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Publications (5 of 5) Show all publications
Gutierrez, J. M., Maraun, D., Widmann, M., Huth, R., Hertig, E., Benestad, R., . . . Page, C. (2019). An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment. International Journal of Climatology, 39(9), 3750-3785
Open this publication in new window or tab >>An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment
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2019 (English)In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088, Vol. 39, no 9, p. 3750-3785Article in journal (Refereed) Published
National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-5243 (URN)10.1002/joc.5462 (DOI)000474001900006 ()
Available from: 2019-07-29 Created: 2019-07-29 Last updated: 2019-07-30Bibliographically approved
Bonaduce, A., Staneva, J., Behrens, A., Bidlot, J.-R. & Wilcke, R. (2019). Wave Climate Change in the North Sea and Baltic Sea. Journal of Marine Science and Engineering, 7(6), Article ID 166.
Open this publication in new window or tab >>Wave Climate Change in the North Sea and Baltic Sea
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2019 (English)In: Journal of Marine Science and Engineering, E-ISSN 2077-1312, Vol. 7, no 6, article id 166Article in journal (Refereed) Published
National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-5252 (URN)10.3390/jmse7060166 (DOI)000473807700004 ()
Available from: 2019-07-29 Created: 2019-07-29 Last updated: 2019-07-29Bibliographically approved
Pulatov, B., Jonsson, A. M., Wilcke, R., Linderson, M.-L., Hall, K. & Bärring, L. (2016). Evaluation of the phenological synchrony between potato crop and Colorado potato beetle under future climate in Europe. Agriculture, Ecosystems & Environment, 224, 39-49
Open this publication in new window or tab >>Evaluation of the phenological synchrony between potato crop and Colorado potato beetle under future climate in Europe
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2016 (English)In: Agriculture, Ecosystems & Environment, ISSN 0167-8809, E-ISSN 1873-2305, Vol. 224, p. 39-49Article in journal (Refereed) Published
National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-2156 (URN)10.1016/j.agee.2016.03.027 (DOI)000375809900005 ()
Available from: 2016-06-15 Created: 2016-06-15 Last updated: 2017-11-28Bibliographically approved
Wilcke, R. & Bärring, L. (2016). Selecting regional climate scenarios for impact modelling studies. Environmental Modelling & Software, 78, 191-201
Open this publication in new window or tab >>Selecting regional climate scenarios for impact modelling studies
2016 (English)In: Environmental Modelling & Software, ISSN 1364-8152, E-ISSN 1873-6726, Vol. 78, p. 191-201Article in journal (Refereed) Published
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.

National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-2034 (URN)10.1016/j.envsoft.2016.01.002 (DOI)000371377800015 ()
Available from: 2016-05-03 Created: 2016-05-02 Last updated: 2017-11-30Bibliographically approved
Maraun, D., Widmann, M., Gutierrez, J. M., Kotlarski, S., Chandler, R. E., Hertig, E., . . . Wilcke, R. (2015). VALUE: A framework to validate downscaling approaches for climate change studies. Earth's Future, 3(1), 1-14
Open this publication in new window or tab >>VALUE: A framework to validate downscaling approaches for climate change studies
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2015 (English)In: Earth's Future, ISSN 1384-5160, E-ISSN 2328-4277, Vol. 3, no 1, p. 1-14Article in journal (Refereed) Published
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.

National Category
Climate Research
Research subject
Climate
Identifiers
urn:nbn:se:smhi:diva-1967 (URN)10.1002/2014EF000259 (DOI)000358138100001 ()
Available from: 2016-04-26 Created: 2016-03-03 Last updated: 2017-11-30Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-8787-5090

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