Greenhouse Gas Scenarios Research Articles

FUTURE GLOBAL MORTALITY FROM CHANGES IN AIR POLLUTION ATTRIBUTABLE TO CLIMATE CHANGE.

The effect of ozone and fine particulate matter on human health is dependent on emissions and climate change. Here the effects of climate change on air pollution mortality are isolated, with increases predicted in all regions except Africa. Ground-level ozone and fine particulate matter (PM 2.5) are associated with premature human mortality1,2,3,4; their future concentrations depend on changes in emissions, which dominate the near-term5, and on climate change6,7. Previous global studies of the air-quality-related health effects of future climate change8,9 used single atmospheric models. However, in related studies, mortality results differ among models10,11,12. Here we use an ensemble of global chemistry–climate models13 to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP8.5 (ref. 14), is probably positive. We estimate 3,340 (−30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (−195,000 to 237,000) in 2100 (14% of the increase in global ozone-related mortality). For PM 2.5, we estimate 55,600 (−34,300 to 164,000) deaths in 2030 and 215,000 (−76,100 to 595,000) in 2100 (countering by 16% the global decrease in PM 2.5-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.

Modelling the response of shallow groundwater levels to combined climate and water-diversion scenarios in Beijing-Tianjin-Hebei Plain, China

A three-dimensional groundwater flow model was implemented to quantify the temporal variation of shallow groundwater levels in response to combined climate and water-diversion scenarios over the next 40 years (2011–2050) in Beijing-Tianjin-Hebei (Jing-Jin-Ji) Plain, China. Groundwater plays a key role in the water supply, but the Jing-Jin-Ji Plain is facing a water crisis. Groundwater levels have declined continuously over the last five decades (1961–2010) due to extensive pumping and climate change, which has resulted in decreased recharge. The implementation of the South-to-North Water Diversion Project (SNWDP) will provide an opportunity to restore the groundwater resources. The response of groundwater levels to combined climate and water-diversion scenarios has been quantified using a groundwater flow model. The impacts of climate change were based on the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset for future high (A2), medium (A1B), and low (B1) greenhouse gas scenarios; precipitation data from CMIP3 were applied in the model. The results show that climate change will slow the rate of decrease of the shallow groundwater levels under three climate-change scenarios over the next 40 years compared to the baseline scenario; however, the shallow groundwater levels will rise significantly (maximum of 6.71 m) when considering scenarios that combine climate change and restrictions on groundwater exploitation. Restrictions on groundwater exploitation for water resource management are imperative to control the decline of levels in the Jing-Jin-Ji area.

Characterizing half‐a‐degree difference: a review of methods for identifying regional climate responses to global warming targets

The Paris Agreement long‐term global temperature goal refers to two global warming levels: well below 2°C and 1.5°C above preindustrial. Regional climate signals at specific global warming levels, and especially the differences between 1.5°C and 2°C, are not well constrained, however. In particular, methodological challenges related to the assessment of such differences have received limited attention. This article reviews alternative approaches for identifying regional climate signals associated with global temperature limits, and evaluates the extent to which they constitute a sound basis for impacts analysis. Four methods are outlined, including comparing data from different greenhouse gas scenarios, sub‐selecting climate models based on global temperature response, pattern scaling, and extracting anomalies at the time of each global temperature increment. These methods have rarely been applied to compare 2°C with 1.5°C, but some demonstrate potential avenues for useful research. Nevertheless, there are methodological challenges associated with the use of existing climate model experiments, which are generally designed to model responses to different levels of greenhouse gas forcing, rather than to model climate responses to a specific level of forcing that targets a given level of global temperature change. Novel approaches may be required to address policy questions, in particular: to differentiate between half degree warming increments while accounting for different sources of uncertainty; to examine mechanisms of regional climate change including the potential for nonlinear responses; and to explore the relevance of time‐lagged processes in the climate system and declining emissions, and the resulting sensitivity to alternative mitigation pathways. WIREs Clim Change 2017, 8:e457. doi: 10.1002/wcc.457This article is categorized under: Assessing Impacts of Climate Change > Scenario Development and Application

