GLORIA

GEOMAR Library Ocean Research Information Access

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Rekonstruktion des Europäischen Klimas für die Instrumentelle Periode mit Hilfe von Datenassimilation durch Upscaling und Nudging (DATUN) : Deklim Schlussbericht ; Laufzeit des Vorhabens: 01.01.2002 - 31.12.2004 (2005)
    [Geesthacht] : Inst. f. Küstenforschung, GKSS
    Details Availability
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: Online-Ressource (35 S., 3,33 MB) , Ill., graph. Darst.
    URL: https://edocs.tib.eu/files/e01fb06/511922221.pdf
    URL: https://doi.org/10.2314/GBV:511922221
    URL: https://edocs.tib.eu/files/e01fb06/511922221l.pdf
    DOI: 10.2314/GBV:511922221
    Language: English
    Note: Förderkennzeichen BMBF 01LD0044. - Literaturverz , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Auch als gedr. Ausg. vorh , Systemvoraussetzungen: Acrobat reader. , Text engl.
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    GEOMAR CATALOGUE
    Link to Library Catalog
    get availability status
  • 2
    Electronic Resource
    Electronic Resource
    Atmospheric science Early peak in Antarctic oscillation index (2004)
    [s.l.] : Nature Publishing Group
    Nature 432 (2004), S. 290-291 
    Details
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] The principal extratropical atmospheric circulation mode in the Southern Hemisphere, the Antarctic oscillation (or Southern Hemisphere annular mode), represents fluctuations in the strength of the circumpolar vortex and has shown a trend towards a positive index in austral summer in recent ...
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1038/432290b
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 3
    facet.materialart.
    Unknown
    Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes (2014)
    AMS (American Meteorological Society)
    In:  Journal of Climate, 27 (18). pp. 6940-6959.
    Details
    Publication Date: 2020-08-04
    Description: Precipitation is highly variable in space and time; hence, rain gauge time series generally exhibit additional random small-scale variability compared to area averages. Therefore, differences between daily precipitation statistics simulated by climate models and gauge observations are generally not only caused by model biases, but also by the corresponding scale gap. Classical bias correction methods, in general, cannot bridge this gap; they do not account for small-scale random variability and may produce artifacts. Here, stochastic model output statistics is proposed as a bias correction framework to explicitly account for random small-scale variability. Daily precipitation simulated by a regional climate model (RCM) is employed to predict the probability distribution of local precipitation. The pairwise correspondence between predictor and predictand required for calibration is ensured by driving the RCM with perfect boundary conditions. Wet day probabilities are described by a logistic regression, and precipitation intensities are described by a mixture model consisting of a gamma distribution for moderate precipitation and a generalized Pareto distribution for extremes. The dependence of the model parameters on simulated precipitation is modeled by a vector generalized linear model. The proposed model effectively corrects systematic biases and correctly represents local-scale random variability for most gauges. Additionally, a simplified model is considered that disregards the separate tail model. This computationally efficient model proves to be a feasible alternative for precipitation up to moderately extreme intensities. The approach sets a new framework for bias correction that combines the advantages of weather generators and RCMs.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1175/JCLI-D-13-00604.1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
    facet.materialart.
    Unknown
    VALUE - A Framework to Validate Downscaling Approaches for Climate Change Studies (2015)
    Wiley
    In:  Earth's Future, 3 (1). pp. 1-14.
    Details
    Publication Date: 2019-05-24
    Description: VALUE is an open European network to validate and compare downscaling methods for climate change research. VALUE aims to foster collaboration and knowledge exchange between climatologists, impact modellers, statisticians, and stakeholders to establish an interdisciplinary downscaling community. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. In this paper, we present the key ingredients of this framework. VALUE's main approach to validation is user- focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur: what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Do methods fail in representing regional climate change? How is the overall representation of regional climate, including errors inherited from global climate models? The framework will be the basis for a comprehensive community-open downscaling intercomparison study, but is intended also to provide general guidance for other validation studies.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
    DOI: 10.1002/2014EF000259
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
    facet.materialart.
    Unknown
    Comparison of GCM- and RCM-simulated precipitation following stochastic postprocessing (2014)
    AGU (American Geophysical Union) | Wiley
    In:  Journal of Geophysical Research: Atmospheres, 119 (19). 11,040-11,053.
