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  • 11
    Publication Date: 2015-02-17
    Description: The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean – regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present day climate. A global ocean – sea ice – marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e. ocean, atmosphere, terrestrial hydrology and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 12
    Publication Date: 2021-07-03
    Description: Regional climate predictions for the next decade are gaining importance, as this period falls within the planning horizon of politics, economy, and society. The potential predictability of climate indices or extremes at the regional scale is of particular interest. The German MiKlip project (“mid‐term climate forecast”) developed the first regional decadal prediction system for Europe at 0.44° resolution, based on the regional model COSMO‐CLM using global MPI‐ESM simulations as boundary conditions. We analyse the skill of this regional system focussing on extremes and user‐oriented variables. The considered quantities are related to temperature extremes, heavy precipitation, wind impacts, and the agronomy sector. Variables related to temperature (e.g., frost days, heat wave days) show high predictive skill (anomaly correlation up to 0.9) with very little dependence on lead‐time, and the skill patterns are spatially robust. The skill patterns for precipitation‐related variables (e.g., heavy precipitation days) and wind‐based indices (like storm days) are less skilful and more heterogeneous, particularly for the latter. Quantities related to the agronomy sector (e.g., growing degree days) show high predictive skill, comparable to temperature. Overall, we provide evidence that decadal predictive skill can be generally found at the regional scale also for extremes and user‐oriented variables, demonstrating how the utility of decadal predictions can be substantially enhanced. This is a very promising first step towards impact‐related modelling at the regional scale and the development of individual user‐oriented products for stakeholders.
    Description: The skill of the regional MiKlip decadal prediction system is analysed focussing on extremes and user‐oriented variables. Variables related to temperature extremes and the agronomy sector show high predictive skill with very little dependence on lead‐time. Skill patterns for precipitation‐related variables and wind‐based indices are less skilful and more heterogeneous, especially for the latter.
    Description: The study was mainly funded by the Bundesministerium für Bildung und Forschung (BMBF) under project FONA MiKlip‐II http://dx.doi.org/10.13039/501100002347
    Description: AXA Research Fund http://dx.doi.org/10.13039/501100001961
    Keywords: 551.6 ; climate services ; Europe ; extremes ; MiKlip ; regional decadal predictions ; user needs
    Type: article
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  • 13
    Publication Date: 2014-07-14
    Description: The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 14
    Publication Date: 2022-03-31
    Description: Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (a) preconditioned, (b) multivariate, (c) temporally compounding, and (d) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (a) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (b) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non‐stationary multivariate process. For instance, future mean sea‐level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (c) In Portugal, deep‐landslides are often caused by temporal clusters of moderate precipitation events. Finally, (d) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors.
    Description: Plain Language Summary: Many societal and environmental impacts from events such as droughts and storms arise from a combination of weather and climate factors referred to as a compound event. Considering the complex nature of these high‐impact events is crucial for an accurate assessment of climate‐related risk, for example to develop adaptation and emergency preparedness strategies. However, compound event research has emerged only recently, therefore our ability to analyze these events is still limited. In practice, studying compound events is a challenging task, which often requires interaction between experts across multiple disciplines. Recently, compound events were divided into four types to aid the framing of research on this topic, but guidelines on how to study these four types are missing. Here, we take a pragmatic approach and—focusing on case studies of different compound event types—illustrate how to address specific research questions that could be of interest to users. The results allow identifying recommendations for compound event analyses. Furthermore, through the case studies, we highlight the relevance that compounding effects have for the occurrence of landslides, flooding, vegetation impacts, and crop failures. The guidelines emerged from this work will assist the development of compound event analysis across disciplines and sectors.
    Description: Key Points: Using case studies representative of four main compound event types we show how compound event‐related research questions can be tackled. We present user‐friendly guidelines for compound event analysis applicable to different compound event types. We demonstrate that compound events cause vegetation impacts, coastal flooding, landslides, and continental‐scale crop yield failures.
    Description: European COST action DAMOCLES
    Description: NERC
    Description: Swiss National Science Foundation
    Description: Helmholtz Initiative and Networking Fund
    Description: Netherlands Organisation for Scientific Research (NWO)
    Description: Fundação para a Ciência e a Tecnologia
    Description: Scientific Employment Stimulus 2017
    Description: Italian Ministry of University and Research
    Description: European Union's Horizon 2020 research and innovation programme
    Description: AXA Research Fund for support
    Description: Portuguese Foundation for Science and Technology
    Keywords: ddc:551.6
    Language: English
    Type: doc-type:article
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  • 15
    Publication Date: 2021-10-27
    Description: Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.
