Regional Climate Change Scenarios Research Articles

Features of climate change and their effects on glacier snow melting in Xinjiang, China

The features of climate change and their effects on glacier snow melting in the past 50years (1961–2010) in Xinjiang were studied. Regional climate data for 49 meteorological stations in the Tianshan Mountains and the northern and southern areas of Xinjiang were collected with the aid of techniques such as climatological statistical diagnosis, regional climate models, remote sensing, and geographic information system. The annual average temperature displayed a rising trend across the Tianshan mountainous area and both areas of Xinjiang. The trend was particularly apparent in winter and autumn with the rate of increase in the annual average minimum temperature being significantly higher than that of the maximum temperature. Rainfall also tended to increase in all three areas over the 50-year period, with the magnitude of change being highest in the mountainous area followed by northern Xinjiang and then southern Xinjiang. As a result of the rising temperatures, there was a negative material balance among the region's glaciers, of which the year 1982/1983 was the key year for the development of Tianshan mountain glacier snow. After this date, glacial ablation intensified with an annual change increase in average temperature of 1°C, leading to a glacier material balance change of about 300mm. To establish rainfall and temperature sequences for three regional climate change scenarios in the 2011–2050 period, we adopted the delta method using actual measurements during the 1961–2000 period against corrected data from rainfall and temperature simulations. All three scenarios indicated that temperatures will continue to increase, that the increase in rainfall may decrease in mountainous regions but will increase in the basin, and that the speed of glacial ablation in Xinjiang will continue to accelerate.

Impact of climate change on waterlogging and salinity distributions in Huai Khamrian subwatershed, NE Thailand

Regional climate models project significant changes in temperature and rainfall over the Greater Mekong Subregion over the twenty-first century. The potential impacts of climate change on areas affected by waterlogging and shallow saline groundwater in Northeast Thailand was investigated using the variable density groundwater model SEAWAT supported with recharge estimates derived from the hydrologic model HELP3. The focal area is the 154 km2 Huai Kamrian subwatershed. Changes in groundwater salinity and waterlogging areas at the middle and end of this century were predicted using the calibrated model. These predictions used the dynamically downscaled PRECIS regional climate change scenarios generated by ECHAM4 GCM A2 and B2 scenarios. Recharge rates are predicted to increase as a result of the higher intensity of rainfall. Shallow watertable areas are projected to increase by approximately 23 % from existing conditions during the middle of the century and up to 25 % by the end of this century. Although the precise rate and timing of climate change impacts are uncertain, all of the scenarios clearly point towards an extension in the area of waterlogging and area affected by shallow saline groundwater areas. Given that areas affected by shallow saline watertables are predicted to expand for both climate change scenarios as well as for the base case, it is concluded that climate change will have a significant impact on the area affected by salinity and waterlogging areas for both climate change scenarios. Evaluation of management options that explore the adaptation to saline environments and to means to reduce salt affected areas are required.

Effects of Climate Change on Invasion Potential Distribution of Lantana camara

Climate change appears to be affecting global patterns of invasive species distribution. Forecasts based on ecological niche modeling suggest that greater impacts can be expected in the future. However, such projections are contingent on assumptions regarding the future climate conditions and invasion potential of a species. This study explores the relationship between climate change and potential distribution of Lantana camara in the National Parks of Jim Corbett and Rajaji (Uttarakhand, India). Using three representative climate change models viz., CSIRO (Commonwealth Scientific and Industrial Research Organization), CCCMA (Canadian Centre for Climate Modeling and Analysis) and HadCM3 (Hadley Centre for Climate Prediction and Research’s General Circulation Model) across the time slices 2020 to 2080 under two regional climate change scenarios A2a and B2a, Lantana camara potential distribution models were derived. The model projections were in consensus that invasion range was likely to expand and infestation would be more severe under the A2a scenario indicating that the species may prefer warmer conditions. Taken together, the modeled results suggest that in the future, the two National Parks may be impacted largely by the gregarious presence of Lantana camara. Predictive models can provide resource managers with a tool for the early detection of invasive species and help circumvent negative ecological impacts resulting in substantial economic savings.

