study and Peel et al. (2014) include that: delta perturbations instead of downscaled GCM climatechange scenarios are used; stochastic modelling is used to derive replicates of runoff series directly, rather than the indirect approach by Peel et al. (2014) in which the rainfall and temperature were modelled stochastically and later used to force a rainfall–runoff model, thus removing the added layer of uncertainty caused by the multi-ensemble rain- fall–runoff modelling; and reservoirimpacts analysis is not limited to the yield/storage alone but includes consideration of perfor- mance indices. As far as the authors are aware, this is the first attempt at characterising the variability of reservoir performance indices within the context of climatechangeimpactsassessment. To demonstrate the applicability of the methodology, it was applied to the Pong reservoir located on the Beas River in Himachal Pradesh, India (see Fig. 1 ). The Pong reservoir principally provides irrigation water although, prior to its diversion to irrigation, its released water first passes through turbines for generating electric- ity ( Jain et al., 2007 ). Consequently, the current study is focusing on the irrigation function of the reservoir. The reservoir inflow is highly influenced by both the Monsoon rainfall and the melting glacier and seasonal snow from the Himalayas; consequently, its ability to satisfactorily perform its functions is susceptible to pos- sible climate-change disturbances in these climatic attributes. For a system that is inextricably linked to the socio-economic well- being of its region ( Jain et al., 2007 ), any significant deterioration in performance or ability to meet the irrigation water demand will have far reaching consequences. This is why it is important to carry out a systematic assessment of the performance of the reservoirduringclimatechange and to use the outcome to potentially inform the development of appropriate solutions.
Abstract. While quantitative assessment of the climatechange impact on hydrology at the basin scale is quite ad- dressed in the literature, extension of quantitative analysis to impact on the ecological, economic and social sphere is still limited, although well recognized as a key issue to sup- port water resource planning and promote public participa- tion. In this paper we propose a framework for assessing climatechange impact on water-related activities at the basin scale. The specific features of our approach are that: (i) the impact quantification is based on a set of performance indi- cators defined together with the stakeholders, thus explicitly taking into account the water-users preferences; (ii) the man- agement policies are obtained by optimal control techniques, linking stakeholder expectations and decision-making; (iii) the multi-objective nature of the management problem is fully preserved by simulating a set of Pareto-optimal man- agement policies, which allows for evaluating not only vari- ations in the indicator values but also tradeoffs among con- flicting objectives. The framework is demonstrated by appli- cation to a real world case study, Lake Como basin (Italy). We show that the most conflicting water-related activities within the basin (i.e. hydropower production and agriculture) are likely to be negatively impacted by climatechange. We discuss the robustness of the estimated impacts to the climate natural variability and the approximations in modeling the physical system and the socio-economic system, and perform an uncertainty analysis of several sources of uncertainty. We demonstrate that the contribution of natural climate uncer- tainty is rather remarkable and that, among different mod- elling uncertainty sources, the one from climate modeling is very significant.
Although these downscaling techniques can match the statistics and probability distribution of historical precipitation, they do not eliminate all errors (Maraun 2016; Eden and Widmann 2014; Grillakis et al. 2013). For instance, quantile mapping automatically modifies the number of wet days in order to match the probability distribution function (PDF) (Maraun 2016). Further, when sampling noise is extremely high, nonparametric quantile mapping basically employs random corrections which generates very noisy solutions (Maraun 2016). van Pelt et al. (2009) study examines two bias-correction methods. They conclude that although the first method amends the average, numerous consecutive precipitation days were incorrectly removed. The second method adjusted the coefficient of variance and mean, but the average underperformed while the temporal precipitation pattern improved. This leads to the hypothesis of this paper that bias-correction may alter the precipitation transition states of climate cycles embedded in the GCMs, which are hydrologically detrimental. For example, monthly and sometimes annual scale climate states that drive precipitation variability are important for water supply planning. At these temporal scales, persistence of certain states, such as multiple months or years of less-than-average precipitation during the wet season can have severe consequences on water management. Multiple consecutive months with below average precipitation could affect streamflow and the availability of surfacewater (Clark et al. 2014). Additionally, multiple wet months would increase the availability of surfacewater, which could be captured and stored for future use. It is important to simulate the transition between these climate states to create a more robust model that can facilitate informed decisions. Although annual budgets are important and was considered, this research focuses on winter and summer months.
