Assessing the influence of climate model uncertainty on EU-wide climate change impact indicators

Despite an increasing understanding of potential climate change impacts in Europe, the associated uncertainties remain a key challenge. In many impact studies, the assessment of uncertainties is underemphasised, or is not performed quantitatively. A key source of uncertainty is the variability of climate change projections across different regional climate models (RCMs) forced by different global circulation models (GCMs). This study builds upon an indicator-based NUTS-2 level assessment that quantified potential changes for three climate-related hazards: heat stress, river flood risk, and forest fire risk, based on five GCM/RCM combinations, and non-climatic factors. First, a sensitivity analysis is performed to determine the fractional contribution of each single input factor to the spatial variance of the hazard indicators, followed by an evaluation of uncertainties in terms of spread in hazard indicator values due to inter-model climate variability, with respect to (changes in) impacts for the period 2041–70. The results show that different GCM/RCM combinations lead to substantially varying impact indicators across all three hazards. Furthermore, a strong influence of inter-model variability on the spatial patterns of uncertainties is revealed. For instance, for river flood risk, uncertainties appear to be particularly high in the Mediterranean, whereas model agreement is higher for central Europe. The findings allow for a hazard-specific identification of areas with low vs. high model agreement (and thus confidence of projected impacts) within Europe, which is of key importance for decision makers when prioritising adaptation options.     

Regional climate changes as the factors of impact on the objects of construction and infrastructure

Considered are the changes in the climate impact on the objects of construction and infrastructure on the territory of Russia. The focus is on the changes in the characteristics of daily air temperature and precipitation expected by the middle of the 21st century, which are of high importance in terms of the building design. The assessment of expected changes is based on the results of ensemble computations using the MGO gobal climate model and the embedded regional model (MGO RCM) with the horizontal resolution of 25 km. Along with the ensemble-averaged estimates of changes in applied climate parameters, an uncertainty of estimates associated with the natural climate variability is analyzed using the data of numerical experiments. The attention is drawn to the most significant effects of climate changes which should be taken into account when developing the measures for adapting the construction sector in Russia.     

Using second-order approximation to incorporate GCM uncertainty in climate change impact assessments

This study presents a method to incorporate uncertainty of climate variables in climate change impact assessments, where the uncertainty being considered refers to the divergence of general circulation model (GCM) projections. The framework assesses how much bias occurs when the uncertainties of climate variables are ignored. The proposed method is based on the second-order expansion of Taylor series, called second-order approximation (SOA). SOA addresses the bias which occurs by assuming the expected value of a function is equal to the function of the expected value of the predictors. This assumption is not valid for nonlinear systems, such as in the case of the relationship of climate variables to streamflow. To investigate the value of SOA in the climate change context, statistical downscaling models for monthly streamflow were set up for six hydrologic reference stations in Australia which cover contrasting hydro-climate regions. It is shown that in all locations SOA makes the largest difference for low flows and changes the overall mean flow by 1–3%. Another advantage of the SOA approach is that the individual contribution of each climate variable to the total difference can be estimated. It is found that geopotential height and specific humidity cause more bias than wind speeds in the downscaling models considered here.     

Future changes of the atmospheric composition and the impact of climate change

The development of the future atmospheric chemical composition is investigated with respect to NO _y and O₃ by means of the off‐line coupled dynamic‐chemical general circulation model ECHAM3/CHEM. Two time slice experiments have been performed for the years 1992 and 2015, which include changes in sea surface temperatures, greenhouse gas concentrations, emissions of CFCs, NO _x and other species, i.e., the 2015 simulation accounts for changes in chemically relevant emissions and for a climate change and its impact on air chemistry. The 2015 simulation clearly shows a global increase in ozone except for large areas of the lower stratosphere, where no significant changes or even decreases in the ozone concentration are found. For a better understanding of the importance of (A) emissions like NO _x and CFCs, (B) future changes of air temperature and water vapour concentration, and (C) other dynamical parameters, like precipitation and changes in the circulation, diabatic circulation, stratosphere‐troposphere‐exchange, the simulation of the future atmosphere has been performed stepwise. This method requires a climate‐chemistry model without interactive coupling of chemical species. Model results show that the direct effect of emissions (A) plays a major rôle for the composition of the future atmosphere, but they also clearly show that climate change (B and C) has a significant impact and strongly reduces the NO _y and ozone concentration in the lower stratosphere.     