FUTURE EXTREME WAVES AT THE GERMAN BALTIC SEA COAST DERIVED FROM REGIONAL CLIMATE MODEL RUNS

Information about possible changes of extreme wave heights are essential for the future safe design of coastal and flood protection structures likes dykes, flood protection dunes, revetments etc. In this study, scenarios of regional climate change up to 2100 are used for the evaluation of changes of wave conditions. Analyses on calculated significant wave heights derived from extreme value statistics are showing a different signal of change for the selected locations along the German Baltic Sea Coast. The results are showing that extreme wave heights with a return level of 200 years can increase up to +14%. But also a decrease of down to -14% were found compared to actual conditions, depending on the location and climate change scenario applied. At the location of Warnemunde a slight increasing trend for the change of extreme wave heights could be found for 3 of 4 scenario runs with a maximum increase of +7%.

Assessing the hydrological impacts of climate change in the headwater catchment of the Tarim River basin, China

Two statistical downscaling models were used to downscale regional climate change scenarios, on the basis of the outputs of three general circulation models (GCMs) and three emission scenarios. Driven by these climate change scenarios, a distributed macro-scale hydrological model (the Variable Infiltration Capacity (VIC) model) was applied to assess the impact of climate change on hydrological processes in the headwater catchment (HC) of the Tarim River basin, China. The results showed that the HC tends to experience warmer and drier conditions under the combined climate change scenarios. The predictions show a decreasing trend of the runoff in the HC, driven by the combined climate change scenarios. The results predicted an increasing trend for winter runoff however, which was consistent with the forecasts from most previous studies on other locations such as the region of St Lawrence tributaries (Quebec, Canada) and the Willamette River Basin (Oregon, USA). There was an inconsistent intra-annual distribution of the changes in precipitation and runoff in the HC; these inconsistencies may be explained by increasing snowmelt runoff resulting from higher air temperature. It was concluded that uncertainties within different GCM outputs are more significant than emission scenarios in the assessment of the potential impact of climate change.

Regional climate change scenarios and their impacts on water requirements for wheat production in Iran

We simulate the effect of climate change on water requirements of cold season wheat in various climatic zones of Iran. The research considers both observed climate (temperature and precipitation) changes during recent decades (1960-2009) based on instrumental records and projected future changes to 2100 based on the MAGICC/SCENGEN 5.3 compound model. 20 General Circulation models are used based on a single scenario known as P50, which is the average of SRES or emission scenarios. Results indicate that whilst winter precipitation has marginally increased across the country as a whole, a significant decline in mean spring precipitation is recorded between 1960 and 2009. However, considerable variability in trends is measured across various climatic regions of Iran. Mean annual temperature / rainfall changes in the various climate zones of Iran for the period 1960-2009 follow: +0.1 ° C / decade / +0.43 mm / decade in arid regions, -0.1 ° C / decade / -1.7 mm / decade in semi-arid regions, +0.1 ° C / decade / -1.33 mm / decade in Mediterranean / semihumid regions and -0.01 ° C / decade / -0.04 mm / decade in humid / hyper humid regions. Temperature projections to 2100 indicate an overall temperature rise of ca. 4.25 ˚C relative to that for 1961-1990, with increases projected for all climatic regions of Iran. Despite an overall projected mean precipitation increase of 36% for the year 2100, relative to that for 1961-1990, these are insufficient to compensate for temperature increases. Consequently, calculated water deficits during the growing season (autumn to spring) in Iran’s wheat producing areas are expected to increase from 5.2% in 1980 to over 23% by 2050 and 38% by 2100.

Testing ensembles of climate change scenarios for “statistical significance”

Climate impacts and adaptation research increasingly uses ensembles of regional and local climate change scenarios. To do so, the ensembles are examined to evaluate whether they describe a systematic difference between present states (and impacts) and envisaged future states—and such differences are often characterized as being statistically significant. This term “significance” is well defined by statistical terminology as the result of a test of a null hypothesis that is applied to samples of observations that are obtained with a defined sampling strategy. However such a statistical null hypothesis may not be a well-posed problem in the context of the evaluation of climate change scenarios. Therefore, the usage of terms such “statistically significant scenario” may be misunderstood in the general discourse about the certainty of projected climate change. We propose to employ instead a simple descriptive approach for characterizing the information in an ensemble of scenarios. Physical plausibility in the light of theoretical reasoning often adds robustness to the interpretation of climate change scenarios.