Adaptation and innovative management will certainly be a useful and necessary response to climatic changes. Several factors, however, suggest that relying solely, or even principally, on adaptation may prove a dangerous policy. First, the impacts of climatechange on the water sector will be very complicated and at least partly unpredictable. Second, many impacts may be non-linear and chaotic, characterized by surprises and unusual events. Third, climatic changes will be imposed on water systems that will be increasingly stressed by other factors, including population growth, competition for financial resources from other sectors, and disputes over water allocations and priorities. Finally, some adaptive strategies may help mitigate some adverse consequences of climatechange while simultaneously worsening others. There is a rapidly growing literature about the impacts of climatechange on water systems, reservoir operations, water quality, hydroelectric generation, navigation, and other water-management concerns. At the same time, this literature has barely scratched the surface of the potential range of impacts, and far more research is needed. One consistent finding is that water-supply systems are sensitive to changes in inflows and demands. Nemec and Schaake (1982), in one of the earliest studies on climateimpacts, showed that large changes in the reliability of water yields from reservoir systems result from small changes in reservoir inflows. This finding has now been reproduced in many studies from many different regions (Cole et al., 1991; McMahon et al., 1989; Mimikou et al., 1991; Nash and Gleick 1993). In the Mesohora reservoir in Greece, a 10 percent decrease in precipitation leads to a tripling of the risk that the hydroelectric facility there will be unable to produce its design power (Mimikou et al., 1991). In a comprehensive analysis of the Colorado River Basin, the highly integrated system of linked reservoirs was shown to be very sensitive to both the physical characteristics of the system and to the way it is managed and operated.
and following with less sensitive parameters later. Parameter adjustment process continues until satisfactory agreement is obtained between the predicted and the observed values. The model has been calibrated and verified for the hydrological year of 1979 and 1995 from the Upper Assiniboine River Basin, Saskatchewan and Manitoba of Canada, and in 1996 and 1997 from the Red River Basin, shared by Canada and the USA (Li and Simonovic 2002 ). The upper Assiniboine river flows to north-eastern direction with a relative small catchment area, so it was lumped into one catchment. Since the catchment area of the Red River Basin flows from south to north with a very large catchment area, a division into three sub-catchments was made, i.e. the upper reach, middle reach and lower reach, and simulated and measured river discharge series at Grand Forks, Emerson and Ste Agathe were compared. The results show that the simulated streamflow reflects the variation in air temperature and precipitation as well as the moisture interaction between the surface soil, subsoil and the groundwater storages. Sensitivity analysis indicates that parameters related to the surface soil storage and the temperature are not sensitive to the selected-parameter variations with ±10%, while the statistical comparison using coefficient of efficiency, coefficient of determination and square of the residual mass curve coefficient reveals that the simulation error is unsystematic and random, and the model can well reproduce the observed flood starting time, peak and the flood duration (Li and Simonovic 2002 ). The model was also successfully applied to simulate the soil moisture storages of different layers and the overland flow in Alberta watersheds by Elshorbagy et al. ( 2005 ), and to assess the sensitivity of complex flood protection system to future climatechange in the Red River Basin by Simonovic and Li ( 2004 ). The main output includes simulated discharge series at the reservoir which is fed to calculate reservoir storage and release. The reservoirwater dynamics model was quantitatively calibrated and tested by Ahmad and Simonovic ( 2000 ) on the basis of the operation rules to control water outflow from the reservoir.