Reservoir yield intercomparison of large dams in Jaguaribe Basin-CE in climate change scenarios

ABSTRACT Climate changes can have different impacts on water resources. Strategies to adapt to climate changes depend on impact studies. In this context, this study aimed to estimate the impact that changes in precipitation, projected by Global Circulation Models (GCMs) in the fifth report by the Intergovernmental Panel on Climate Change (IPCC-AR5) may cause on reservoir yield (Q90) of large reservoirs (Castanhão and Banabuiú), located in the Jaguaribe River Basin, Ceará. The rainfall data are from 20 GCMs using two greenhouse gas scenarios (RCP4.5 and RCP8.5). The precipitation projections were used as input data for the rainfall-runoff model (SMAP) and, after the reservoirs’ inflow generation, the reservoir yields were simulated in the AcquaNet model, for the time periods of 2040-2069 and 2070-2099. The results were analyzed and presented a great divergence, in sign (increase or decrease) and in the magnitude of change of Q90. However, most Q90 projections indicated reduction in both reservoirs, for the two periods, especially at the end of the 21th century.

Future projections of wind resource in a mountainous archipelago, Canary Islands

Large-scale atmospheric patterns and near-surface winds are expected to be modified in the future due to climate change, altering the availability of wind resources on a regional scale. These possible changes are especially important in isolated power systems, as is the case for a great percentage of the islands. High-resolution climate regionalization is therefore necessary to assess the future projections of wind resource, mainly in the case of orographically complex territories, such as The Canary Islands. In this work, WRF was used to perform a dynamic regionalization in this Archipelago, using the pseudo-global warming technique to compute the initial and boundary conditions from a reanalysis dataset and from the monthly mean changes obtained from the simulations of fourteen global climate models included in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Projections of mean wind, wind energy density and extractable wind power were obtained for two future decades (2045–2054 and 2090–2099) and for two different greenhouse gas scenarios (RCP4.5 and RCP8.5) and the results were compared with those for 1995–2004. Statistically significant changes in wind resource were found in some areas, mainly during summer. Most of these areas correspond to zones where at present wind farms are located.

Quantification of uncertainty in reference evapotranspiration climate change signals in Belgium

Projections of evapotranspiration form the basis of future runoff and water availability assessment in a climate change context. The scarcity of data or insufficiency of time/funds compels the application of simple reference evapotranspiration (ETo) methods requiring less meteorological inputs for ETo projections which adds uncertainty to the projected changes. This study investigates the bias in ETo climate change signals derived from seven simple temperature- and radiation-based methods (Blaney–Criddle, Hargreaves–Samani, Schendel, Makkink, Turc, Jensen–Haise, Tabari) compared with that from the standard Penman–Monteith FAO 56 method on the basis of 12 general circulation model (GCM) outputs from the Coupled Model Intercomparison Project Phase 5 for central Belgium for four future greenhouse gas scenarios (RCP2.6, RCP4.5, RCP6.0, RCP8.5). The results show the lack of conformity on the amount of ETo changes between the simple and standard methods, with biases of over 100% for some simple methods. The uncertainty affiliated with ETo methods for monthly ETo changes is smaller but of comparable magnitude to GCM uncertainty, which is usually the major source of uncertainty, and larger for daily extreme ETo changes. This emphasizes the imperative of addressing the uncertainty associated with ETo methods for quantifying the hydrological response to climate change.