    Keywords: 550 ; impact forecasting ; natural hazards ; early warning
    Language: English
    Type: map
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  • 16
    Publication Date: 2021-10-12
    Description: The seasonal cycle of rainfall over the Greater Horn of Africa (GHA) is dominated by the latitudinal migration and activity of the tropical rain belt (TRB). The TRB exhibits high interannual variability in the GHA and the reasons for the recent dry period in the Long Rains (March–May) are poorly understood. In addition, few studies have addressed the rainfall fluctuations during the Msimu Rains (Dec.–Mar.) in the southern GHA region. Interannual variations of the seasonal cycle of the TRB between 1981 and 2018 were analysed using two statistical indices. The Rainfall Cluster Index (RCI) describes the seasonal cycle as a succession of six characteristic rainfall patterns, while the Seasonal Location Index (SLI) captures the latitudinal location of the TRB. The SLI and RCI depict the full seasonal cycle of the TRB supporting interpretations of the interannual variations and trends. The Msimu Rains are dominated by two clusters with opposite rainfall characteristics between the Congo Basin and Tanzania. The associated anomalies in moisture flux and divergence indicate variations in the location of the TRB originating from an interplay between low-level air flows from the Atlantic and Indian Oceans and tropical and subtropical teleconnections. The peak period of the Long Rains shows a complex composition of five clusters, which is tightly connected to intraseasonal and interannual variability of latitudinal locations of the TRB. A persistent location of the TRB near the equator, evidenced in a frequent occurrence of a cluster related to an anomalously weak Walker circulation, is associated with wet conditions over East Africa. Dry Long Rains are associated with strong and frequent latitudinal variations of the TRB position with a late onset and intermittent rainfall. These results offer new opportunities to understand recent variability and trends in the GHA region.
    Keywords: 551.6 ; Greater Horn of Africa ; seasonal cycle of rainfall ; ropical rain belt ; interannual variability
    Language: English
    Type: map
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  • 17
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    COPERNICUS GESELLSCHAFT MBH
    In:  EPIC3Climate of the Past, COPERNICUS GESELLSCHAFT MBH, 17(6), pp. 2559-2576, ISSN: 1814-9324
    Publication Date: 2022-02-15
    Description: During the Last Glacial Maximum (LGM), a very cold and dry period around 26.5–19 kyr BP, permafrost was widespread across Europe. In this work, we explore the possible benefit of using regional climate model data to improve the permafrost representation in France, decipher how the atmospheric circulation affects the permafrost boundaries in the models, and test the role of ground thermal contraction cracking in wedge development during the LGM. With these aims, criteria for possible thermal contraction cracking of the ground are applied to climate model data for the first time. Our results show that the permafrost extent and ground cracking regions deviate from proxy evidence when the simulated large-scale circulation in both global and regional climate models favours prevailing westerly winds. A colder and, with regard to proxy data, more realistic version of the LGM climate is achieved given more frequent easterly winds conditions. Given the appropriate forcing, an added value of the regional climate model simulation can be achieved in representing permafrost and ground thermal contraction cracking. Furthermore, the model data provide evidence that thermal contraction cracking occurred in Europe during the LGM in a wide latitudinal band south of the probable permafrost border, in agreement with field data analysis. This enables the reconsideration of the role of sand-wedge casts to identify past permafrost regions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 18
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    Wiley
    In:  Annals of the New York Academy of Sciences, 1436 (1). pp. 54-69.
    Publication Date: 2020-01-02
    Description: Regional climate modeling bridges the gap between the coarse resolution of current global climate models and the regional-to-local scales, where the impacts of climate change are of primary interest. Here, we present a review of the added value of the regional climate modeling approach within the scope of paleoclimate research and discuss the current major challenges and perspectives. Two time periods serve as an example: the Holocene, including the Last Millennium, and the Last Glacial Maximum. Reviewing the existing literature reveals the benefits of regional paleo climate modeling, particularly over areas with complex terrain. However, this depends largely on the variable of interest, as the added value of regional modeling arises from a more realistic representation of physical processes and climate feedbacks compared to global climate models, and this affects different climate variables in various ways. In particular, hydrological processes have been shown to be better represented in regional models, and they can deliver more realistic meteorological data to drive ice sheet and glacier modeling. Thus, regional climate models provide a clear benefit to answer fundamental paleoclimate research questions and may be key to advance a meaningful joint interpretation of climate model and proxy data.
    Type: Article , PeerReviewed
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  • 19
    Publication Date: 2020-04-28
    Type: Article , PeerReviewed
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  • 20
    Publication Date: 2020-04-28
    Type: Article , PeerReviewed
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