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  • CITATION GEO-LEO  (3)
  • circulation patterns  (3)
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  • 1
    Publication Date: 2024-01-24
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Reliable prediction of heavy precipitation events causing floods in a world of changing climate is crucial for the development of appropriate adaption strategies. Many attempts to provide such predictions have already been conducted but there is still much potential for improvement left. This is particularly true for statistical downscaling of heavy precipitation due to changes present in the corresponding atmospheric drivers. In this study, a circulation pattern (CP) conditional downscaling to the station level is proposed which considers occurring frequency changes of CPs. Following a strict circulation‐to‐environment approach we use atmospheric predictors to derive CPs. Subsequently, precipitation observations are used to derive CP conditional cumulative distribution functions (CDFs) of daily precipitation. Raw precipitation time series are sampled from these CDFs. Bias correction is applied to the sampled time series with quantile mapping (QM) and parametric transfer functions (PTFs) as methods being tested. The added value of this CP conditional downscaling approach is evaluated against the corresponding common non‐CP conditional approach. The performance evaluation is conducted by using Kling–Gupta Efficiency (KGE), root mean squared error (RMSE), and mean absolute error (MAE) metrics. In both cases the applied bias correction is identical. Potential added value can therefore only be attributed to the CP conditioning. It can be shown that the proposed CP conditional downscaling approach is capable of yielding more reliable and accurate downscaled daily precipitation time series in comparison to a non‐CP conditional approach. This can be seen in particular for the extreme parts of the distribution. Above the 95th percentile, an average performance gain of +0.24 and a maximum gain of +0.6 in terms of KGE is observed. These findings support the assumption of conserving and utilizing atmospheric information through CPs can be beneficial for more reliable statistical precipitation downscaling. Due to the availability of these atmospheric predictors in climate model output, the presented method is potentially suitable for downscaling precipitation projections.〈/p〉
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview
    Description: https://cdc.dwd.de/portal/
    Keywords: ddc:551.5 ; bias correction ; circulation patterns ; ERA5 ; extreme events ; heavy precipitation ; simulated annealing ; statistical downscaling
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2024-01-30
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Projected changes in summer precipitation deficits partly depend on alterations in synoptic circulations. Here, the automated Jenkinson–Collison classification is used to assess the ability of 21 global climate models (GCMs) to capture the frequency of recurring circulation types (CTs) and their implications for European daily precipitation amounts in summer (JJA). The ability of the GCMs to reproduce the observed present‐day climate features is evaluated first. Most GCMs capture the observed links between the mean CTs directional flow characteristics and the occurrence of dry days and related dry months. The most robust relationships are found for anticyclonic and easterly CTs which are generally associated with higher‐than‐average occurrences of dry conditions. Future changes in summer CTs' frequencies are estimated in the high‐emission SSP5‐8.5 scenario for the sake of a high signal‐to‐noise ratio. Our results reveal consistent changes, mainly in the zonal CTs. A robust decrease in frequency of the westerlies and an increase in the frequency of easterly CTs favour more continental, dry and warm air masses over central Europe. These dynamical changes are shown to enhance the projected summer drying over central and southern Europe.〈/p〉
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Summer large‐scale circulations are derived over Europe using an automated classification. Spatial characteristics of the patterns and their influence on dry days are investigated. Future changes are explored based on global climate models. The predicted drier summers in Europe are found to be influenced by consistent changes in west‐easterly circulations.〈boxed-text position="anchor" content-type="graphic" id="joc8033-blkfxd-0001" xml:lang="en"〉 〈graphic position="anchor" id="jats-graphic-1" xlink:href="urn:x-wiley:08998418:media:joc8033:joc8033-toc-0001"〉 〈/graphic〉 〈/boxed-text〉〈/p〉
    Description: EU International Training Network (ITN) Climate Advanced Forecasting of sub‐seasonal Extremes (CAFE)
    Description: H2020 Marie Skłodowska‐Curie Actions
    Description: https://github.com/PedroLormendez/jcclass
    Keywords: ddc:551.6 ; circulation patterns ; climate change ; precipitation ; weather extremes
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2024-05-22
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉As projected by multiple climate models, short‐duration heavy precipitation events (SDHPEs) are expected to intensify particularly quickly under the changing climate posing substantial risk to natural and human systems. Yet over the years, SDHPEs have received less scientific attention than long‐duration heavy precipitation events (LDHPEs), mainly due to the limitations of measurement systems. Our aim is to provide insight into spatial and temporal variability of SDHPEs detected by the radar network of the 〈italic toggle="no"〉Deutscher Wetterdienst〈/italic〉 (DWD) in Germany from 2001 to 2020 as well as to explore their links to circulation patterns (CPs). The study is based on the Catalogue of Radar‐based heavy Rainfall Events (CatRaRE) generated using reprocessed gauge‐adjusted data of the DWD radar network as well as a new numerical method for classifying CPs over Central Europe called “〈italic toggle="no"〉Großwetterlagen〈/italic〉 for Reanalyses” (GWL‐REA). The results have demonstrated that SDHPEs, which are defined based on either locally valid precipitation values with a return period of 5 years (CatRaRE T5) or absolute precipitation values equal to DWD Warning Level 3 (CatRaRE W3), are common phenomena occurring most frequently in the afternoon hours of the summer season. They constitute up to 90% of all heavy precipitation events included in the catalogues covering relatively small areas—the median area of SDHPEs ranges from 22 km〈sup〉2〈/sup〉 (CatRaRE T5) to 24 km〈sup〉2〈/sup〉 (CatRaRE W3), while the median area of LDHPEs ranges from 175 km〈sup〉2〈/sup〉 (CatRaRE W3) to 184 km〈sup〉2〈/sup〉 (CatRaRE T5). As compared to LDHPEs, SDHPEs are generated by a wider spectrum of circulation conditions, including not only cyclonic but also anticyclonic CPs. In the warm season, the anticyclonic CPs, often accompanied by air mass advection from the south, can induce high thermal instability leading to the development of relatively small, isolated convective cells, which often cannot be captured by rain gauge stations.〈/p〉
    Description: Federal Ministry for Digital and Transport (BMDV)
    Description: https://www.dwd.de/DE/leistungen/catrare/catrare.html
    Keywords: ddc:551.6 ; CatRaRE ; circulation patterns ; GWL‐REA ; heavy precipitation events ; long‐duration precipitation ; radar data ; short‐duration precipitation
    Language: English
    Type: doc-type:article
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