A simple model perturbed physics study of the simulated climate sensitivity uncertainty and its relation to control climate biases

In this study the relationship between climate model biases in the control climate and the simulated climate sensitivity are discussed on the basis of perturbed physics ensemble simulations with a globally resolved energy balance (GREB) model. It is illustrated that the uncertainties in the simulated climate sensitivity (estimated by the transient response to CO₂ forcing scenarios in the twenty first century or idealized 2 × CO₂ forcing experiments) can be conceptually split into two parts: a direct effect of the perturbed physics on the climate sensitivity independent of the control mean climate and an indirect effect of the perturbed physics by changing the control mean climate, which in turn changes the climate sensitivity, as the climate sensitivity itself is depending on the control climate. Biases in the control climate are negatively correlated with the climate sensitivity (colder climates have larger sensitivities), if no physics are perturbed. Perturbed physics that lead to warmer control climate, would in average also lead to larger climate sensitivities, if the control climate is held at the observed reference climate by flux corrections. Thus the effects of control biases and perturbed physics are opposing each other and are partially cancelling each other out. In the GREB model the biases in the control climate are the more important effect for the regional climate sensitivity uncertainties, but for the global mean climate sensitivity both, the biases in the control climate and the perturbed physics, are equally important.     

Regional climate changes as simulated in time-slice experiments

Three 30 year long simulations have been performed with a T42 atmosphere model, in which the sea-surface temperature (SST) and sea-ice distribution have been taken from a transient climate change experiment with a T21 global coupled ocean-atmosphere model. In this so-called time-slice experiment, the SST values (and the greenhouse gas concentration) were taken at present time CO₂ level, at the time of CO₂ doubling and tripling.The annual cycle of temperature and precipitation has been studied over the IPCC regions and has been compared with observations. Additionally the combination of temperature and precipitation change has been analysed. Further parameters investigated include the difference between daily minimum and maximum temperature, the rainfall intensity and the length of droughts.While the regional simulation of the annual cycle of the near surface temperature is quite realistic with deviations rarely exceeding 3 K, the precipitation is reproduced to a much smaller degree of accuracy.The changes in temperature at the time of CO₂ doubling amount to only 30–40% of those at the 3 * CO₂ level and show hardly any seasonal variation, contrary to the 3 * CO₂ experiment. The comparatively small response to the CO₂ doubling can be attributed to the cold-start of the simulation, from which the SST has been extracted. The strong change in the seasonality cannot be explained by internal fluctuations and cold start alone, but has to be caused by feedback mechanisms. Due to the delay in warming caused by the transient experiment, from which the SST has been derived, the 3 * CO₂ experiment can be compared to the CO₂ doubling studies performed with mixed-layer models.The precipitation change does not display a clear signal. However, an increase of the rain intensity and of longer dry periods is simulated in many regions of the globe.The changes in these parameters as well as the combination of temperature- and precipitation change and the changes in the daily temperature range give valuable hints, in which regions observational studies should be intensified and under which aspects the observational data should be evaluated.     

Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia

Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021–2060 and far future period 2061–2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment.     

Global-scale climate impact functions: the relationship between climate forcing and impact

Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator.     

Satellite monitoring of global land cover changes and their impact on climate

Land cover is a crucial, spatially and temporally varying component of global carbon and climate systems. Therefore accurate estimation and monitoring of land cover changes is important in global change research. Although, land cover has dramatically changed over the last few centuries, until now there has been no consistent way of quantifying the changes globally.In this study we used long-term climate, soils data along with coarse resolution satellite observations to quantify the magnitude and spatial extent of global land cover changes due to anthropogenic processes. Differences between potential leaf area index, derived from climate-soil-leaf area equilibrium and actual leaf area index obtained from satellite data were used to estimate changes in land cover.Forest clearing for agriculture and irrigated farming in arid and semi-arid lands are found to be two major sources of climatically important land cover changes. Satellite derived Spectral Vegetation indices (SV I) and surface temperatures (T s) show strong impact of land cover changes on climatic processes. Irrigated agriculture in dry areas increased energy absorption and evapotranspiration (ET) compared to natural vegetation. On the other hand, forest clearing for crops decreased energy absorption andET. A land cover classification and monitoring system is proposed using satellite derivedSV I andT s that simultaneously characterize energy absorption and exchange processes. This completely remote sensing based approach is useful for monitoring land cover changes as well as their impacts on climate. Monitoring the spatio-temporal dynamics of land cover is possible with current operational satellites, and could be substantially improved with the Earth Observing System (EOS) era satellite sensors.     