Food security and water scarcity have become two major concerns for future human’s sustainable development, particularly in the context of climatechange. Here we present a comprehensive assessment of climatechangeimpacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climatechange are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security.
new tools such as the reduction or elimination of subsidies, sophisticated pricing mechanisms, and smart markets provide incentives to use less water, produce more with existing resources, and reallocate water among different users. Water marketing is viewed by many as offering great potential to increase the efficiency of both water use and allocation (NRC 1992, Western Water Policy Review Advisory Commission 1998). As conditions change, markets can help resources move from lower- to higher-value uses. The characteristics of water resources and the institutions established to control them have inhibited large-scale water marketing to date. Water remains underpriced and market transfers are constrained by institutional and legal issues. Efficient markets require that buyers and sellers bear the full costs and benefits of transfers. However, when water is transferred, third parties are likely to be affected. Where such externalities are ignored, the market transfers not only water, but also other benefits that water provides from a non-consenting third party to the parties to the transfer. A challenge for developing more effective water markets is to develop institutions that can expeditiously and efficiently take third-party impacts into account (Loh and Gomez 1996, Gomez and Steding 1998, Dellapenna 1999). As a result, despite their potential advantages, prices and markets have been slow to develop as tools for adapting to changing supply and demand conditions. The potential gains are breaking down many of the barriers to transfers in the western United States. Temporary transfers are becoming increasingly common for responding to short-term supply and demand fluctuations. Water banks can provide a clearinghouse to facilitate the pooling of water rights for rental. The temporary nature of such a transfer blunts a principal third-party concern that a transfer will permanently undermine the economic and social viability of the water-exporting area. California’s emergency Drought Water Banks in the early 1990s helped mitigate the impacts of a prolonged drought by facilitating water transfers among willing buyers and sellers. Dellapenna (1999) and others have noted, however, that the California Water Bank was not a true market, but rather a state-managed reallocation effort that moved water from small users to large users at a price set by the state, not a functioning market. More recent efforts to develop more functioning markets on a smaller scale have had some success (California Department of Water Resources, http://rubicon.water.ca.gov/b16098/ v2txt/ch6e.html). Idaho and Texas have established permanent water banks and other states are considering establishing them as well.
The impacts of climatechange on water resources are potentially large and could result from increases in temperature and from changes in mean annual values and the variability of precipitation. However, our ability to predict climatechangeimpacts on water resources and plan for adaptation and amelioration is hindered by the lack of good predictions of future climate at regional scales and a lack of fundamental understanding of many of the effects of climatevariability on the physical, chemical, and biological characteristics of water resources. Several areas of future research are critical for improving our understanding of and our ability to predict effects of climatechange on water resources. These include the development of better regional climate models, studies of relationships between climatevariability and physiological and ecosystem processes, initiation of integrated assessment of impacts, and analyses that define viable response options for future changes in climate. Many water bodies are highly managed and changes in water resources management (infrastructure, operations, and administration) can potentially ameliorate some of the impacts of climatechange. Adaptation will be necessary in many cases, however, and it is only through an improved understanding of climate and its effects on water resources that we can begin to plan the adaptation strategies that will be needed.
deaths and injuries annually in the United States. Climatechange may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation. Key words: climatechange, extreme weather events, flooding, global warming, natural disasters, storms. — Environ Health Perspect 109(suppl 2):191–198 (2001).
