A method for incorporating climate variability in climate change impact assessments: Sensitivity of river flows in the Eden catchment to precipitation scenarios

Interest in the impacts of climate change is ever increasing. This is particularly true of the water sector where understanding potential changes in the occurrence of both floods and droughts is important for strategic planning. Climate variability has been shown to have a significant impact on UK climate and accounting for this in future climate change projections is essential to fully anticipate potential future impacts. In this paper a new resampling methodology is developed which includes the variability of both baseline and future precipitation. The resampling methodology is applied to 13 CMIP3 climate models for the 2080s, resulting in an ensemble of monthly precipitation change factors. The change factors are applied to the Eden catchment in eastern Scotland with analysis undertaken for the sensitivity of future river flows to the changes in precipitation. Climate variability is shown to influence the magnitude and direction of change of both precipitation and in turn river flow, which are not apparent without the use of the resampling methodology. The transformation of precipitation changes to river flow changes display a degree of non-linearity due to the catchment’s role in buffering the response. The resampling methodology developed in this paper provides a new technique for creating climate change scenarios which incorporate the important issue of climate variability.     

The impact of climate change on the river rhine: A scenario study

This paper concerns the impact of human-induced global climate change on the River Rhine discharge. For this purpose a model for climate assessment, named ESCAPE, is coupled to a water balance model, named RHINEFLOW. From climate scenarios, changes in regional annual water availability and seasonal discharge in the River Rhine Basin are estimated. The climate scenarios are based on greenhouse gases emissions scenarios. An assessment is made for best guess seasonal discharge changes and for changes in frequencies of low and high discharges in the downstream reaches of the river. In addition, a quantitative estimation of the uncertainties associated with this guess is arrived at.The results show that the extent and range of uncertainty is large with respect to the best guess changes. The uncertainty range is 2–3 times larger for the Business-as-Usual than for the Accelerated Policies scenarios. This large range stems from the doubtful precipitation simulations from the present General Circulation Models. This scenario study showed the precipitation scenarios to be the key-elements within the present range of reliable climate change scenarios.For the River Rhine best guess changes for annual water availability are small according to both scenarios. The river changes from a present combined snow-melt-rain fed river to an almost entirely rain fed river. The difference between present-day large average discharge in winter and the small average discharge in autumn should increase for all scenarios. This trend is largest in the Alpine part of the basin. Here, winter discharges should increase even for scenarios forecasting annual precipitation decreases. Summer discharge should decrease. Best guess scenarios should lead to increased frequencies of both low and high flow events in the downstream (Dutch) part of the river. The results indicate changes could be larger than presently assumed in worst case scenarios used by the Dutch water management authorities.     

Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 1: baseline climate

Assessing future climate and its potential implications on river flows is a key challenge facing water resource planners. Sound, scientifically-based advice to decision makers also needs to incorporate information on the uncertainty in the results. Moreover, existing bias in the reproduction of the ‘current’ (or baseline) river flow regime is likely to transfer to the simulations of flow in future time horizons, and it is thus critical to undertake baseline flow assessment while undertaking future impacts studies. This paper investigates the three main sources of uncertainty surrounding climate change impact studies on river flows: uncertainty in GCMs, in downscaling techniques and in hydrological modelling. The study looked at four British catchments’ flow series simulated by a lumped conceptual rainfall–runoff model with observed and GCM-derived rainfall series representative of the baseline time horizon (1961–1990). A block-resample technique was used to assess climate variability, either from observed records (natural variability) or reproduced by GCMs. Variations in mean monthly flows due to hydrological model uncertainty from different model structures or model parameters were also evaluated. Three GCMs (HadCM3, CCGCM2, and CSIRO-mk2) and two downscaling techniques (SDSM and HadRM3) were considered. Results showed that for all four catchments, GCM uncertainty is generally larger than downscaling uncertainty, and both are consistently greater than uncertainty from hydrological modelling or natural variability. No GCM or downscaling technique was found to be significantly better or to have a systematic bias smaller than the others. This highlights the need to consider more than one GCM and downscaling technique in impact studies, and to assess the bias they introduce when modelling river flows.     

Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 2: future climate

The first part of this paper demonstrated the existence of bias in GCM-derived precipitation series, downscaled using either a statistical technique (here the Statistical Downscaling Model) or dynamical method (here high resolution Regional Climate Model HadRM3) propagating to river flow estimated by a lumped hydrological model. This paper uses the same models and methods for a future time horizon (2080s) and analyses how significant these projected changes are compared to baseline natural variability in four British catchments. The UKCIP02 scenarios, which are widely used in the UK for climate change impact, are also considered. Results show that GCMs are the largest source of uncertainty in future flows. Uncertainties from downscaling techniques and emission scenarios are of similar magnitude, and generally smaller than GCM uncertainty. For catchments where hydrological modelling uncertainty is smaller than GCM variability for baseline flow, this uncertainty can be ignored for future projections, but might be significant otherwise. Predicted changes are not always significant compared to baseline variability, less than 50% of projections suggesting a significant change in monthly flow. Insignificant changes could occur due to climate variability alone and thus cannot be attributed to climate change, but are often ignored in climate change studies and could lead to misleading conclusions. Existing systematic bias in reproducing current climate does impact future projections and must, therefore, be considered when interpreting results. Changes in river flow variability, important for water management planning, can be easily assessed from simple resampling techniques applied to both baseline and future time horizons. Assessing future climate and its potential implication for river flows is a key challenge facing water resource planners. This two-part paper demonstrates that uncertainty due to hydrological and climate modelling must and can be accounted for to provide sound, scientifically-based advice to decision makers.     

A method to evaluate the usability of interactive climate change impact decision aids

Reducing the impacts from climate change requires people to make decisions that may prompt substantial changes in their lives. One possible way to help them is with personalized decision aids. Here we describe a method for evaluating such aids, in terms of how they affect users’ understanding of their situation, defined in terms of their (a) knowledge, (b) consistency of preferences, and (c) active mastery of the material. Our method provides a simple way to evaluate the usability of climate-change decision aids, and to address concerns that the choice of display could bias users’ attitudes. We demonstrate it with the Surging Seas Risk Finder, a decision aid focused on coastal flooding (http://sealevel.climatecentral.org/).     

From headwater tributaries to international river: Observing and adapting to climate variability and change in the Nile basin

Egypt is almost totally dependent upon water that originates from the upstream headwaters of the Nile in the humid Ethiopian and East African highlands. Analysis of rainfall and river flow records during the 20th century demonstrates high levels of interannual and interdecadal variability. This is experienced locally and regionally in the headwater regions of the Nile and internationally through its effects on downstream Nile flows in Sudan and Egypt. Examples of climate variability are presented from areas in the basin where it exerts a strong influence on society; the Ethiopian highlands (links with food security), Lake Victoria (management of non-stationary lake levels) and Egypt (exposure to interdecadal variability of Nile flows). These examples reveal adaptations across various scales by individuals and institutions acting alongside other social and economic considerations.Water resources management in the downstream riparian Egypt has involved institutional level reactive adaptations to prolonged periods of low and high Nile flows. Observed responses include the establishment of more robust contingency planning and early warning systems alongside strategic assessment of water use and planning in response to low flows during the 1980s. In the 1990s high flows have enabled Egypt to pursue opportunistic policies to expand irrigation. These policies are embedded in wider socio-political and economic considerations but increase Egypt's exposure and sensitivity to climate driven fluctuations in Nile flows. Analysis of climate change projections for the region shows there is no clear indication of how Nile flows will be affected because of uncertainty about future rainfall patterns in the basin. In many instances the most appropriate entry point for adaptation to climate change will be coping with climate variability and will play out against the certainty of looming national water scarcity in Egypt due to rapid population growth and its possible exacerbation by water demands from upstream riparians.     