Developing higher resolution climate change scenarios for agricultural risk assessment: progress, challenges and prospects

Climate change presents perhaps the greatest economic and environmental challenge we have ever faced. Climate change and its associated impacts, adaptation and vulnerability have become the focus of current policy, business and research. This paper provides invaluable information for those interested in climate change and its impacts. This paper comprehensively reviews the advances made in the development of regional climate change scenarios and their application in agricultural impact, adaptation and vulnerability assessment. Construction of regional climate change scenarios evolved from the application of arbitrary scenarios to the application of scenarios based on general circulation models (GCMs). GCM-based climate change scenarios progressed from equilibrium climate change scenarios to transient climate change scenarios; from the use of direct GCM outputs to the use of downscaled GCM outputs; from the use of single scenarios to the use of probabilistic climate change scenarios; and from the application of mean climate change scenarios to the application of integrated climate change scenarios considering changes in both mean climate and climate variability.

Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, São Francisco and the Paraná River basins

The objective of this study is to assess the climate projections over South America using the Eta-CPTEC regional model driven by four members of an ensemble of the Met Office Hadley Centre Global Coupled climate model HadCM3. The global model ensemble was run over the twenty-first century according to the SRES A1B emissions scenario, but with each member having a different climate sensitivity. The four members selected to drive the Eta-CPTEC model span the sensitivity range in the global model ensemble. The Eta-CPTEC model nested in these lateral boundary conditions was configured with a 40-km grid size and was run over 1961–1990 to represent baseline climate, and 2011–2100 to simulate possible future changes. Results presented here focus on austral summer and winter climate of 2011–2040, 2041–2070 and 2071–2100 periods, for South America and for three major river basins in Brazil. Projections of changes in upper and low-level circulation and the mean sea level pressure (SLP) fields simulate a pattern of weakening of the tropical circulation and strengthening of the subtropical circulation, marked by intensification at the surface of the Chaco Low and the subtropical highs. Strong warming (4–6°C) of continental South America increases the temperature gradient between continental South America and the South Atlantic. This leads to stronger SLP gradients between continent and oceans, and to changes in moisture transport and rainfall. Large rainfall reductions are simulated in Amazonia and Northeast Brazil (reaching up to 40%), and rainfall increases around the northern coast of Peru and Ecuador and in southeastern South America, reaching up to 30% in northern Argentina. All changes are more intense after 2040. The Precipitation–Evaporation (P–E) difference in the A1B downscaled scenario suggest water deficits and river runoff reductions in the eastern Amazon and Sao Francisco Basin, making these regions susceptible to drier conditions and droughts in the future.

The new national climate change documents of Mexico: what do the regional climate change scenarios represent?

This paper presents a review of the methodology applied for generating the regional climate change scenarios utilized in important National Documents of Mexico, such as the Fourth National Communication to the United Nations Framework Convention on Climate Change, the Fourth National Report to the Convention on Biological Diversity and The Economics of Climate Change in Mexico. It is shown that these regional climate change scenarios, which are one of the main inputs to support the assessments presented in these documents, are an example of the erroneous use of statistical downscaling techniques. The arguments presented here imply that the work based on such scenarios should be revised and therefore, these documents are inadequate for supporting national decision- making.

Climate Scenario Development and Applications for Local/Regional Climate Change Impact Assessments: An Overview for the Non-Climate Scientist

Although downscaling methods for deriving local ⁄regional climate change scenarios have been extensively studied, little guidance exists on how to use the downscaled scenarios in applications such as impact assessments. In this second part of a two-part communication, we review for nonclimate scientists a number of practical considerations when utilizing climate change scenarios. The issues discussed are drawn from questions frequently asked by our colleagues on assessment teams and include sources of observational data for scenario evaluation, the advantages of scenario ensembles, adjusting for scenario biases, and the availability of archived downscaled scenarios. Together with Part I, which reviews various downscaling methods, Part II is intended to improve the communication between suppliers and users of local ⁄regional climate change scenarios, with the overall goal of improving the utility of climate impact assessments through a better understanding by all assessment team members of the strengths and limitations of local ⁄regional climate change scenarios.