The SWAT simulation results representing five agricultural scenarios, eight AOGCMs, three representative concentra- tion pathways (RCP2.6, RCP4.5 and RCP8.5) and three 20- year temporal blocks (early, mid-, and late 21st centuries) were systematically aggregated to analyze the combined im- pacts of agricultural scenario and climatechange on water, total suspended solids, total nitrogen and total phosphorous yields at the Raccoon River watershed outlet. Moreover, the effects of climatechange on corn and switchgrass yields were assessed by analyzing the results of the AC and AS scenarios. In general, the results indicated the need for develop- ing alternative biofuel cropping systems to counteract future problems that could develop from relying on intensification of corn production in Corn Belt region watersheds to miti- gate potential future water quality problems. The results of this study were consistent with the findings of Wilson and Weng (2011), where future climatechange would exert a larger impact on the concentration of pollutants than the po- tential impact of land use (Fig. 4a–f). The results also showed that significant reduction in water pollution could be accom- plished by expanded planting of switchgrass in the RRW as depicted by the PS and AS scenarios. Even though it pro- vides the best results in alleviating water quality problems in the future, the promising future water quality benefits sug- gested by the AS scenario results are unrealistic due to the need for production of corn or other crops. Planting more switchgrass could reduce row crop (especially corn) produc- tion in the region significantly. However, if biofuels from switchgrass become commercially viable, cellulosic biofuel production could reduce the pressure on the need for corn and make planting more switchgrass feasible. There were, however, scenarios where results indicated reductions in wa- ter quality in PS relative to the BL historical simulation. This shows that planting switchgrass alone may not be sufficient to improve water quality for heavily tile agricultural water- sheds like the RRW. Therefore, our results indicate that sub- stantially improving water quality will require a combination of working land practices (such as conservation tillage and cover crops) and land retirement/perennial plantings (such as planting grasses such as switchgrass). This will in turn neces- sitate substantive conservation efforts, higher than historical levels. Unfortunately, the latest farm bill has both reduced overall conservation funding by almost EUR 4 billion over a 10 year span and reduced the proportion of funding going to land retirement (Stubbs, 2014). Therefore, increased conser- vation will only occur via novel public–private partnerships or through regulatory drivers.
Abstract. Projected hydrological variability is important for future resource and hazard management of water sup- plies because changes in hydrological variability can cause more disasters than changes in the mean state. However, cli- mate change scenarios downscaled from Earth System Mod- els (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate cli- mate change scenarios via three steps: (i) spatial downscal- ing of ESMs using a transfer function method, (ii) tempo- ral downscaling of ESMs using a single-site weather gener- ator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipi- tation and temperature change scenarios for 2011–2040 were generated from five ESMs under four representative concen- tration pathways to project changes in streamflow variabil- ity using the Soil and WaterAssessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable corre- lation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly stream- flow with a model efficiency coefficient of 0.78. It was pro- jected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 ◦ C; the vari-
The Water Footprint was first introduced by Hoestra in order to evaluate how the human activities related to the utilization of water can become more sustainable. Serving the aim of raising awareness and improving sustainable water management, the WF is proved as a very useful indicator (Kolokytha, 2014). It refers to all forms of freshwater use (consumption and pollution) that contribute to the production of goods and services consumed by the users of a certain geographical region or a river basin (Hoekstra and Chapagain, 2008). The three types of water namely blue, green and grey water are analysed separately in order to evaluate water quantity (rain, ground and surfacewater) and water quality (grey water). The analysis of the WF in a river basin provides valuable information to facilitate the efficient allocation of water resources in different economic and environmental requirements as it provides new data in order to tackle with water scarcity and water pollution problems.
SWAT model (Sediment and WaterAssessment Tool) was used to evaluate the im- pacts of climatechange on water resources in Al-Adhaim Basin which is located in north east of Iraq. Al-Adhaim River is the main source of fresh water to Kirkuk City, one of the largest cities of Iraq. Recent studies have shown that blue and green waters of the basin have been manifesting increasing variability contributing to more severe droughts and floods apparently due to climatechange. In order to gain greater ap- preciation of the impacts of climatechange on water resources in the study area in near and distant future, SWAT (Soil and WaterAssessment Tool) has been used. The model is first tested for its suitability in capturing the basin characteristics, and then, forecasts from six GCMs with about half-a-century lead time to 2046-2064 and one-century lead time to 2080-2100 are incorporated to evaluate the impacts of cli- mate change on water resources under three emission scenarios: A2, A1B and B1. The results showed worsening water resources regime into the future.