The impact of climate change on cropland productivity: evidence from satellite based products at the river basin scale in Africa

We investigate the effect of climate change on crop productivity in Africa using satellite derived data on land use and net primary productivity (NPP) at a small river basin scale, distinguishing between the impact of local and upper-catchment weather. Regression results show that both of these are determining factors of local cropland productivity. These estimates are then combined with climate change predictions obtained from two general circulation models (GCMs) under two greenhouse gas emissions (GHG) assumptions to evaluate the impact of climate change by 2100. For some scenarios significant decreases are predicted over the northern and southern parts of Africa.     

Estimation of impact of climate change on the peak discharge probability of the river Rhine

RHINEFLOW is a GIS based water balance model that has been developed to study the changes in the water balance compartments of the river Rhine basin on a monthly time basis. The model has been designed to study the sensitivity of the Rhine discharge to a climate change. The calculated discharge has been calibrated and validated on the period 1956 to 1980. For this period the model efficiency of RHINEFLOW is between 0.74 and 0.81 both for the entire Rhine and for its tributaries. Also calculated values for variations in other compartments, e.g. snow storage and actual evapotranspiration, were in good agreement with the measured values.Since a high correlation between monthly discharge and peak discharge was found for the period 1900–1980 The RHINEFLOW model is used to assess the probability of exceedence for discharge peaks under possible future climate conditions.The probabilities of exceedence were calculated from the conditional probabilities of peak discharges for a series of 15 classes of monthly discharges. Comparison of a calculated frequency distribution of high discharge peaks with observed peaks in a test series showed that the method performs well.Scenarios for temperature changes between 0 °C and plus 4 °C and precipitation changes between plus 20% and minus 20% have been applied. Within this range flood frequencies are more sensitive for a precipitation change than for a temperature change. The present two-year return period peak flow (6500–7000 m³/s) decreases by about 6% due to a temperature rise of 4 °C; a precipitation decrease of 20% leads to 30% lower two-year peaks whilst 20% precipitation increase raises them by approximately 30%.Application of a Business As Usual (BAU) and an Accelerated Policy (AP) climate scenario resulted in a significant increase in probability of peak flows for the BAU scenario, while for the AP scenario no significant change could be found. Due to sampling errors, accurate estimations of recurrence times of discharge peaks7000 m³/s require a longer sampling time series than 90 years. For management purposes the method can be applied to estimate changes of probabilities of events with a relatively long recurrence time.     

A co-evolutionary approach to climate change impact assessment: Part I. Integrating socio-economic and climate change scenarios

Climate change policies currently pay disproportionately greater attention to the mitigation of climate change through emission reductions strategies than to adaptation measures. Realising that the world is already committed to some global warming, policy makers are beginning to turn their attention to the challenge of preparing society to adapt to the unfolding impacts at the local level. This two-part article presents an integrated, or `co-evolutionary', approach to using scenarios in adaptation and vulnerability assessment. Part I explains how climate and social scenarios can be integrated to better understand the inter-relationships between a changing climate and the dynamic evolution of social, economic and political systems. The integrated scenarios are then calibrated so that they can be applied `bottom up’ to local stakeholders in vulnerable sectors of the economy. Part I concludes that a co-evolutionary approach (1) produces a more sophisticated and dynamic account of the potential feedbacks between natural and human systems; (2) suggests that sustainability indicators are both a potentially valuable input to and an output of integrated scenario formulation and application. Part II describes how a broadly representative sample of public, private and voluntary organisations in the East Anglian region of the UK responded to the scenarios, and identifies future research priorities.     

The benefits of quantifying climate model uncertainty in climate change impacts assessment: an example with heat-related mortality change estimates

