The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling
Abstract
There is now a large published literature on the strengths and weaknesses of downscaling methods for different climatic variables, in different regions and seasons. However, little attention is given to the choice of downscaling method when examining the impacts of climate change on hydrological systems. This review paper assesses the current downscaling literature, examining new developments in the downscaling field specifically for hydrological impacts. Sections focus on the downscaling concept; new methods; comparative methodological studies; the modelling of extremes; and the application to hydrological impacts. Consideration is then given to new developments in climate scenario construction which may offer the most potential for advancement within the ‘downscaling for hydrological impacts’ community, such as probabilistic modelling, pattern scaling and downscaling of multiple variables and suggests ways that they can be merged with downscaling techniques in a probabilistic climate change scenario framework to assess the uncertainties associated with future projections. Within hydrological impact studies there is still little consideration given to applied research; how the results can be best used to enable stakeholders and managers to make informed, robust decisions on adaptation and mitigation strategies in the face of many uncertainties about the future. It is suggested that there is a need for a move away from comparison studies into the provision of decision‐making tools for planning and management that are robust to future uncertainties; with examination and understanding of uncertainties within the modelling system. Copyright © 2007 Royal Meteorological Society
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Cites
Quantification of modelling uncertainties in a large ensemble of climate change simulations.
Murphy, J. M., Sexton, D. M. H., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., & Stainforth, D. A. (2004) · Nature · doi:10.1038/nature02771 · Cited by 1,655
Probability of regional climate change based on the Reliability Ensemble Averaging (REA) method
Giorgi, F., & Mearns, L. O. (2003) · Geophysical Research Letters · doi:10.1029/2003gl017130 · Cited by 258
Probabilistic climate change projections using neural networks
Knutti, R., Stocker, T. F., Joos, F., & Plattner, G.-K. (2003) · Climate Dynamics · doi:10.1007/s00382-003-0345-1 · Cited by 197
Cited by
Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios
Kling, H., Fuchs, M., & Paulin, M. (2012) · Journal of Hydrology · doi:10.1016/j.jhydrol.2012.01.011 · Cited by 1,676
Using weather data and climate model output in economic analyses of climate change
Auffhammer, M., Hsiang, S. M., Schlenker, W., & Sobel, A. (2013) · Review of Environmental Economics and Policy · doi:10.1093/reep/ret016 · Cited by 662
Seasonal Drought Prediction: Advances, Challenges, and Future Prospects
Hao, Z., Singh, V. P., & Xia, Y. (2018) · Reviews of Geophysics · doi:10.1002/2016rg000549 · Cited by 607
Teutschbein, C., & Seibert, J. (2010) · Geography Compass · doi:10.1111/j.1749-8198.2010.00357.x · Cited by 357
Shaw, A., Sheppard, S., Burch, S., Flanders, D., Wiek, A., Carmichael, J., Robinson, J., & Cohen, S. (2009) · Global Environmental Change · doi:10.1016/j.gloenvcha.2009.04.002 · Cited by 313
Metadata
- Authors
- Fowler, H. J., Blenkinsop, S., & Tebaldi, C.
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2007-09-14
- Volume
- 27
- Issue
- 12
- Pages
- 1547-1578
- ISSN
- 0899-8418 (ISSN-L)
- 1097-0088
- OpenAlex
- W2093141926
- Cited by
- 2,158
- References
- 3
- FWCI
- 45.18
- Type
- journal article
- Language
- en
- Open access
- closed
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