High resolution climate simulation:Methods for improving and customising climate information with focus on outreach and uncertainty assessmen
For adaptation to climate change in Greenland in terms of specific planning, assessment and risk analysis, the full range of climate estimates as indicated by the uncertainty interval is necessary. In this research the expected climate change and associated uncertainties in Greenland are estimated....
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| Format: | Book |
| Language: | English |
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Niels Bohr Institute, Faculty of Science, University of Copenhagen
2018
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| Online Access: | https://curis.ku.dk/portal/da/publications/high-resolution-climate-simulation(eaf736ac-2301-46a6-9b5e-6c4ba25821af).html https://soeg.kb.dk/permalink/45KBDK_KGL/1pioq0f/alma99122448522505763 |
| Summary: | For adaptation to climate change in Greenland in terms of specific planning, assessment and risk analysis, the full range of climate estimates as indicated by the uncertainty interval is necessary. In this research the expected climate change and associated uncertainties in Greenland are estimated. The assessment of future climate change is based on the high-resolution regional climate model (RCM), HIRHAM5, emission scenarios used by IPCC and on European regional climate studies (EURO-CORDEX). Projections of future climate change based on an ensemble of climate models are more robust than estimates based on a single model. Here a statistical method to better frame results based on HIRHAM5 is utilized to assess uncertainties of projected climate change results. Climate variability and change are expected to increase towards year 2100 in terms of higher temperatures, more winter precipitation, more frequent and more extreme weather events. Using HIRHAM5-simulations over Greenland in combination with an ensemble of coarser RCM simulations from a different geographical setting; EURO-CORDEX, we investigate to what extent the uncertainty of projected high-resolution climate change can be evaluated from corresponding temperature spread in a wider set of global climate models (GCMs), CMIP5. Our proposed uncertainty assessment method establishes a foundation on which high-resolution and relative costly regional climate projections in general can be assessed. Also when using only a single RCM without the presence of analogous downscaling experiments with other RCMs and GCMs, the uncertainty assessment is relying on already existing information from CMIP5. Thus, the uncertainty of a wide range of climate indices that scale with temperature can be evaluated and quantified through the inter-model temperature spread within CMIP5. Furthermore we explore possibilities of combining long time series of observed temperature and precipitation at Greenlandic coastal stations with proxy measurements of temperature and solid ... |
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