Modelling soil organic carbon changes on arable land under climate change - a case study analysis of the Kočín farm in Slovakia

We have estimated soil organic carbon and crop yield changes under distinct climate change scenarios for the Kočín farm in Slovakia. Two regional climate change scenarios, i.e. the A2 and B2 SRES emission scenarios, and a reference climate scenario have been included into the bio-physical process model EPIC to simulate the effects on the topsoil organic carbon stocks and crop yields for the period of 2010–2050. In addition, we have used the data from several fields of the Kočín farm including the soil data, crop rotational and management data as well as topographical data. The topsoil organic carbon stocks show a decreasing trend for the period of 2010–2050. Among all crop rotation systems and soil profiles, the losses over the period are 9.0%, 9.5%, and 10.7% for the reference, A2, and B2 climate scenarios, respectively. Increasing temperatures accelerate the decomposition of the soil organic carbon particularly when soils are intensively managed. The soil organic carbon changes are crop-rotation specific, which is partly due to the climate scenarios that affect the crop biomass production differently. This is shown by comparison of the crop yields. We conclude that EPIC is capable to reliably simulate effects of climate change on soil organic carbon and crop yields.

High Temperature Triggers Latent Variation among Individuals: Oviposition Rate and Probability for Outbreaks

BackgroundIt is anticipated that extreme population events, such as extinctions and outbreaks, will become more frequent as a consequence of climate change. To evaluate the increased probability of such events, it is crucial to understand the mechanisms involved. Variation between individuals in their response to climatic factors is an important consideration, especially if microevolution is expected to change the composition of populations.Methodology/Principal FindingsHere we present data of a willow leaf beetle species, showing high variation among individuals in oviposition rate at a high temperature (20°C). It is particularly noteworthy that not all individuals responded to changes in temperature; individuals laying few eggs at 20°C continued to do so when transferred to 12°C, whereas individuals that laid many eggs at 20°C reduced their oviposition and laid the same number of eggs as the others when transferred to 12°C. When transferred back to 20°C most individuals reverted to their original oviposition rate. Thus, high variation among individuals was only observed at the higher temperature. Using a simple population model and based on regional climate change scenarios we show that the probability of outbreaks increases if there is a realistic increase in the number of warm summers. The probability of outbreaks also increased with increasing heritability of the ability to respond to increased temperature.Conclusions/SignificanceIf climate becomes warmer and there is latent variation among individuals in their temperature response, the probability for outbreaks may increase. However, the likelihood for microevolution to play a role may be low. This conclusion is based on the fact that it has been difficult to show that microevolution affect the probability for extinctions. Our results highlight the urge for cautiousness when predicting the future concerning probabilities for extreme population events.

Expected trends of regional climate change for the Carpathian Basin for the 21st century

The Regional Climate Models (RCMs) nested into Global Climate Models (GCMs) are expected to improve the regional climate change scenarios for the European subregions. This paper discusses the RCM experiments for the end of the 21st century using the model Providing REgional Climates for Impact Studies (PRECIS) for the Carpathian Basin. Expected future changes in mean values, distributions and empirical probabilities are analysed for the period 2071–2100 (compared to 1961–1990, as a reference period). Significant warming and annual drying is projected, together with substantial changes in the distribution of daily mean temperature and monthly mean precipitation.

Validation of temperature trends in the ENSEMBLES regional climate model runs driven by ERA40

In the EU-Project ENSEMBLES, a major objective was the development of a weighting system for regional climate models (RCMs) based on the ability of the RCMs to reproduce observed characteristics of important atmospheric variables. Within this context, a suite of state-of-the-art RCMs was employed for the creation of probabilistic future regional climate change scenarios for Europe. Among others, one measure to determine the individual RCM-weights is their ability to reproduce the observed trends in 2 m temperature in the reanalysis (ERA40)-driven experiments for the period 1960-2000. As the reference, we used the new ENSEMBLES observational gridded dataset for Europe (E-OBS). As additional datasets for comparisons, we also used the near-surface temperature datasets from the CRU observations and from the ERA40 and NCEP/NCAR reanalysis. The analysis was performed for the land fraction of 8 different European regions, the so-called PRU- DENCE regions defined within the PRUDENCE project (http://prudence.dmi.dk). Annual and sea- sonal linear trends in near-surface temperature were computed for each ENSEMBLES RCM, the E-OBS dataset, and for the additional datasets mentioned above. In all regions, the computed linear temperature trends based on annual mean temperatures showed smaller values for the RCMs and the NCEP/NCAR reanalysis than for both observational datasets, and in most regions also smaller values than for the ERA40 reanalysis dataset. Depending on the magnitude of the difference in linear trends between the individual RCMs and the E-OBS dataset, skill scores were assigned to each RCM. The resulting skill scores were of similar magnitude (0.7-0.9) for the different models and regions (except for Scandinavia, which had lower skill scores around 0.6-0.8). Spatially aggregated for all of Europe, and combined from annual and seasonal into one value for each RCM, these skill scores were included in the general ENSEMBLES RCM weighting system

