Special Report Emission Scenarios Research Articles

Modelling climate change impact on soil loss and erosion vulnerability in a watershed of Shiwalik Himalayas

Understanding the impact of climate change on soil erosion is required to plan effective soil conservation and management practices in hilly and mountainous landscape. Though, few studies have been executed in Indian Himalayas, much less in Shiwalik Himalayas. Thus, keeping this in view, the aim of the study is to estimate the possible impact of projected climate change scenarios on soil loss and erosion vulnerability using Statistical Downscaling Model (SDSM), MarkSim Weather Generator, Agricultural Policy Environmental eXtender (APEX) model and AHP method. The present study downscaled four climate scenarios on the near-future, noted the 2020 s (2011–2040), mid-future, noted 2050 s (2011–2070) and far-future, noted 2080 s (2071–2100/2095) under two Special Report Emission Scenarios (SRES), A2 and B2 with two Representative Concentration Pathway (RCP), 4.5 and 8.5 scenarios. Both SRES and RCP scenarios predicted an increase in temperature and annual rainfall depth during 21st century. Calibrated APEX model was used to simulate future soil loss. The study exposed that the average annual soil loss might increase up to 46.94%, 38.80%, 35.34% and 25.93% in the A2, B2, RCP 4.5 and RCP 8.5 scenarios respectively from the base period (1985–2014). The vulnerability assessment indicates, most of the areas might be under risk from slightly to highly vulnerable and was found that forest land cover could resist this erosion vulnerability to a certain extent. The findings of the study showed a possibility for climate change to increase the rate of soil loss unless conservation strategies or proper land use plans are remunerated. This study offers scientists and policymakers to a detailed understanding of the future impact of rainfall on soil loss and erosion vulnerability in the Shiwalik Himalayas.

Climate change and predicting future temperature in Iraq using CanESM2 and HadCM3 modeling

Climate change and global warming have become a major environmental threat, especially for dry countries. Identifying and assessing future climate change are, therefore, paramount for suitable environmental planning to adapt to and reduce their effects. In this study, changes in the maximum and minimum temperatures in southwest Iraq during the period 2020–2099 were generated using two general circulation models (GCMs), CanESM2 and HadCM3, based on two special report emission scenarios (SRES), A2 and B2, and three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5). Seven meteorological stations representing the study area were selected for model calibration and validation in the statistical downscaling model (SDSM) based on the observed period 1979–2018. The statistical indexes showed a good agreement between the downscaling and observed temperature data for seven meteorological stations in Iraq, where determination coefficient R2 ranged from 0.861 to 0.918 and 0.855 to 0.896 for maximum and minimum temperature, respectively. For the major changes, the results exhibited an increase in mean annual maximum temperature of between 0.48 and 2.5 ℃ (RCP8.5) over the stations by the end of the twenty-first century, while the minimum temperature is expected to rise by 0.22 ℃ (RCP2.6) and 1.76 ℃ (RCP8.5). This increase will affect water resources, because increased surface water evaporation causes water scarcity. HadCM3 shows greater maximum temperature changes than CanESM2 across Iraq.

Future scenarios (2011-2040) of temporal and spatial changes in precipitation in the Paraitinga and Paraibuna watersheds, São Paulo, Brazil

The alteration of global climate regimes due to anthropic action and excessive emission of greenhouse gases has been widely researched because it alters the patterns of climatological normals, generating changes in temperatures and precipitation worldwide. This study aimed to analyze the spatial and temporal variability of precipitation in the Paraitinga and Paraibuna watersheds that together form the Paraibuna Dam, the main one of the Paraiba do Sul river watershed. This dam supplies the São Paulo Metropolitan Region by transporting water to the Cantareira System, the Rio de Janeiro Metropolitan Region by transporting water to the Guandu watershed, and the Paraiba Valley Metropolitan Region, one of the most industrialized in Brazil. To investigate future precipitation trends, past and future climate simulations were used from the HadCM3/Eta model using the SRES (Special Report Emission Scenarios) A1B, and precipitation analysis using Quantis techniques to determine extreme rainfall and drought periods. The results point to an increase in precipitation averages in the region, followed by a greater intensity of extreme rainfall, which may lead to a higher occurrence of natural disasters such as landslides.