    Details
    Publication Date: 2018-02-27
    Description: In order to assess to what extent regional climate models (RCMs) yield better representations of climatic states than general circulation models (GCMs), the output of each is usually directly compared with observations. RCM output is often bias corrected, and in some cases correction methods can also be applied to GCMs. This leads to the question of whether bias-corrected RCMs perform better than bias-corrected GCMs. Here the first results from such a comparison are presented, followed by discussion of the value added by RCMs in this setup. Stochastic postprocessing, based on Model Output Statistics (MOS), is used to estimate daily precipitation at 465 stations across the United Kingdom between 1961 and 2000 using simulated precipitation from two RCMs (RACMO2 and CCLM) and, for the first time, a GCM (ECHAM5) as predictors. The large-scale weather states in each simulation are forced toward observations. The MOS method uses logistic regression to model precipitation occurrence and a Gamma distribution for the wet day distribution, and is cross validated based on Brier and quantile skill scores. A major outcome of the study is that the corrected GCM-simulated precipitation yields consistently higher validation scores than the corrected RCM-simulated precipitation. This seems to suggest that, in a setup with postprocessing, there is no clear added value by RCMs with respect to downscaling individual weather states. However, due to the different ways of controlling the atmospheric circulation in the RCM and the GCM simulations, such a strong conclusion cannot be drawn. Yet the study demonstrates how challenging it is to demonstrate the value added by RCMs in this setup.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1002/2014JD021732
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
    facet.materialart.
    Unknown
    A Combined Statistical Bias Correction and Stochastic Downscaling Method for Precipitation (2017)
    Copernicus Publications (EGU)
    In:  Hydrology and Earth System Sciences, 21 . pp. 1693-1719.
    Details
    Publication Date: 2020-02-06
    Description: Much of our knowledge about future changes in precipitation relies on global (GCM) and/or regional climate models (RCM) that have resolutions which are much coarser than typical spatial scales of precipitation, particularly extremes. The major problems with these projections are both climate model biases and the gap between gridbox and point scale. Wong et al. developed a model to jointly bias correct and downscale precipitation at daily scales. This approach, however, relied on pairwise correspondence between predictor and predictand for calibration, and thus, on nudged simulations which are rarely available. Here we present an extension of this approach that separates the downscaling from the bias correction and in principle is applicable to free running GCMs/RCMs. In a first step, we bias correct RCM-simulated precipitation against gridded observations at the same scale using a parametric quantile mapping approach. To correct the whole distribution including extreme tails we apply a mixture distribution of a gamma distribution for the precipitation mass and a generalized Pareto distribution for the extreme tail. In a second step, we bridge the scale gap: we predict local variance employing a vector generalized linear gamma model (VGLM gamma) with the bias corrected time series as predictor. The VGLM gamma model is calibrated between gridded and point scale (station) observations. For evaluation we adopt the perfect predictor experimental setup of VALUE. Precipitation is in most cases improved by (parts of) our method across different European climates. The method generally performs better in summer than in winter and in winter best in the Mediterranean region with a mild winter climate and worst for continental winter climate in mid & eastern Europe or Scandinavia. A strength of this two-step method is that the best combination of bias correction and downscaling methods can be selected. This implies that the concept can be extended to a wide range of method combinations.
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.5194/hess-21-1693-2017
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 7
    facet.materialart.
    Unknown
    Diving into the past – A paleo data-model comparison workshop on the Late Glacial and Holocene (2019)
    AMS (American Meteorological Society)
    In:  Bulletin of the American Meteorological Society, 100 (1). ES1-ES4.
    Details
    Publication Date: 2022-01-31
    Type: Article , PeerReviewed
    Format: text
    DOI: 10.1175/BAMS-D-18-0169.1
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 8
    facet.materialart.
    Unknown
    Bacterial methane oxidation in landfill cover layers - a coupled FE multiphase description (2013)
    Wiley-Blackwell
    Details
    Publication Date: 2013-11-30
    Description: Landfill gas is composed of methane (CH 4 ) and (CO 2 ) at a ratio of about (60% – 40%), whereby the impact of methane on the greenhouse effect is about 25 times higher than that of carbon dioxide. Bacterial methane oxidation, taking place in the landfill cover layer, helps to reduce the climate active emissions from landfill sites. This contribution presents a theoretical and numerical approach to model the coupled processes of bacterial methane oxidation. An isothermal biphasic model based on the Theory of Porous Media (TPM) and Mixture Theory is introduced as well as the coupled finite element (FE) calculation concept. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)
    Electronic ISSN: 1617-7061
    Topics: Mathematics , Physics , Technology
    Published by Wiley-Blackwell
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    PAPER CURRENT
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...