General circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. What is less clear is the extent to which local (subgrid) scale meteorological processes will be affected. So-called 'downscaling' techniques have subsequently emerged as a means of bridging the gap between what climate modellers are currently able to provide and what impact assessors require. This article reviews the present generation of downscaling tools under four main headings: regression methods; weather pattern (circulation)-based approaches; stochastic weather generators; and limited-area climate models. The penultimate section summarizes the results of an international experiment to intercompare several precipitation models used for downscaling. It shows that circulation-based downscaling methods perform well in simulating present observed and model-generated daily precipitation characteristics, but are able to capture only part of the daily precipitation variability changes associated with model-derived changes in climate. The final section examines a number of ongoing challenges to the future development of climate downscaling. I The rationale for downscalingEven if global climate models in the future are run at high resolution there will remain the need to 'downscale' the results from such models to individual sites or localities for impact studies. Downscaling methodologies are still under development and more work needs to be done in intercomparing these methodologies and quantifying the accuracy of such methods (DOE, 1996: 34).The present generation of general circulation models (GCMs) of the climate system are restricted in their usefulness for many subgrid scale applications by their coarse spatial Source: Modified after Hostetler (1994) and temporal resolution (Wigley et al., 1990;Carter et al., 1994). For example, hydrological models are frequently concerned with small, subcatchment (even hillslope) scale processes, occurring on spatial scales much smaller than those resolved in GCMs (see Figure 1). GCMs deal most proficiently with fluid dynamics at the continental scale and parameterize regional and smaller-scale processes. These scale-related sensitivities and mismatch problems are further exacerbated because they usually involve the most uncertain components of climate models, water vapour and cloud feedback effects (Rind et al., 1992). As Hostetler (1994) has observed, the greatest errors in the parameterizations of both GCMs and hydrological models occur on the scale(s) at which climate and terrestrial impact models interface. These mismatch problems, which affect both the temporal and spatial dimensions, have important implications for the credence of impact studies derived by the output of models of climate change, especially as research into potential human-induced modifications to hydrological and ecological cycles is assuming increasing significance. Downloaded from 532 change. A major focus of the BAHC (Biological Aspects of the Hydrol...
[1] A probabilistic framework is presented for combining information from an ensemble of four general circulation models (GCMs), two greenhouse gas emission scenarios, two statistical downscaling techniques, two hydrological model structures, and two sets of hydrological model parameters. GCMs were weighted according to an index of reliability for downscaled effective rainfall, a key determinant of low flows in the River Thames. Hydrological model structures were weighted by performance at reproducing annual low-flow series. Weights were also assigned to sets of water resource model (CATCHMOD) parameters using the Nash-Sutcliffe efficiency criterion. Emission scenarios and downscaling methods were unweighted. A Monte Carlo approach was then used to explore components of uncertainty affecting projections for the River Thames by the 2080s. The resulting cumulative distribution functions (CDFs) of low flows were most sensitive to uncertainty in the climate change scenarios and downscaling of different GCMs. Uncertainties due to the hydrological model parameters and emission scenario increase with time but were less important. Abrupt changes in low-flow CDFs were attributed to uncertainties in statistically downscaled summer rainfall. This was linked to different behavior of atmospheric moisture among the chosen GCMs.
It is now accepted that some human-induced climate change is unavoidable. Potential impacts on water supply have received much attention, but relatively little is known about the concomitant changes in water quality. Projected changes in air temperature and rainfall could affect river flows and, hence, the mobility and dilution of contaminants. Increased water temperatures will affect chemical reaction kinetics and, combined with deteriorations in quality, freshwater ecological status. With increased flows there will be changes in stream power and, hence, sediment loads with the potential to alter the morphology of rivers and the transfer of sediments to lakes, thereby impacting freshwater habitats in both lake and stream systems. This paper reviews such impacts through the lens of UK surface water quality. Widely accepted climate change scenarios suggest more frequent droughts in summer, as well as flash-flooding, leading to uncontrolled discharges from urban areas to receiving water courses and estuaries. Invasion by alien species is highly likely, as is migration of species within the UK adapting to changing temperatures and flow regimes. Lower flows, reduced velocities and, hence, higher water residence times in rivers and lakes will enhance the potential for toxic algal blooms and reduce dissolved oxygen levels. Upland streams could experience increased dissolved organic carbon and colour levels, requiring action at water treatment plants to prevent toxic by-products entering public water supplies. Storms that terminate drought periods will flush nutrients from urban and rural areas or generate acid pulses in acidified upland catchments. Policy responses to climate change, such as the growth of bio-fuels or emission controls, will further impact freshwater quality.Key words climate change; water quality; rivers; catchments; lakes; estuaries; ecology; hydrochemistry Une revue des impacts potentiels du changement climatique sur la qualité des eaux de surface Résumé Il est maintenant admis qu'un certain changement climatique d'origine anthropique est inévitable. Les impacts potentiels sur l'alimentation en eau ont fait l'objet de nombreuses attentions, mais peu de connaissances sont disponibles sur les changements associés en termes de qualité de l'eau. Les changements prévus en termes de température de l'air et de précipitations pourraient affecter les écoulements des rivières et par conséquent la mobilité et la dilution des substances polluantes. Une augmentation des températures de l'eau affectera la cinétique des réactions chimiques et, par combinaison avec les dégradations de la qualité, l'état écologique des hydrosystèmes. Une augmentation des écoulements aura pour conséquences des changements dans la puissance des cours d'eau et donc aussi des charges sédimentaires qui pourront altérer la morphologie des rivières et le transfert de sédiments vers les lacs, ce qui aura des impacts sur les habitats hydrobiologiques dans les systèmes lacustres et fluviatiles. Cet article fait une revue de tels imp...