Climate Change Impacts on Catchment-Scale Extreme Rainfall Variability: Case Study of Rize Province, Turkey

AbstractThis paper conducts a catchment-scale analysis of extreme rainfall events of the reference (1961–1990) and three future climate periods (2013–2039, 2040–2070, and 2071–2100) for Rize Province, Turkey. The extreme value theory (EVT) is applied to analyze observational and projected extreme rainfall data including regional climate model (RCM) outputs guided by two general circulation models (GCM) under SRES-A2 and RCP8.5 greenhouse gas scenarios. A new rapid and effective bias correction method is also developed and applied to adjust the climate models simulations. The EVT analysis results demonstrated significant differences between the model runs for both the reference and future periods with considerable spatial variability in rainfall extremes. Based upon the assembled mean results, approximately a 30% decrease in the median value of extreme rainfall events is projected over the study region for the near future, 2013–2039, and middle of the century. This change dramatically decreases to 15% of i...

Climate change is projected to reduce carrying capacity and redistribute species richness in North Pacific pelagic marine ecosystems

Climate change is expected to impact all aspects of marine ecosystems, including fisheries. Here, we use output from a suite of 11 earth system models to examine projected changes in two ecosystem-defining variables: temperature and food availability. In particular, we examine projected changes in epipelagic temperature and, as a proxy for food availability, zooplankton density. We find that under RCP8.5, a high business-as-usual greenhouse gas scenario, increasing temperatures may alter the spatial distribution of tuna and billfish species richness across the North Pacific basin. Furthermore, warmer waters and declining zooplankton densities may act together to lower carrying capacity for commercially valuable fish by 2-5% per decade over the 21st century. These changes have the potential to significantly impact the magnitude, composition, and distribution of commercial fish catch across the pelagic North Pacific. Such changes will in turn ultimately impact commercial fisheries' economic value. Fishery managers should anticipate these climate impacts to ensure sustainable fishery yields and livelihoods.

A probabilistic study of the return of stratospheric ozone to 1960 levels

AbstractAnthropogenic emissions of greenhouse gases and ozone‐depleting substances are expected to continue to affect concentrations of ozone in the stratosphere through the 21st century. While a range of estimates for when stratospheric ozone is expected to return to unperturbed levels is available in the literature, quantification of the spread in results is sparse. Here we present the first probabilistic study of latitudinally resolved years of return of stratospheric ozone to 1960 levels. Results from our 180‐member ensemble, simulated with a newly developed simple climate model, suggest that the spread in return years of ozone is largest around 40°N/S and in the southern high latitudes and decreases with increasing greenhouse gas emissions. The spread in projections of ozone is larger for higher greenhouse gas scenarios and is larger in the polar regions than in the midlatitudes, while the spread in ozone radiative forcing is smallest in the polar regions.

Climate Feedback Variance and the Interaction of Aerosol Forcing and Feedbacks

AbstractAerosols can influence cloud radiative effects and, thus, may alter interpretation of how Earth’s radiative budget responds to climate forcing. Three different ensemble experiments from the same climate model with different greenhouse gas and aerosol scenarios are used to analyze the role of aerosols in climate feedbacks and their spread across initial condition ensembles of transient climate simulations. The standard deviation of global feedback parameters across ensemble members is low, typically 0.02 W m−2 K−1. Feedbacks from high (8.5 W m−2) and moderate (4.5 W m−2) year 2100 forcing cases are nearly identical. An aerosol kernel is introduced to remove effects of aerosol cloud interactions that alias into cloud feedbacks. Adjusted cloud feedbacks indicate an “aerosol feedback” resulting from changes to climate that increase sea-salt emissions, mostly in the Southern Ocean. Ensemble simulations also indicate higher tropical cloud feedbacks with higher aerosol loading. These effects contribute to a difference in cloud feedbacks of nearly 50% between ensembles of the same model. These two effects are also seen in aquaplanet simulations with varying fixed drop number. Thus aerosols can be a significant modifier of cloud feedbacks, and different representations of aerosols and their interactions with clouds may contribute to multimodel spread in climate feedbacks and climate sensitivity in multimodel archives.

Effects of a warming trend on cool climate viticulture in Michigan, USA.