Downscaling of Future Temperature and Precipitation Extremes in Addis Ababa under Climate Change

One of the recent advances in climate science research is the development of global general circulation models (GCMs) to simulate changes in climatic elements of the present and future, which helps us to determine consequences earlier and prepare for necessary adaptation measures. However, it is difficult to apply the raw data of GCMs at a local scale, such as the urban scale, without downscaling due to coarse resolution. This study, therefore, statistically downscaled daily maximum temperature, minimum temperature, and precipitation in 30-year intervals from the second generation of the Earth System Model (CanESM2) and Coupled Global Climate Model (CGCM3) under two Representative Concentration Pathways (RCP) Scenarios (RCP4.5 and RCP8.5) and two Special Report Emission Scenarios (SRES), A1B and A2, to examine future changes and their extremes. Two representative meteorological stations (Entoto at high elevation and Addis Ababa at downtown and medium elevation) were selected for model calibration and validation in the Statistical Downscaling Model (SDSM). Twelve core temperature and precipitation indices were selected to assess temperature changes and precipitation extremes. For the largest changes the results showed that the maximum temperature increases were in the range of 0.9 °C (RCP4.5) in 2020 to 2.1 °C (CGCM3A2) in 2080 at Addis Ababa Observatory. The minimum temperature is projected to increase by 0.3 °C (RCP4.5) in 2020 and 1.0 °C in 2080 (CGCM3A1B). While the changes in maximum temperature are lower at Entoto station compared to Addis Ababa Observatory, the highest minimum temperature change is projected at Addis Ababa Observatory, which ranges from 0.25 °C in the 2020s to 1.04 °C in 2080 according to the CGCM3 model. Except for the coldest nights (TNn), the mean temperature and other temperature indices will continue to increase to the end of this century. The highest precipitation change is projected by CGCM3A2 and CanESM2 RCP8.5 at an increase of about 11.8% and 16.62% by 2080. The highest total precipitation increase is 29% (RCP4.5) in winter and 20.9% (RCP8.5) in summer by 2080. There is high interseasonal variability in changes of extreme events. The topographic role will diminish in influence on the air temperature distribution due to the high rate of urbanization. The rise in temperature will exacerbate the urban heat highland effects in warm seasons and an increase in precipitation is expected along with a possible risk of flooding due to a low level of infrastructure development and a high rate of urbanization.

Climate Change Impacts on Nutrient Losses of Two Watersheds in the Great Lakes Region

Non-point sources (NPS) of agricultural chemical pollution are one major reason for the water quality degradation of the Great Lakes, which impacts millions of residents in the states and provinces that are bordering them. Future climate change will further impact water quality in both direct and indirect ways by influencing the hydrological cycle and processes of nutrient transportation and transformation, but studies are still rare. This study focuses on quantifying the impacts of climate change on nutrient (Nitrogen and Phosphorus) losses from the two small watersheds (Walworth watershed and Green Lake watershed) within the Great Lakes region. Analysis focused on changes through this century (comparing the nutrient loss prediction of three future periods from 2015 to 2099 with 30 years for each period against the historical nutrient estimation data from 1985 to 2008). The effects on total phosphorus and nitrate-nitrogen losses due to changes in precipitation quantity, intensity, and frequency, as well as air temperature, are evaluated for the two small watersheds, under three special report emission scenarios (SRES A2, A1B, B1). The newly developed Water Erosion Prediction Project-Water Quality (WEPP-WQ) model is utilized to simulate nutrient losses with downscaled and bias corrected future climate forcing from two General Circulation Models (GFDL, HadCM3). For each watershed, the observed runoff and nutrient loads are used to calibrate and validate the model before the application of the WEPP-WQ model to examine potential impacts from future climate change. Total phosphorus loss is projected to increase by 28% to 89% for the Green Lake watershed and 25% to 108% for the Walworth watershed mainly due to the combined effects of increase of precipitation quantity, extreme storm events in intensity and frequency, and air temperature. Nitrate-nitrogen losses are projected to increase by 1.1% to 38% for the Green Lake watershed and 8% to 95% for the Walworth watershed with the different major influencing factors in each future periods.