The majority of climate change impacts assessments account for climate change uncertainty by adopting the scenario-based approach. This typically involves assessing the impacts for a small number of emissions scenarios but neglecting the role of climate model physics uncertainty. Perturbed physics ensemble (PPE) climate simulations offer a unique opportunity to explore this uncertainty. Furthermore, PPEs mean it is now possible to make risk-based impacts estimates because they allow for a range of estimates to be presented to decision-makers, which spans the range of climate model physics uncertainty inherent from a given climate model and emissions scenario, due to uncertainty associated with the understanding of physical processes in the climate model. This is generally not possible with the scenario-based approach. Here, we present the first application of a PPE to estimate the impact of climate change on heat-related mortality. By using the estimated impacts of climate change on heat-related mortality in six cities, we demonstrate the benefits of quantifying climate model physics uncertainty in climate change impacts assessment over the more common scenario-based approach. We also show that the impacts are more sensitive to climate model physics uncertainty than they are to emissions scenario uncertainty, and least sensitive to whether the climate change projections are from a global climate model or a regional climate model. The results demonstrate the importance of presenting model uncertainties in climate change impacts assessments if the impacts are to be placed within a climate risk management framework.     

Impact of climate change on low-flows in the river Meuse

In this study observed precipitation, temperature, and discharge records from the Meuse basin for the period 1911–2003 are analysed. The primary aim is to establish which meteorological conditions generate (critical) low-flows of the Meuse. This is achieved by examining the relationships between observed seasonal precipitation and temperature anomalies, and low-flow indices. Secondly, the possible impact of climate change on the (joint) occurrence of these low-flow generating meteorological conditions is addressed. This is based on the outcomes of recently reported RCM climate simulations for Europe given a scenario with increased atmospheric greenhouse-gas concentrations. The observed record (1911–2003) hints at the importance of multi-seasonal droughts in the generation of critical low-flows of the river Meuse. The RCM simulations point to a future with wetter winters and drier summers in Northwest Europe. No increase in the likelihood of multi-seasonal droughts is simulated. However, the RCM scenario runs produce multi-seasonal precipitation and temperature anomalies that are out of the range of the observed record for the period 1911–2003. The impact of climate change on low-flows has also been simulated with a hydrological model. This simulation indicates that climate change will lead to a decrease in the average discharge of the Meuse during the low-flow season. However, the model has difficulties to simulate critical low-flow conditions of the Meuse.     

Potential impact of climate change on the water availability of South Saskatchewan River Basin

The potential hydrologic impact of climatic change on three sub-basins of the South Saskatchewan River Basin (SSRB) within Alberta, namely, Oldman, Bow and Red Deer River basins was investigated using the Modified Interactions Soil-Biosphere-Atmosphere (MISBA) land surface scheme of Kerkhoven and Gan (Advances in Water Resources 29:808–826 2006). The European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40) climate data, Digital Elevation Model of the National Water Research Institute, land cover data and a priori soil parameters from the Ecoclimap global data set were used to drive MISBA to simulate the runoff of SSRB. Four SRES scenarios (A21, A1FI, B21 and B11) of four General Circulation Models (CCSRNIES, CGCM2, ECHAM4 and HadCM3) of IPCC were used to adjust climate data of the 1961–1990 base period (climate normal) to study the effect of climate change on SSRB over three 30-year time periods (2010–2039, 2040–2069, 2070–2099). The model results of MISBA forced under various climate change projections of the four GCMs with respect to the 1961–1990 normal show that SSRB is expected to experience a decrease in future streamflow and snow water equivalent, and an earlier onset of spring runoff despite of projected increasing trends in precipitation over the 21st century. Apparently the projected increase in evaporation loss due to a warmer climate over the 21st century will offset the projected precipitation increase, leading to an overall decreasing trend in the basin runoff of SSRB. Finally, a Gamma probability distribution function was fitted to the mean annual maximum flow and mean annual mean flow data simulated for the Oldman, Bow and Red Deer River Basins by MISBA to statistically quantify the possible range of uncertainties associated with SRES climate scenarios projected by the four GCMs selected for this study.     