Historically, Michigan’s climate had mainly three challenges for grape production: growing season temperatures were too low, the growing season was too short and there was too much rain near harvest. However, climate change in the past decades has led to a vastly different landscape that is evolving to meet the new climate. Recently, there has been a significant move from Vitis labrusca (North American) grape plantings to Vitis vinifera (wine grapes) as a consequence of Michigan’s shifting climate. The goal of this study was to analyze the historical shift in climate and its potential future impact on the grape industry. We obtained data climate model projection data from two greenhouse gas (GHG) emission scenarios. First, a multi-linear regression model was built to predict future grape yields (t/ac) using data from the climate model projections. Second, trends in the severity of the three challenges (temperature, season length, precipitation timing) were analyzed. In both GHG scenarios grape yields are seen to improve, but to different extents. The improvement is likely a response to warmer season temperatures canceling out losses to early season frost. Model projections recommend that Michigan’s future climate will be more accommodating for all varieties of grapes. This suggests that grape production will continue to grow, but the landscape will continue to evolve with more emphasis on varieties that are more climatically sensitive to cold temperatures. Climate change has greatly affected Michigan’s viticultural landscape, and will continue to do so in the coming decades.

Climate change and species distribution: possible scenarios for thermophilic ticks in Romania.

Several zoonotic tick-borne diseases are emerging in Europe due to various factors, including changes of the cultural landscape, increasing human populations, variation of social habits and climate change. We have modelled the potential range changes for two thermophilic tick species (Hyalomma marginatum and Rhipicephalus annulatus) by use of MaxEnt® and 15 climatic predictors, taking into account the aptitude for future climatic change in Romania. Current models predict increased temperatures, both in the short term (up to 2050) and in the long term (up to 2070), together with possible changes also of the other climatic factors (e.g. precipitation), and may lead to higher zoonotic risks associated with an expansion of the range of the target species. Three different models were constructed (the present, 2050 and 2070) for four representative concentration pathways (RCPs) of greenhouse gas scenarios: RCP2.6, RCP4.5, RCP6, and RCP8.5. The most dramatic scenario (RCP8.5) produced the highest increase in the probable distribution range for both species. In concordance with similar continental-wide studies, both tick species displayed a shift of distribution towards previously cooler areas of Romania. In most scenarios, this would lead to wider ranges; from 9.7 to 43.1% for H. marginatum, and from 53.4 to 205.2% for R annulatus. Although the developed models demonstrate a good predictive power, the issue of species ecology should also be considered.

Impact of rising greenhouse gas concentrations on future tropical ozone and UV exposure

AbstractFuture projections of tropical total column ozone (TCO) are challenging, as its evolution is affected not only by the expected decline of ozone depleting substances but also by the uncertain increase of greenhouse gas (GHG) emissions. To assess the range of tropical TCO projections, we analyze simulations with a chemistry‐climate model forced by three different GHG scenarios (Representative Concentration Pathway (RCP) 4.5, RCP6.0, and RCP8.5). We find that tropical TCO will be lower by the end of the 21st century compared to the 1960s in all scenarios with the largest decrease in the medium RCP6.0 scenario. Uncertainties of the projected TCO changes arise from the magnitude of stratospheric column decrease and tropospheric ozone increase which both strongly vary between the scenarios. In the three scenario simulations the stratospheric column decrease is not compensated by the increase in tropospheric ozone. The concomitant increase in harmful ultraviolet irradiance reaches up to 15% in specific regions in the RCP6.0 scenario.