Combined and synergistic effects of climate change and urbanization on water quality in the Wolf Bay watershed, southern Alabama

This study investigated potential changes in flow, total suspended solid (TSS) and nutrient (nitrogen and phosphorous) loadings under future climate change, land use/cover (LULC) change and combined change scenarios in the Wolf Bay watershed, southern Alabama, USA. Four Global Circulation Models (GCMs) under three Special Report Emission Scenarios (SRES) of greenhouse gas were used to assess the future climate change (2016–2040). Three projected LULC maps (2030) were employed to reflect different extents of urbanization in future. The individual, combined and synergistic impacts of LULC and climate change on water quantity/quality were analyzed by the Soil and Water Assessment Tool (SWAT). Under the “climate change only” scenario, monthly distribution and projected variation of TSS are expected to follow a pattern similar to streamflow. Nutrients are influenced both by flow and management practices. The variation of Total Nitrogen (TN) and Total Phosphorous (TP) generally follow the flow trend as well. No evident difference in the N:P ratio was projected. Under the “LULC change only” scenario, TN was projected to decrease, mainly due to the shrinkage of croplands. TP will increase in fall and winter. The N:P ratio shows a strong decreasing potential. Under the “combined change” scenario, LULC and climate change effect were considered simultaneously. Results indicate that if future loadings are expected to increase/decrease under any individual scenario, then the combined change will intensify that trend. Conversely, if their effects are in opposite directions, an offsetting effect occurs. Science-based management practices are needed to reduce nutrient loadings to the Bay.

Statistical downscaling of meteorological time series and climatic projections in a watershed in Turkey

In this study, meteorological time series from five meteorological stations in and around a watershed in Turkey were used in the statistical downscaling of global climate model results to be used for future projections. Two general circulation models (GCMs), Canadian Climate Center (CGCM3.1(T63)) and Met Office Hadley Centre (2012) (HadCM3) models, were used with three Special Report Emission Scenarios, A1B, A2, and B2. The statistical downscaling model SDSM was used for the downscaling. The downscaled ensembles were put to validation with GCM predictors against observations using nonparametric statistical tests. The two most important meteorological variables, temperature and precipitation, passed validation statistics, and partial validation was achieved with other time series relevant in hydrological studies, namely, cloudiness, relative humidity, and wind velocity. Heat waves, number of dry days, length of dry and wet spells, and maximum precipitation were derived from the primary time series as annual series. The change in monthly predictor sets used in constructing the multiple regression equations for downscaling was examined over the watershed and over the months in a year. Projections between 1962 and 2100 showed that temperatures and dryness indicators show increasing trends while precipitation, relative humidity, and cloudiness tend to decrease. The spatial changes over the watershed and monthly temporal changes revealed that the western parts of the watershed where water is produced for subsequent downstream use will get drier than the rest and the precipitation distribution over the year will shift. Temperatures showed increasing trends over the whole watershed unparalleled with another period in history. The results emphasize the necessity of mitigation efforts to combat climate change on local and global scales and the introduction of adaptation strategies for the region under study which was shown to be vulnerable to climate change.

Modeling future land use scenarios in South Korea: applying the IPCC special report on emissions scenarios and the SLEUTH model on a local scale.

This study developed three scenarios of future land use/land cover on a local level for the Kyung-An River Basin and its vicinity in South Korea at a 30-m resolution based on the two scenario families of the Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES): A2 and B1, as well as a business-as-usual scenario. The IPCC SRES A2 and B1 were used to define future local development patterns and associated land use change. We quantified the population-driven demand for urban land use for each qualitative storyline and allocated the urban demand in geographic space using the SLEUTH model. The model results demonstrate the possible land use/land cover change scenarios for the years from 2000 to 2070 by examining the broad narrative of each SRES within the context of a local setting, such as the Kyoungan River Basin, constructing narratives of local development shifts and modeling a set of 'best guess' approximations of the future land use conditions in the study area. This study found substantial differences in demands and patterns of land use changes among the scenarios, indicating compact development patterns under the SRES B1 compared to the rapid and dispersed development under the SRES A2.