Impact of reservoir operation and climate change on the hydrological regime of the Sesan and Srepok Rivers in the Lower Mekong Basin

The transboundary Sesan and Srepok sub-basins (2S) are the “hot-spot” areas for reservoir development in the Lower Mekong region, with 12 reservoirs built in the Vietnam territory. This study examines the impacts of reservoir operations in Vietnam and projected climate change on the downstream hydrologic regime of the 2S Rivers by jointly applying the Soil Water Assessment Tool (SWAT) and Water Evaluation and Planning (WEAP) models. Different scenarios of reservoir operation are considered and simulated to assess their impact on annual, seasonal, and monthly flow regimes under maximum hydropower capacity generation with and without taking into account the minimum flow requirement downstream near the Vietnam border with Cambodia. The precipitation and temperature projections from the high-resolution regional climate model HadGEM3-RA under two Representative Concentration Pathways, 4.5 and 8.5, of HadGEM2-AO are used as future climate change scenarios for the impact assessment. The study results show that reservoir operation leads to an increase in the dry season stream flows and a decrease in the wet season stream flows. The monthly flow regime exhibits considerable changes for both the Sesan and Srepok Rivers but with different magnitudes and patterns of increase and decrease. Climate change is likely to induce considerable changes in stream flows, though these changes are comparatively lower than those caused by reservoir operation. Climate change is likely to have both counterbalancing and reinforcing effects over the impact of reservoir operation, reducing changes during dry season but increasing changes in most of the other months.     

Abrupt changes as indicators of decadal climate variability

 A statistical test has revealed that abrupt regional climate changes are produced in a coupled atmosphere-ocean general circulation model. Abrupt changes are detected over much of the globe although the occurrence frequency is small over the continents. Over the tropical Pacific Ocean and northern Pacific Ocean, surface air temperature (SAT) and sea level pressure (SLP) shift rapidly on decadal time scales. The regional climate changes presented here have been classified into three types. The first type consists of statistically significant shifts in SLP and statistically significant shifts in SAT which are of opposite sign, and which are reinforced through a positive feedback between the atmosphere and the ocean. The second type is for those occurrences where changes are of the same sign. The third type includes those with a significant shift in only one meteorological element. The second and third types are generally generated by changes in air pressure and wind fields induced by changes of the first type. For example, when SLP increases and sea surface temperature (SST) decreases abruptly in the tropical Pacific Ocean, it triggers abrupt regional changes in middle and high latitudes. The abrupt changes in the model climate have characteristics which are very similar to those of observed rapid shifts. Thus, it is concluded that abrupt changes are a predominant part of regional climate change on decadal time scales. Received: 11 February 1999 / Accepted: 18 May 2000     

The impact of ecosystem functional type changes on the La Plata Basin climate

In this paper, the effects of land cover changes on the climate of the La Plata Basin in southern South America are investigated using the Weather and Research Forecasting (WRF) Model configured on a 30/10km two-way interactive nested grid. To assess the regional climate changes resulting from land surface changes, the standard land cover types are replaced by time-varying Ecosystem Functional Types (EFTs), which is a newly devised land-cover classification that characterizes the spatial and interannual variability of surface vegetation dynamics. These variations indicate that natural and anthropogenic activities have caused changes in the surface physical parameters of the basin, such as albedo and roughness length, that contributed to regional climate changes. EFTs are obtained from functional attributes of vegetation computed from properties of the Normalized Difference Vegetation Index (NDVI) to represent patches of the land surface with homogeneous energy and gas exchanges with the atmosphere. Four simulations are conducted, each experimental period ranging from September to November in two contrasting years, 1988 and 1998. The influence of an identical EFT change on the surface heat fluxes, 2-m temperature and humidity, 10-m winds, convective instabilities and large-scale moisture fluxes and precipitation are explored for 1988 (a dry year) and 1998 (a wet year). Results show that the surface and atmospheric climate has a larger response to the same EFT changes in a dry year for 2-m temperature and 10-m wind; the response is larger in a wet year for 2-m water vapor mixing ratio, convective available potential energy, vertically integrated moisture fluxes and surface precipitation. For EFTs with high productivity and a weak seasonal cycle, the nearsurface temperature during the spring of 1988 and 1998 increased by as much as 1℃ in the central and western portions of La Plata Basin. Additionally, for higher productivity EFTs, precipitation differences were generally positive in both dry and wet years, although the patterns are not uniform and exhibit certain patchiness with drier conditions.     

The impact of potential abrupt climate changes on near-term policy choices

We investigate an important scientific uncertainty facing climate-change policymakers, namely, the impact of potential abrupt climatic change. We examine sequential decision strategies for abating climate change where near-term policies are viewed as the first of a series of decisions which adapt over the years to improving scientific information. We compare two illustrative near-term (1992–2002) policies - moderate and aggressive emission reductions - followed by a subsequent long-term policy chosen to limit global-mean temperature change to a specified ‘climate target’. We calculate the global-mean surface temperature change using a simple climate/ocean model and simple models of greenhouse-gas concentrations. We alter model parameters to examine the impact of abrupt changes in the sinks of carbon dioxide, the sources of methane, the circulation of the oceans, and the climate sensitivity, ΔT _2x. Although the abrupt changes increase the long-term costs of responding to climate change, they do not significantly affect the comparatively small cost difference between near-term strategies. Except for an abrupt increase in ΔT _2x, the investigated abrupt climate changes do not significantly alter the values of the climate target for which each near-term strategy is preferred. In contrast, innovations that reduce the cost of limiting greenhouse-gas emissions offer the potential for substantial abatement cost savings, regardless of which level of near-term abatement is selected.     