Comparison of different statistical downscaling methods for climate change rainfall projections over the Lake Victoria basin considering CMIP3 and CMIP5

In this study, outputs of three statistical downscaling (SD) methods including the change factor (Delta), simplified (simQP) and advanced (wetQP) quantile-perturbation-based approaches were compared based on daily rainfall series at 9 meteorological stations in the Lake Victoria basin (LVB) in Eastern Africa. The comparison was made considering phase 5 and phase 3 of the Coupled Model Inter-comparison Project, i.e. CMIP5 and CMIP3 respectively. For the CMIP5 (CMIP3) at each station, there were a total of 7 (14) GCMs, 18 (20) daily historical (control) simulations over the period 1961–2000, and 35 (49) daily future projection series of the periods 2050s and 2090s. The ensemble mean of the GCMs' Bias in reproducing rainfall extremes for return periods in the range of 1 to 40 years for the CMIP5 (CMIP3) varied from −19.05% to 3.11% (−65.85% to −4.86%). For the high greenhouse gas scenario rcp8.5 (A2) of the CMIP5 (CMIP3), the ensemble mean of the projected changes over the LVB in the 10-year rainfall intensity quantile obtained from the Delta, simQP, wetQP SD goes up to 5.8, 10 and 22.4% (11.7, 15.9 and 43.6%) in the 2050s and 8, 11.4, and 25.4% (14.2, 23.3 and 40.6%) in the 2090s. Rainfall totals of the main wet (dry) season are generally projected to increase (decrease) in both the 2050s and 2090s. Because the outputs from the three SD methods captured well the pattern of monthly rainfall totals, the difference between the projected changes of seasonal or annual rainfall totals from the Delta, simQP and wetQP was shown to be insignificant. However, the differences in the results from the Delta, simQP and wetQP methods with respect to the projections of rainfall quantiles indicate that the choice of the SD method can be made on a case by case basis in line with the objectives of the climate change impact study, e.g. the Delta does not capture well the changes in rainfall extremes, whereas the wetQP is suitable for both rainfall extremes and rainfall totals at both seasonal and annual time scales. The findings of this study also show the need to consider evaluations of the inter-GCM differences in the LVB as a data scarce region in assessing the discernible impact of climate change on rainfall extremes and/totals for decision making related to water resources management and engineering.

Projected Changes in Wave Conditions in the Baltic Sea by the end of 21st Century and the Corresponding Shoreline Changes

ABSTRACT Suursaar, U.; Tonisson, H; Alari, V.; Raudsepp, U.; Rastas, H., and Anderson, A., 2016. Projected changes in wave conditions in the Baltic Sea by the end of 21st century and the corresponding shoreline changes. In: Vila-Concejo, A.; Bruce, E.; Kennedy, D.M., and McCarroll, R.J. (eds.), Proceedings of the 14th International Coastal Symposium (Sydney, Australia). Journal of Coastal Research, Special Issue, No. 75, pp. 1012 - 1016. Coconut Creek (Florida), ISSN 0749-0208. The aim of the study is to analyse possible future changes in the Baltic Sea wave conditions and to project coastal changes in six differently exposed Estonian coastal sections resulting from changing wind climates. In the open parts of the Baltic Sea, the SWAN model with 3 NM spatial resolution was used for simulation of wave fields in 1966–2100. Regional climate projection EUR-11 assuming the RCP4.5 greenhouse gas scenario was used as wind forcing. In addition, using a site-dependently calibrated fetch-based wave model, a set of ...

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005–2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

Climate Change Dynamics and Imperatives for Food Security in Nigeria

Decadal variability in African rainfall is projected from General Circulation Models (GCMs) to continue under elevated greenhouse gas scenarios. Effects on rain intensity, spatio-temporal variability of growing seasons, flooding, drought, and land-use change impose feedbacks at regional-local scales. Yet, empirical knowledge of associated impacts on crop yield is limited; thus, we examined the imperatives for food security in Nigeria. Bivariate correlation and multiple regression suggests impending drought in the northern region where livestock farming is predominant. Relative contributions of climate independent variables in determining crop yield by backward selection procedures with stepwise approach indexed the impacts of annual climate variability by a parameter computed as annual yield minus mean annual yield divided by the standard deviation. Results show Z-distribution approximately 5 to + 5, when < 3 or > 3 indicate impacts significant at 95% confidence levels. In conclusion, we established the interwoven relationship between climatic change and food security.