Infrastructure sufficiency in meeting water demand under climate-induced socio-hydrological transition in the urbanizing Capibaribe River basin – Brazil

Abstract. Water availability for a range of human uses will increasingly be affected by climate change, especially in the arid and semiarid tropics. The main objective of this study is to evaluate the infrastructure sufficiency in meeting water demand under climate-induced socio-hydrological transition in the Capibaribe River basin (CRB). The basin has experienced spatial and sectoral (agriculture-to-urban) reconfiguration of water demands. Human settlements that were once dispersed, relying on intermittent sources of surface water, are now larger and more spatially concentrated, which increases water-scarcity effects. Based on the application of linked hydrologic and water-resources models using precipitation and temperature projections of the IPCC SRES (Special Report: Emissions Scenarios) A1B scenario, a reduction in rainfall of 26.0% translated to streamflow reduction of 60.0%. We used simulations from four members of the HadCM3 (UK Met Office Hadley Centre) perturbed physics ensemble, in which a single model structure is used and perturbations are introduced to the physical parameterization schemes in the model (Chou et al., 2012). We considered that the change of the water availability in the basin in the future scenarios must drive the water management and the development of adaptation strategies that will manage the water demand. Several adaptive responses are considered, including water-loss reductions, wastewater collection and reuse, and rainwater collection cisterns, which together have potential to reduce future water demand by 23.0%. This study demonstrates the vulnerabilities of the infrastructure system during socio-hydrological transition in response to hydroclimatic and demand variabilities in the CRB and also indicates the differential spatial impacts and vulnerability of multiple uses of water to changes over time. The simulations showed that the measures proposed and the water from interbasin transfer project of the São Francisco River had a positive impact over the water supply in the basin, mainly for human use. Industry and irrigation will suffer impact unless other measures are implemented for demand control.

Development of water use scenarios as a tool for adaptation to climate change

Abstract. The project ADAPTACLIMA, promoted by EPAL, the largest Portuguese Water Supply Utility, aims to provide the company with an adaptation strategy in the medium and long term to reduce the vulnerability of its activities to climate change. We used the four scenarios (A1, A2, B1, B2) adopted in the Special Report Emissions Scenarios (SRES) of the IPCC (Intergovernmental Panel on Climate Change) to produce local scenarios of water use. Available population SRES for Portugal were downscaled to the study area using a linear approach. Local land use scenarios were produced using the following steps: (1) characterization of the present land use for each municipality of the study area using Corine Land Cover and adaptation of the CLC classes to those used in the SRES; (2) identification of recent tendencies in land use change for the study area; (3) identification of SRES tendencies for land use change in Europe; and (4) production of local scenarios of land use. Water use scenarios were derived considering both population and land use scenarios as well as scenarios of change in other parameters (technological developments, increases in efficiency, climate changes, or political and behavioural changes). The A2 scenario forecasts an increase in population (+16%) in the study area while the other scenarios show a reduction in the resident population (−6 to 8%). All scenarios, but especially A1, show a reduction in agricultural area and an increase in urban area. Regardless of the scenario, water use will progressively be reduced until 2100. These reductions are mainly due to increased water use efficiency and the reduction of irrigated land. The results accord with several projects modelling water use at regional and global level.

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.