Hoosiers’ furnaces use far more energy per year than their air conditioners or other space-cooling appliances. Because of that, minimum winter temperature is the most important factor influencing residential energy demand. Predicted changes in annual and seasonal temperatures and precipitation are readily available. However, there are other climate factors that also affect energy demand that are not readily available. For instance, higher wind speeds in spring and fall increase heating demands, but projections of these wind speeds are limited. Humidity, storm frequency, and storm intensity also influence residential energy demand, but these variables are not commonly available from future climate projections. Excluding changes in humidity (which is expected to increase throughout this century) from future residential demand projections is likely to cause an underestimation of demand for cooling.
38 The length of the growing season and its reliability (Jaetzold and Kutsch, 1982) determines the suitability of crops and cultivars that can be cultivated in a given area and is an important indicator of yield potentials. The lengths of the growing season in the CRV exhibits a high inter annual variability with slight declining trend. The onset date of the growing season shows a trend towards late starting. With a high correlation between the starting date of the growing season and length of the growing season, delay of the onset implies shortened growing period leading to low crop productivity. Earlier studies also provided evidence that uncertainty of the growing season is one of the main challenges for rainfed crop production. World Bank (2006), for instance, reported that the late start of the Kiremt in 1997 caused a reduction in average yield of cereals by 10% across Ethiopia. Camberlin and Okoola (2003) observed a 25-30% maize yield reduction in Kenya due to a 20 day delay of the main rainfall season. The CRV is further characterized by intermittent dry spells with higher probabilities of occurrence during the growing season. Most of the crops cultivated in the CRV are most likely to be exposed to moisture stress. For instance, at Ziway, there is a chance of 26% of getting dry spells of longer than 7 days at the early growth stage of a crop and the probability is higher (92%) during the late development stage of the crop. Earlier studies by Segele and Lamb (2005) and Araya and Stroosnijder (2011) also indicate that dry spells of about 10 days length is one of the major causes of crop failure in rainfed farming systems of Ethiopia. The latter authors indicate that 20% of crop failure in drought prone parts of Ethiopia is due to dry spells during the growing season. In general, the Belg has higher probability of dry spells than the Kiremt. This may be because Belg rainfall is influenced much more by cyclonic activity than the Kiremt period and negative anomalies in sea surface temperature (SST) are strongly associated with rainfall deficiency in the Belg season (Seleshi and Camberlin, 2006). The water requirement satisfaction index calculated for 90-day and 120-day cycled maize cultivars indicates that the effective rainfall available during the growing season is not sufficient for maximum production of the crops in most of the seasons. Crops, particularly long cycled varieties experience water stress during the growing season and farmers need to shift to short cycled crops as long as rainfall is the only source of water for crop production. The analysis provides an indication for the necessity of improved farm management practices to support production of short cycled varieties.
High fecal indicator bacteria (FIB) in surfacewater leads to water quality advisories at recreational beaches, adversely impacting their recreational and economic value (Austin et al. 2007). In the United States and Canada, beach water quality advisories are issued based on concentrations of FIB (E. coli and enterococci at freshwater and marine beaches, respectively) in water samples taken between ankle- to chest-depth surfacewater (Enns et al. 2012, Health Canada 2012, United States Environmental Protection Agency 2012). Over the last decade it has been widely shown that FIB concentrations are often elevated in foreshore beach sand and pore water (herein referred to as the foreshore reservoir) on a bulk volumetric basis relative to adjacent surfacewater (e.g. Kinzelman et al. 2004, Russell et al. 2012, Staley et al. 2015, Whitman and Nevers 2003). Particularly at non-point source beaches, the foreshore reservoir can be an important source of FIB to nearshore surface waters thereby triggering a beach water quality advisory (Bai and Lung 2005, Edge and Hill 2007, Vogel et al. 2016, Yamahara et al. 2007). This reservoir may also represent a potential direct health risk to beachgoers (Heaney et al. 2009, Solo-Gabriele et al. 2015). While the influence of environmental factors (e.g., wave conditions, rainfall, temperature, UV, and currents) on surfacewater FIB concentrations has been well studied in order to improve prediction of beach water quality exceedances (e.g. Enns et al. 2012, Nevers and Whitman 2005, Olyphant and Whitman 2004, Vogel et al. 2016, Whitman et al. 2004), there is limited understanding of how FIB concentrations (sand and pore water) in the foreshore reservoir vary at long- (seasonal) and short-term (daily) time scales. Further, the environmental factors that affect this variability including the relationship between FIB concentrations in the surfacewater and foreshore reservoir are unclear (Russell et al. 2012, Whitman and Nevers 2003). Understanding short-term (daily) and long-term (seasonal) variability in foreshore sand and pore water FIB concentrations is needed to better understand environmental factors affecting FIB accumulation in the reservoir, when and if the reservoir will affect the surfacewater quality, and to improve management strategies for reducing microbial contamination at beaches.
