A framework for testing the ability of models to project climate change and its impacts

Refsgaard, Jens Christian; Madsen, Henrik; Andréassian, Vazken; Arnbjerg‐Nielsen, Karsten; Davidson, Thomas A.; Drews, Martin; Hamilton, David P.; Jeppesen, Erik; Kjellström, Erik; Olesen, Jørgen E.; Sonnenborg, Torben O.; Trolle, Dennis; Willems, Patrick; Christensen, Jens Hesselbjerg

doi:10.1007/s10584-013-0990-2

Cited by 111 publications

(76 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hatterman et al 2016, Merz et al 2011. Refsgaard et al (2013) and Coron et al (2011) suggest how this could be done for catchment-scale impact modelling but these methods are difficult to implement in continental-or globalscale models. In Greuell et al (2015), we proposed one index (interannual variability) that gives one indication of how well existing models react to median changes in climate, but acknowledge that this should be supplemented with other analysis and benchmarks.…”

Section: Uncertainties and Limitationsmentioning

confidence: 99%

Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level

et al. 2017

View full text Add to dashboard Cite

Impacts of climate change at 1.5, 2 and 3°C mean global warming above preindustrial level are investigated and compared for runoff, discharge and snowpack in Europe. Ensembles of climate projections representing each of the warming levels were assembled to describe the hydro-meteorological climate at 1.5, 2 and 3°C. These ensembles were then used to force an ensemble of five hydrological models and changes to hydrological indicators were calculated. It is seen that there are clear changes in local impacts on evapotranspiration, mean, low and high runoff and snow water equivalent between a 1.5, 2 and 3°C degree warmer world. In a warmer world, the hydrological impacts of climate change are more intense and spatially more extensive. Robust increases in runoff affect the Scandinavian mountains at 1.5°C, but at 3°C extend over most of Norway, Sweden and northern Poland. At 3°C, Norway is affected by robust changes in all indicators. Decreases in mean annual runoff are seen only in Portugal at 1.5°C warming, but at 3°C warming, decreases to runoff are seen around the entire Iberian coast, the Balkan Coast and parts of the French coast. In affected parts of Europe, there is a distinct increase in the changes to mean, low and high runoff at 2°C compared to 1.5°C, strengthening the case for mitigation to lower levels of global warming. Between 2 and 3°C, the changes in low and high runoff levels continue to increase, but the Climatic Change (2017) 143: 13-26 DOI 10.100713-26 DOI 10. /s10584-017-1971 Electronic supplementary material The online version of this article (doi:10.1007/s10584-017-1971-7) contains supplementary material, which is available to authorized users.

show abstract

Section: Uncertainties and Limitationsmentioning

confidence: 99%

Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Annual precipitation from 1960 to 2015 was observed from the 11 rainfall stations in Luoyugou. Potential evapotranspiration was calculated with day-to-day minimum and maximum air temperatures, relative humidity, hours of sunshine, and wind speed for the period of 1960-2015 from 11 national weather stations, using the Penman-Monteith equation recommended by FAO [15].…”

Section: Databasesmentioning

confidence: 99%

Effects of Climate Change and Human Activity on Runoff in a Typical Loess Gullied-Hilly Region Watershed

Lv¹,

Zuo²,

Xiao³

et al. 2018

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

“…That they do not reproduce it completely is because they consist 10 of a finite number of possibly biased and dependent models that typically have to be chosen based on availability rather than on statistical considerations (Knutti et al, 2013;Tebaldi and Knutti, 2007). To mitigate this problem, some researchers assign weights to individual models, but there is an ongoing debate about this: some researchers are making a general case for the benefits of weighting (Ylhäisi et al, 2015) or its drawbacks (Aghakouchak et al, 2013), some are detailing when it may make sense on the basis of model performance (Refsgaard et al, 2014;Rodwell and Palmer, 2007) or genealogy (Masson and Knutti, 15 2011), but all approaches are disputed. The relative importance of model response increases with projection lead time and is particularly significant for extreme summer precipitation (Bosshard et al, 2013).…”

Section: Model Responsementioning

confidence: 99%

Climate uncertainty in flood protection planning

Dittes

Špačková

Schoppa

et al. 2017

Preprint

View full text Add to dashboard Cite

Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure life time, which is typically many decades long. Flood protection requirements should account for multiple future 10 uncertain factors: socio-economic, e.g. whether the population and with it the damage potential grows or falls; technological, e.g. possible advancements in flood protection; and climatic, e.g. whether extreme discharge will become more frequent or not. We focus here on the planning implications of the uncertainty in extreme discharge. We account for the sequential nature of the decision process, in which the adequacy of the protection is regularly revised in the future based on the discharges that have been observed by that point and that reduce uncertainty. For planning purposes, we categorize uncertainties as either 15 'visible', if they can be quantified from available catchment data, or 'hidden', if they cannot be quantified from catchment data and must be estimated, e.g. from literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g. through projections, historic record) is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-20 alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection.

show abstract

A framework for testing the ability of models to project climate change and its impacts

Cited by 111 publications

References 40 publications

Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level

Impacts of climate change on European hydrology at 1.5, 2 and 3 degrees mean global warming above preindustrial level

Effects of Climate Change and Human Activity on Runoff in a Typical Loess Gullied-Hilly Region Watershed

Climate uncertainty in flood protection planning

Contact Info

Product

Resources

About