Aerosol and ozone changes as forcing for climate evolution between 1850 and 2100

Global aerosol and ozone distributions and their associated radiative forcings were simulated between 1850 and 2100 following a recent historical emission dataset and under the representative concentration pathways (RCP) for the future. These simulations were used in an Earth System Model to account for the changes in both radiatively and chemically active compounds, when simulating the climate evolution. The past negative stratospheric ozone trends result in a negative climate forcing culminating at ?0.15 W m^?2 in the 1990s. In the meantime, the tropospheric ozone burden increase generates a positive climate forcing peaking at 0.41 W m^?2. The future evolution of ozone strongly depends on the RCP scenario considered. In RCP4.5 and RCP6.0, the evolution of both stratospheric and tropospheric ozone generate relatively weak radiative forcing changes until 2060–2070 followed by a relative 30 % decrease in radiative forcing by 2100. In contrast, RCP8.5 and RCP2.6 model projections exhibit strongly different ozone radiative forcing trajectories. In the RCP2.6 scenario, both effects (stratospheric ozone, a negative forcing, and tropospheric ozone, a positive forcing) decline towards 1950s values while they both get stronger in the RCP8.5 scenario. Over the twentieth century, the evolution of the total aerosol burden is characterized by a strong increase after World War II until the middle of the 1980s followed by a stabilization during the last decade due to the strong decrease in sulfates in OECD countries since the 1970s. The cooling effects reach their maximal values in 1980, with ?0.34 and ?0.28 W m^?2 respectively for direct and indirect total radiative forcings. According to the RCP scenarios, the aerosol content, after peaking around 2010, is projected to decline strongly and monotonically during the twenty-first century for the RCP8.5, 4.5 and 2.6 scenarios. While for RCP6.0 the decline occurs later, after peaking around 2050. As a consequence the relative importance of the total cooling effect of aerosols becomes weaker throughout the twenty-first century compared with the positive forcing of greenhouse gases. Nevertheless, both surface ozone and aerosol content show very different regional features depending on the future scenario considered. Hence, in 2050, surface ozone changes vary between ?12 and +12 ppbv over Asia depending on the RCP projection, whereas the regional direct aerosol radiative forcing can locally exceed ?3 W m^?2.     

Considering attitudinal uncertainty in the climate change skepticism continuum

In this paper we present an empirically driven language to discuss climate change skepticism. We conceptualize skeptic/skepticism as an umbrella term that includes those who actively reject climate science and those who are uncertain about climate change. We propose four categories for better empirical analysis of climate skepticism: epistemic deniers, epistemic doubters (borrowing from Capstick and Pidgeon 2014), attribution deniers, and attribution doubters (borrowing from Rahmstorf 2004). Using a unique dataset of surveys (n = 1000) and interviews (n = 33) with residents of the U.S. Pacific Northwest who are skeptical about climate change, we compare those four groups across several predictors and demographic variables (age, race, gender, political ideology, religiosity, income, education, and level of trust in science) and outcome variables (environmental concern, policy support, and conspiracy ideation (adherence to the belief that climate change is a “hoax”). We demonstrate the importance of considering attitudinal uncertainty in the analysis of climate skepticism by providing evidence for the presence of a continuum of thought wherein epistemic deniers and attribution doubters make up the two ends of a continuum with more complicated distinctions between epistemic doubters and attribution deniers.     

Evaluation of the impact of climate changes on water storage and groundwater recharge at the watershed scale

 The increase of concentration of carbon dioxide and other greenhouse gases in the atmosphere will certainly affect hydrological regimes. Global warning is thus expected to have major implications on water resources management. Our objective is to present a general approach to evaluate the effect of potential climate changes on groundwater resources. In the current stage of knowledge, large-scale global climate models are probably the best available tools to provide estimates of the effects of raising greenhouse gases on rainfall and evaporation patterns through a continuous, three dimensional simulation of atmospheric, oceanic and cryospheric processes. However their spatial resolution (generally some thousands of square kilometers) is not compatible with that of watershed hydrologic models. The main purpose of this study is to evaluate the impact of potential climate changes upon groundwater resources. A general methodology is proposed in order to disaggregate outputs of large-scale models and thus to make information directly usable by hydrologic models. As an illustration, this method is applied to a CO₂-doubling scenario through the development of a local weather generator, although many uncertainties are not yet assessed about the results of climate models. Two important hydrological variables: rainfall and potential evapotranspiration are thus generated. They are then used by coupling with a physically based hydrological model to estimate the effects of climate changes on groundwater recharge and soil moisture in the root zone. Received: 17 April 1998 / Accepted: 29 September 1998