黑龙江省1981-2010年气候平均值的变化及对气候评价的影响

利用黑龙江省气候评价业务使用的71个气象台站的气温、降水和日照时数资料,对1981-2010年气候平均值和1971-2000年气候平均值进行比较。结果表明:黑龙江省大部地区年平均气温升高,冬季偏暖突出;年降水量大部地区增多,春季、夏季、冬季降水量增多,秋季减少,7月降水量增幅最大;年日照时数大部地区减少。     

The impact of climate change on the Niger River Basin hydroclimatology, West Africa

Climate change has the potential to reduce water availability in West Africa. This study aims to quantify the expected impact of increased greenhouse gases (GHGs) on hydroclimatology of Niger River Basin (NRB). Boundary data from a general circulation model are used to force a regional climate model, to produce dynamically downscaled hydroclimatic variables of NRB under present-day (PRS) and future climate scenarios. The data were further analyzed to detect changes in atmospheric and surface water balance components and moisture recycling ratio (β). The results show that elevated GHGs (under A1B scenario) would produce a drier climate during the rainy season and a wetter climate during the dry season. A warmer climate over NRB in all months was projected. Highest temperature increase of 3 °C occurs about 14°N in May and June, and the smallest increase of 0.5 °C occurs below 8°N in wet-dry transition period. Evaporation reduces during wet season and increases during the dry periods. Humidity increases by 2 % in the dry season, but decreases by 2–4 % in the wet season. Maximum change in moisture influx of 20.7 % and outflux of 20.6 % occur in June and July, respectively. β is projected to decrease in 75 % of the months with biggest relative change of ?18.4 % in June. The projected decrease in precipitation efficiency (ρ) during the wet season reaches ?20.3 % in June. For PRS run, about 66 % of the available atmospheric moisture in NRB precipitates between June and September, of which around 21 % originates from local evaporation. The result suggests that under enhanced GHGs, local evaporation will contribute less to atmospheric moisture and precipitation over the basin. Projected changes in rainfall and streamflow for Upper Niger and Benue sub-basin are significantly different during the wet season.     

Interdecadal variability of regional climate change: implications for the development of regional climate change scenarios

Summary Illustrative examples are discussed of the interdecadal variability features of the regional climate change signal in 5 AOGCM transient simulations. It is shown that the regional precipitation change signal is characterized by large variability at decadal to multidecadal scales, with the structure of the variability varying markedly across regions. Conversely, the regional temperature change signal shows low interdecadal variability. Results are compared across scenarios, models and different realizations with the same model. Our analysis indicates that, at the decadal scale, linear scaling of the regional climate change signal by the global temperature change works relatively well for temperature but less so for precipitation. The nonlinear fraction of the climate change signal tends to decrease with the magnitude of the signal. The implications of interdecadal variability for the generation of regional climate change scenarios are discussed, in particular concerning the use of multi-experiment ensembles to produce such scenarios.     

Vulnerability to climate change in the Arctic: A case study from Arctic Bay,Canada

This paper develops a vulnerability-based approach to characterize the human implications of climate change in Arctic Bay, Canada. It focuses on community vulnerabilities associated with resource harvesting and the processes through which people adapt to them in the context of livelihood assets, constraints, and outside influences. Inuit in Arctic Bay have demonstrated significant adaptability in the face of changing climate-related exposures. This adaptability is facilitated by traditional Inuit knowledge, strong social networks, flexibility in seasonal hunting cycles, some modern technologies, and economic support. Changing Inuit livelihoods, however, have undermined certain aspects of adaptive capacity, and have resulted in emerging vulnerabilities in certain sections of the community.     

Uncertainty in climate change projections: the role of internal variability

Uncertainty in future climate change presents a key challenge for adaptation planning. In this study, uncertainty arising from internal climate variability is investigated using a new 40-member ensemble conducted with the National Center for Atmospheric Research Community Climate System Model Version 3 (CCSM3) under the SRES A1B greenhouse gas and ozone recovery forcing scenarios during 2000–2060. The contribution of intrinsic atmospheric variability to the total uncertainty is further examined using a 10,000-year control integration of the atmospheric model component of CCSM3 under fixed boundary conditions. The global climate response is characterized in terms of air temperature, precipitation, and sea level pressure during winter and summer. The dominant source of uncertainty in the simulated climate response at middle and high latitudes is internal atmospheric variability associated with the annular modes of circulation variability. Coupled ocean-atmosphere variability plays a dominant role in the tropics, with attendant effects at higher latitudes via atmospheric teleconnections. Uncertainties in the forced response are generally larger for sea level pressure than precipitation, and smallest for air temperature. Accordingly, forced changes in air temperature can be detected earlier and with fewer ensemble members than those in atmospheric circulation and precipitation. Implications of the results for detection and attribution of observed climate change and for multi-model climate assessments are discussed. Internal variability is estimated to account for at least half of the inter-model spread in projected climate trends during 2005–2060 in the CMIP3 multi-model ensemble.     