Simulated differences in 21st century aridity due to different scenarios of greenhouse gases and aerosols

Aridity, defined as the ratio of precipitation (P) to potential evapotranspiration (PET) over land, is critical to natural ecosystems and agricultural production. Global climate models project global decreases of P/PET (drying) in the 21st century. We examine the uncertainty of aridity projections due to scenarios of greenhouse gases (GHGs) and aerosols with three sets of ensemble simulations from a single climate model, the Community Earth System Model (CESM1). Ensembles consist of two Radiative Concentration Pathways (RCPs) and a scenario with RCP-like GHGs but with aerosol precursor emissions and atmospheric oxidants fixed at the year 2005 level. Under a high GHGs emission scenario (RCP8.5), global land P/PET decreases (drying) by 6.4 ± 0.8 % in 2060–2080 relative to 1985–2005. A GHG mitigation scenario (RCP4.5) would reduce the drying (P/PET decrease) to 3.7 ± 0.6 %. Although future aerosol emissions reduction would increase P, we find that it has little impact on global aridity due to offsetting effects on PET. Regionally, deceasing aerosols can have significant effects and aerosol-induced P/PET changes are due to different factors across different regions. When normalized by global mean temperature response, GHGs decrease global land P/PET by 2.7 ± 0.6 %/°C and surface temperature changes dominate GHG-induced P/PET change.

Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices

Hydropower represents the world’s largest renewable energy source. As a flexible technology, it enhances reliability and security of the electricity system. However, climate change and market liberalization may hinder investment due to the evolution of water runoffs and electricity prices. Both alter expected revenue and bring uncertainty. It increases risk and deters investment. Our research assesses how climate change and market fluctuation affect annual revenue. But this paper focuses on the uncertainty, rather than on forecasting. This transdisciplinary topic is investigated by means of a mixed method, i.e. both quantitative and qualitative. The quantitative approach uses established models in natural sciences and economics. The uncertainty is accounted for by applying various scenarios and various datasets coming from different models. Based on those results, uncertainty is discussed through an analysis discerning three dimensions of uncertainty. Uncertainty analysis requires the assessment of a large panel of models and data sets. It is therefore rarely carried out. The originality of the paper also lies on the combination of quantitative established models with a qualitative analysis. The results surprisingly show that the greenhouse gas scenarios may in fact represent a low source of uncertainty, unlike electricity prices. Like forecasting, the main uncertainties are actually case study related and depend on the investigated variables. It is also shown that the nature of uncertainty evolves. Runoff uncertainty goes from variability, i.e. inherent randomness, to epistemic, i.e. limitation of science. The reverse situation occurs with the electricity price. The implications for scientists and policy makers are discussed.

Can sensitivity to temperature during germination help predict global warming vulnerability?

AbstractSeed germination is vital for persistence in species that rely on seeds for post-disturbance regeneration. It is a high-risk phase and vulnerable to environmental parameters. Here, I assessed temperature sensitivity for germination in Banksia L.f. (Proteaceae) from south-western Australia, screening all 38 endemic obligate seeder species. A bi-directional temperature gradient plate with 49 temperature combinations (constant and fluctuating) between 5 and 40°C was used to profile germination temperature requirements and identify upper and lower temperature thresholds for germination. Using these data the impact of increasing temperatures on germination in these species was modelled under high and low greenhouse gas scenarios for 2050 and 2070. The results suggest that many Banksia species from the region have wide physiological tolerance for high germination temperatures, although a number of common, but geographically restricted species, such as B. praemorsa, B. oreophila and B. quercifolia, have more narrow temperature windows for germination than at least one of the rarer species (B. verticillata). Only B. dryandroides is expected to decline in germination in the future; however, the optimal germination timing for many species is predicted to occur later under climate warming. In conjunction with declining rainfall, this germination delay will place seedlings closer to the summer dry in this seasonal Mediterranean-climate ecosystem and thus they will be more vulnerable to desiccation. The framework developed here can be used to identify vulnerable species for monitoring of early population decline.