift as the project evolves. Finally, we propose a roadmap for developing and testing draft multi-risk indicators in MYRIAD-EU. The WP1 team would like to acknowledge all the contributions of the consortium on this task and the feedback from the External Advisory Board, in particular the chair of the board Virginia Murray, Head of Global Disaster Risk Reduction at the UK Health Security Agency, and the contribution of Jenty Kirsch-Wood, Head of Global Risk Management and Reporting at UNDRR, for her reflections on the findings of this work

    A submonthly database for detecting changes in vegetation-atmosphere coupling

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    Land-atmosphere coupling and changes in coupling regimes are important for making precise future climate predictions and understanding vegetation-climate feedbacks. Here we introduce the Vegetation-Atmosphere Coupling (VAC) index which identifies regions and times of concurrent strong anomalies in temperature and photosynthetic activity. The different classes of the index determine whether a location is currently in an energy-limited or water-limited regime, and its high temporal resolution allows to investigate how these regimes change over time at the regional scale. We show that the VAC index helps to distinguish different evaporative regimes. It can therefore provide indirect information about the local soil moisture state. We further demonstrate how the index can be used to understand processes leading to and occurring during extreme climate events, using the 2010 heat wave in Russia and the 2010 Amazon drought as examples.ISSN:0094-8276ISSN:1944-800
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