Change search
Refine search result
1 - 5 of 5
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Bonaduce, Antonio
    et al.
    Staneva, Joanna
    Behrens, Arno
    Bidlot, Jean-Raymond
    Wilcke, Renate
    SMHI, Research Department, Climate research - Rossby Centre.
    Wave Climate Change in the North Sea and Baltic Sea2019In: Journal of Marine Science and Engineering, E-ISSN 2077-1312, Vol. 7, no 6, article id 166Article in journal (Refereed)
  • 2. Gutierrez, J. M.
    et al.
    Maraun, D.
    Widmann, M.
    Huth, R.
    Hertig, E.
    Benestad, R.
    Roessler, O.
    Wibig, J.
    Wilcke, Renate
    SMHI, Research Department, Climate research - Rossby Centre.
    Kotlarski, S.
    San Martin, D.
    Herrera, S.
    Bedia, J.
    Casanueva, A.
    Manzanas, R.
    Iturbide, M.
    Vrac, M.
    Dubrovsky, M.
    Ribalaygua, J.
    Portoles, J.
    Raty, O.
    Raisanen, J.
    Hingray, B.
    Raynaud, D.
    Casado, M. J.
    Ramos, P.
    Zerenner, T.
    Turco, M.
    Bosshard, Thomas
    SMHI, Research Department, Hydrology.
    Stepanek, P.
    Bartholy, J.
    Pongracz, R.
    Keller, D. E.
    Fischer, A. M.
    Cardoso, R. M.
    Soares, P. M. M.
    Czernecki, B.
    Page, C.
    An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment2019In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088, Vol. 39, no 9, p. 3750-3785Article in journal (Refereed)
  • 3. Maraun, Douglas
    et al.
    Widmann, Martin
    Gutierrez, Jose M.
    Kotlarski, Sven
    Chandler, Richard E.
    Hertig, Elke
    Wibig, Joanna
    Huth, Radan
    Wilcke, Renate
    SMHI, Research Department, Climate research - Rossby Centre.
    VALUE: A framework to validate downscaling approaches for climate change studies2015In: Earth's Future, ISSN 1384-5160, E-ISSN 2328-4277, Vol. 3, no 1, p. 1-14Article in journal (Refereed)
    Abstract [en]

    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.

  • 4. Pulatov, Bakhtiyor
    et al.
    Jonsson, Anna Maria
    Wilcke, Renate
    SMHI, Research Department, Climate research - Rossby Centre.
    Linderson, Maj-Lena
    Hall, Karin
    Bärring, Lars
    SMHI, Research Department, Climate research - Rossby Centre.
    Evaluation of the phenological synchrony between potato crop and Colorado potato beetle under future climate in Europe2016In: Agriculture, Ecosystems & Environment, ISSN 0167-8809, E-ISSN 1873-2305, Vol. 224, p. 39-49Article in journal (Refereed)
  • 5.
    Wilcke, Renate
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Bärring, Lars
    SMHI, Research Department, Climate research - Rossby Centre.
    Selecting regional climate scenarios for impact modelling studies2016In: Environmental Modelling & Software, ISSN 1364-8152, E-ISSN 1873-6726, Vol. 78, p. 191-201Article in journal (Refereed)
    Abstract [en]

    In climate change research ensembles of climate simulations are produced in an attempt to cover the uncertainty in future projections. Many climate change impact studies face difficulties using the full number of simulations available, and therefore often only subsets are used. Until now such subsets were chosen based on their representation of temperature change or by accessibility of the simulations. By using more specific information about the needs of the impact study as guidance for the clustering of simulations, the subset fits the purpose of climate change impact research more appropriately. Here, the sensitivity of such a procedure is explored, particularly with regard to the use of different climate variables, seasons, and regions in Europe. While temperature dominates the clustering, the resulting selection is influenced by all variables, leading to the conclusion that different subsets fit different impact studies best. (C) 2016 The Authors. Published by Elsevier Ltd.

1 - 5 of 5
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
v. 2.35.7
|