Future river flows have been estimated using the hydrological model, Simplified Hydrolog (SIMHYD), which is integrated with data from three different general climate models and emission scenarios. In this study, two different representative concentration pathway (RCP) emission scenarios RCP 4.5 and RCP 8.5 were selected to obtain downscaled future precipitation and potential evapotranspiration data from government agencies for the period of 2016 to 2100. Data from the two emission scenarios show an anticipated warmer and drier climate for the Murrumbidgee catchment. Runoff in the Murrumbidgee catchment is controlled by various dams and weirs, which yields positive results in runoff even when monthly rainfall trend was negative. The overall runoff simulations indicated that impact of climatechange is short and intense.
However, the general trend is that in the past five years farmers in the area suffered a great loss of crop yield due to poor rains and excessive temperature resulting from climatevariability which in turn affected crop production in the area. The gradual decrease in maize production in different years of production could have been caused by the fact that the areas had been receiving low rainfall levels to climatevariability. This finding clearly justifies the former scenario in Kiwege village in 2008/09 whereby indigenous settlers in the area were given food relief by the government of Tanzania due to prolonged drought spell. As a result of the 2009 drought which affected more than 1.5 million people in Tanzania, more than 120,000 million tonnes of food aid was required in the country (Munishi et al.,2010). Although other factors may have contributed towards decrease in yield, there is, however, sufficient evidence revealing how climatechange had impacted on crop yield loss as indicated by Munishi et al. (2010) who demonstrated that rainfall characteristics in some parts of Tanzania show a gradual decrease in the length of the growing season, decreasing trend of number of rainy days during the growing season, and decreasing seasonal rainfall amount in areas that are most vulnerable hence poor yield.
Climate scenarios were constructed (Osborn et al. 2014) by pattern-scaling output from 21 of the climate models in the CMIP3 set (Meehl et al. 2007a: Supplementary Table 2) to match the changes in global mean temperature projected under the four SRES emissions scenarios A1b, A2, B1 and B2. These global temperature changes were estimated using the MAGICC4.2 simple climate model with parameters appropriate to each climate model (Meehl et al. 2007b: Supplementary Fig. 1a). Pattern-scaling was used rather than simply constructing climate scenarios directly from climate model output partly to better separate out the effects of underlying climatechange and internal climatic variability, and partly to allow scenarios to be constructed for all combinations of climate model and emissions scenario. Rescaled changes in mean monthly climate variables (and year to year variability in monthly precipitation) were applied to the CRU TS3.0 0.5×0.5 o 1961-1990 climatology (Harris et al. 2014) using the delta method to create perturbed 30-year time series representing conditions around 2020, 2050 and 2080 (Osborn et al. 2014). The terrestrial ecosystem and soil carbon impact models require transient climate scenarios, and these were produced by repeating the CRU 1961-1990 time series and rescaling to construct time series from 1991 to 2100 using gradually increasing global mean temperatures (Osborn et al. 2014). Pattern-scaling makes assumptions about the relation- ship between rate of forcing and the spatial pattern of change, which have been demonstrated to be broadly appropriate for the averaged climate indicators used here (e.g. Tebaldi and Arblaster 2014), but which do constitute caveats to the quantitative interpretation of results.