Historic and future extent of wildfires in the Southern Rockies Ecoregion, USA

Wildfires play a formative role in the processes that have created the ecosystems of the Southern Rockies Ecoregion (SRE). The extent of wildfires is influenced mainly by precipitation and temperature, which control biomass growth and fuel moisture. Forecasts of climate change in the SRE show an increase in temperatures, bringing warmer springs with earlier runoff and longer fire seasons. Increasing wildfire extent and intensity would affect human safety, livelihoods, and landscapes. Our summary of historical wildfire records from the national forests of the SRE from 1930 to 2006 revealed an order of magnitude increase in the annual number of fires recorded over the full time period and in the number of large fires since 1970. We developed a model of percent burned area in the SRE for the period 1970–2006 using temperature and precipitation variables (R2=0.51, p=1.7E-05). We applied this model to predict percent burned area using data from two downscaled global circulation models (GCMs), for the Intergovernmental Panel on Climate Change Special Report Emissions Scenarios A2 (projects high increases in temperature) and B1 (projects lower temperature increases), for the time period 2010–2070. The results showed increasing trends in median burned areas for all scenarios and GCM combinations with higher increases for the B1 scenario. The results suggest that precipitation increases could at least partially compensate for the effect of temperature increases on burned area but the strength of this ameliorating effect of precipitation will remain uncertain until the GCMs are further developed.

Dynamic responses of terrestrial ecosystems structure and function to climate change in China

Our understanding of the structure and function of China's terrestrial ecosystems, particularly their responses to transient climate change on timescales of decades to centuries, can be further improved by dynamic vegetation models that include vegetation dynamics as well as biogeochemical processes. Here, the Lund‐Potsdam‐Jena dynamic global vegetation model was calibrated to reasonably capture the general patterns of vegetation distribution across China's terrestrial ecosystems. New parameter values were used for bioclimatic limits, and the model was validated against satellite, in situ, and inventory data for net primary production (NPP), leaf area index, and carbon storage simulations. Dynamic responses of China's terrestrial ecosystems to rising atmospheric CO2 concentration ([CO2]) and climate change in the 20th and 21st centuries were then simulated. Simulations were driven by eight climate scenarios consisting of combinations of two general circulation models and four emission scenarios from Intergovernmental Panel on Climate Change Special Report Emission Scenarios ranging from low emission to fossil intensive emission. We derived possible temporal and spatial change patterns of vegetation distribution, carbon flux, and carbon pools across China. Simulations showed that regional changes in temperature and precipitation would cause substantial vegetation changes in northern, northeastern, and western China. Such vegetation dynamics, and associated mechanisms such as responses of NPP and heterotrophic respiration to rising [CO2] and regional climate change, would lead to corresponding changes in temporal and spatial patterns of carbon flux and carbon pools. As a result, some regional ecosystems could switch from carbon sinks to carbon sources or vice versa by the end of the 21st century. China's terrestrial ecosystems have an average carbon uptake of 0.12 to 0.20 Gt C yr−1 over the period of 1981–2100; however, the rate of increase in carbon sinks is projected to decrease after about 2040, particularly under the fossil intensive emission scenario.

Evaluation of the terrestrial carbon cycle, future plant geography and climate‐carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs)

AbstractThis study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO2, to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO2 content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO2 on plant production are not considered, implying a positive terrestrial climate‐carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra‐tropics in response to future climate. When both counteracting effects of climate and atmospheric CO2 on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO2 from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.

Permafrost Thawing in Circum-Arctic and Highlands under Climatic Change Scenario Projected by Community Climate System Model (CCSM3)

From three-member ensemble projections under the climatic change scenario, the Intergovernmental Panel on Climate Change (IPCC) Special Report Emissions Scenarios (SRES) A1B, regional impacts of global warming on near-surface permafrost are investigated for six analysis regions in the circum-arctic and highlands: Alaska, Alaskan Arctic, Canadian Arctic, Eastern Siberia, Russian Arctic, and Tibetan Plateau, using the Community Climate System Model version 3 (CCSM3). The projected results for the 21st century under the A1B scenario indicated that the ice volume in the deepest model soil layer at about 3 m depth, which had been completely frozen during the 1870s in the historical simulation, begins to melt abruptly at around 2000 in each region. Particularly in Alaska and Eastern Siberia which are more advanced than the other regions in the thawing of permafrost, more than 50% of the ice volume disappears by 2030. From a viewpoint of regional vulnerability, the Alaskan Arctic at around 2020 may suffer the most severe damage as it has the highest thawing rate. Owing to thawing of the frozen soil, subsurface runoff increases by 215.4% and soil moisture decreases by -19.3% in Eastern Siberia for the 1990s to the 2090s.