辽河流域气候变化及对径流影响预估与评估分析

辽河流域属于气候变暖较为显著区域,增温幅度比全球和全国的增温幅度都要高。同时辽河流域也是水资源较为匮乏且需求量大的地区,因此气候变化对水资源影响问题也更值得关注。基于长期历史观测气象水文数据和未来不同情景下气候变化预估资料,建立评估气候变化与径流量的关系,预估未来气候变化对径流量的可能影响,为辽河流域应对气候变化决策提供科学依据。结果表明：1961—2020年,辽河流域气温为持续上升趋势,降水没有明显的增减趋势,但存在阶段性变化;辽河流域降水量与径流量有较好的相关关系,具有较为一致的长期变化趋势与特征,年降水量与径流量相关数达到0.6以上。日降水量与径流量相关分析表明,降水发生后次日且为大雨降水等级(即日降水量≥25 mm)时,两者相关系数可高达0.85;敏感性试验和模式模拟试验表明,径流量对气候变化有明显的响应,降水增加(减少)、气温降低(升高),则径流量增加(减少);在未来RCP8.5排放情景下气温升高趋势最为明显,未来径流量也为显著增加趋势;RCP2.6排放情景下气温增加的幅度最小,未来径流量也表现为无明显增减趋势;RCP4.5情景下,气温增加的幅度居中,未来径流量则为减少趋势。     

Cultural barriers to climate change adaptation: A case study from Northern Burkina Faso

Human adaptation to climate change is a heterogeneous process influenced by more than economic and technological development. It is increasingly acknowledged in the adaptation to climate change literature that factors such as class, gender and culture play a large role when adaptation strategies are either chosen or rejected at the local scale. This paper explores adaptation strategies by focusing on livelihood diversification in the face of the most recent of recurrent droughts in the Sahel. It is shown that for Fulbe, one of the two main ethnic groups in the small village in Northern Burkina Faso studied, culture acts as a major barrier to embracing four of the most successful livelihood strategies: labour migration, working for development projects, gardening, and the engagement of women in economic activities.     

Impact of snow variability on the Swiss winter tourism sector: implications in an era of climate change

An analysis procedure is developed to explore the robustness and overall productivity of reservoir management under plausible assumptions about climate fluctuation and change. Results are presented based on a stylized version of a multi-use reservoir management model adapted from Angat Dam, Philippines. Analysis focuses on October-March, during which climatological inflow declines as the dry season arrives, and reservoir management becomes critical and challenging. Inflow is assumed to be impacted by climate fluctuations representing interannual variation (white noise), decadal to multidecadal variability (MDV, here represented by a stochastic autoregressive process) and global change (GC), here represented by a systematic linear trend in seasonal inflow total over the simulation period of 2008–2047. Stochastic (Monte Carlo) simulations are undertaken to explore reservoir performance. In this way, reservoir reliability and risk of extreme persistent water deficit are assessed in the presence of different combinations and magnitudes of GC and MDV. The effectiveness of dynamic management is then explored as a possible climate change adaptation practice, focusing on reservoir performance in the presence of a 20 % downward inflow trend. In these dynamic management experiments, the October-March water allocation each year is adjusted based on seasonal forecasts and updated climate normals. The results illustrate how, in the near-term, MDV can be as significant as GC in impact for this kind of climate-related problem. The results also illustrate how dynamic management can mitigate the impacts. Overall, this type of analysis can deliver guidance on the expected benefits and risks of different management strategies and climate scenarios.