Global temperature targets, such as the widely accepted 2°C limit, may fail to 12 communicate the urgency of reducing CO 2 emissions. Translation of CO 2 emissions 13 into regional-and impact-related climate targets could be more powerful because 14 they resonate better with national interests. We illustrate this approach using 15 regional changes in extreme temperatures and precipitation. These scale robustly 16 with global temperature across scenarios, and thus with cumulative CO 2 emissions. 17 This is particularly relevant for changes in regional extreme temperatures on land, 18 which are much greater than changes in the associated global mean. 19 20 The IPCC 5 th Assessment Report included a figure in the Summary for Policymakers 21 (SPM) of the Working Group 1 (WG1) that linked global mean temperature changes 22 (ΔT glob) to total CO 2 emissions from 1870 onwards 1 (Fig. 1). This figure is compelling 23 because it shows a clear linear relationship between cumulative CO 2 emissions and a 24 measure of the global climate response. The obvious consequences are that every ton of 25 CO 2 contributes about the same amount of global-scale warming, no matter when it is 26 emitted, that any target for the stabilization of ΔT glob implies a finite CO 2 budget or quota 27 that can be emitted, and that global net emissions at some point need to be zero 2,3,4,5,6. 28 29 This simple relationship between CO 2 emissions and changes in ΔT glob (Fig. 1) has helped 30 overcome one communication barrier for the public in relating greenhouse gas emissions 31 with the climate system response. Yet, another obstacle remains the actual appreciation of 32 associated climate impacts, namely the translation of changes in global mean temperature 33 to regional-scale consequences for society and the environment. In this Perspective, we 34 demonstrate the feasibility of-as well as make the case for-quantitatively relating 35 global-scale cumulative CO 2 emissions to regional climate targets. We illustrate this 36 approach by scaling changes in hot and cold extreme temperatures and heavy 37 precipitation events with changes in the global mean temperature. 38 39 Global vs regional climate targets 40 Our experience shows that the implications of projected global mean temperature 41 changes tend to be underestimated at regional (and country) level, because these are 42 much smaller than the expected changes in regional temperature mean and extremes over 43 most land areas 7,8,9,10. The limitations of focusing on global mean temperature as a 44 measure of climate change has, for instance, been evidenced by the public debate about 45 the recent "hiatus". This has fixated attention on changes in ΔT glob instead of the 46 discernible worldwide impacts of the continued increases in radiative forcing 1 ,11,12,13,14. 47
Simulated daily precipitation, temperature, and runoff time series were compared in three mountainous basins in the United States: (1) the Animas River basin in Colorado, (2) the East Fork of the Carson River basin in Nevada and California, and (3) the Cle Elum River basin in Washington State. Two methods of climate scenario generation were compared: delta change and statistical downscaling. The delta change method uses differences between simulated current and future climate conditions from the Hadley Centre for Climate Prediction and Research (HadCM2) General Circulation Model (GCM) added to observed time series of climate variables. A statistical downscaling (SDS) model was developed for each basin using station data and output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEPINCAR) reanalysis regridded to the scale of HadCM2. The SDS model was then used to simulate local climate variables using HadCM2 output for current and future conditions. Surface climate variables from each scenario were used in a precipitation‐runoff model. Results from this study show that, in the basins tested, a precipitation‐runoff model can simulate realistic runoff series for current conditions using statistically down‐scaled NCEP output. But, use of downscaled HadCM2 output for current or future climate assessments are questionable because the GCM does not produce accurate estimates of the surface variables needed for runoff in these regions. Given the uncertainties in the GCMs ability to simulate current conditions based on either the delta change or downscaling approaches, future climate assessments based on either of these approaches must be treated with caution.
This article reviews the historical development of statistical weather models, from simple analyses of runs of consecutive rainy and dry days at single sites, through to multisite models of daily precipitation. Weather generators have been used extensively in water engineering design and in agricultural, ecosystem and hydrological impact studies as a means of in-filling missing data or for producing indefinitely long synthetic weather series from finite station records. We begin by describing the statistical properties of the rainfall occurrence and amount processes which are necessary precursors to the simulation of other (dependent) meteorological variables. The relationship between these daily weather models and lower-frequency variations in climate statistics is considered next, noting that conventional weather generator techniques often fail to capture wholly interannual variability. Possible solutions to this deficiency - such as the use of mixtures of slowly and rapidly varying conditioning variables - are discussed. Common applications of weather generators are then described. These include the modelling of climate-sensitive systems, the simulation of missing weather data and statistical downscaling of regional climate change scenarios. Finally, we conclude by considering ongoing advances in the simulation of spatially correlated weather series at multiple sites, the downscaling of interannual climate variability and the scope for using nonparametric techniques to synthesize weather series.
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