Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling

Abstract

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.

Impacts of climate change on nutrient losses from the Pike River watershed of southern Québec

“…This allows assessing uncertainties rising from climate modelling by providing a range in which future climate impacts are expected to occur. Furthermore different sources of uncertainties are known in climate modelling and affect impact modelling outcome (Fowler et al 2007;de Elia and Cote 2009;Frigon et al 2010). Using a range of projections as described above allows us to include and get some understanding of the effect of the different sources of uncertainties on the results.…”

Climate Projections of Future Extreme Events in Malaysia

“…Factors of change are used specifically to perturb the statistically derived time series to generate statistical expressions of future hourly time series (Wilby et al, 2004;Fowler et al, 2007;Fatichi et al, 2011). The climate statistical properties for a given station are calculated from the observations as well as from the GCMs.…”

“…Despite numerous uncertainties in the different GCMs (Chu et al, 2010), these outputs provide hydrologists with priceless information. However, the coarse resolution of GCMs may lead to mismatch between the model's variables against observational variables for many climate change impact studies (Fowler et al, 2007;Hessami et al, 2008;Hashmi et al, 2009;Chu et al, 2010;Hashmi et al, 2010;Fatichi et al, 2011). The mismatch issues tend to produce inaccurate simulations of current regional climate for sub-grid scales (Chu et al, 2010;Guo et al, 2011).…”

“…Basically, statistical downscaling approaches could be categorized into three main generic classes, namely regression models, weather generators and weather typing methods. Regression models could assess the relation between the climatic variables at local scale (e.g., rainfall) and a set of large-scale atmospheric variables (Fowler et al, 2007). On the other hand, weather generators are employed to reproduce time series of climatic variables such as rainfall, atmospheric humidity and wind speed.…”

Changes in runoff time series in Thuringia, Germany – Mann-Kendall trend test and extreme value analysis

“…Bavarian Adaptation Strategy in 2009) level. Before taking the step of impact-modeling -using regional climate projections to drive hydrological models (Fowler et al, 2007;Maraun et al, 2010) -a first approach in assessing possible changes in runoff is to analyze measured runoff time series (e.g. Mudelsee et al, 2006;Kundzewicz et al, 2005).…”