Simulated changes in the atmospheric water balance over South Asia in the eight IPCC AR4 coupled climate models

This paper evaluates the performance of eight state-of-art IPCC-AR4 coupled atmosphere-ocean general circulation models in their representation of regional characteristics of atmospheric water balance over South Asia. The results presented here are the regional climate change scenarios of atmospheric water balance components, precipitation, moisture convergence and evaporation (P, C and E) up to the end of the twenty-second century based on IPCC AR4 modelling experiments conducted for (A1B) future greenhouse gas emission scenario. The AOGCMs, despite their relatively coarse resolution, have shown a reasonable skill in depicting the hydrological cycle over the South Asian region. However, considerable biases do exist with reference to the observed atmospheric water balance and also inter-model differences. The monsoon rainfall and atmospheric water balance changes under A1B scenario are discussed in detail. Spatial patterns of rainfall change projections indicate maximum increase over northwest India in most of the models, but changes in the atmospheric water balance are generally widespread over South Asia. While the scenarios presented in this study are indicative of the expected range of rainfall and water balance changes, it must be noted that the quantitative estimates still have large uncertainties associated with them.

Evaluation of three different regional climate change scenarios for the application of a water balance model in a mesoscale catchment in Northeast Germany

Abstract. Future climate changes might have some impacts on catchment hydrology. An assessment of such impacts on e.g. ground water recharge is required to derive adaptation strategies for future water resources management. The main objective of our study was an analysis of three different regional climate change scenarios for a catchment with an area of 2415 km2 located in the Northeastern German lowlands. These data sets consist of the STAR-scenario with a time period 1951–2055, the WettReg-scenario covering the period 1961–2100 and the grid based REMO-scenario for the time span 1950–2100. All three data sets are based on the SRES scenario A1B of the IPCC. In our analysis, we compared the meteorological data for the control period obtained from the regional climate change scenarios with corresponding data measured at meteorological stations in the catchment. The results of this analysis indicated, that there are high differences between the different regional climate change scenarios regarding the temporal dynamics and the amount of precipitation. In addition, we applied a water balance model using input data obtained from the different climate change scenarios and analyzed the impact of these different input data on the model output groundwater recharge. The results of our study indicated, that these regional climate change scenarios due to the uncertainties in the projections of precipitation show only a limited suitability for hydrologic impact analysis used for the establishment of future concrete water management procedures in their present state.

Creating regional climate change scenarios over southern South America for the 2020’s and 2050’s using the pattern scaling technique: validity and limitations

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.

Potential impacts on hydrology and hydropower production under climate warming of the Sierra Nevada

Watersheds of the Cosumnes, American, Bear and Yuba (CABY) Rivers in the Sierra Nevada, California, are managed with a complex network of reservoirs, dams, hydropower plants and water conveyances. While water transfers are based on priorities among competing demands, hydropower generation is licensed by the Federal Energy Regulatory Commission (FERC) and regulated by federal and state laws and multi-party agreements. This paper presents an integrated river basin management (IRBM) model for the CABY region, built to evaluate management and regional climate change scenarios using the Water Evaluation and Planning (WEAP) system. We simulated potential impacts of climate warming on hydrology and hydropower production by imposing a fixed increase of temperature (+2, 4 and 6°C) over weekly historical (1981–2000) climate, with all other climate variables unchanged. Results demonstrate that climate warming will reduce hydropower generation if operational rules remain unchanged, making the case for climate change induced hydrological change as a foreseeable future condition to be included in the FERC licensing process. IRBM tools such as the CABY model presented here are useful in deliberating the same.

Inter-specific competition in mixed forests of Douglas-fir (Pseudotsuga menziesii) and common beech (Fagus sylvatica) under climate change — a model-based analysis

• Mixed forests feature competitive interactions of the contributing species which influence their response to environmental change. • We analyzed climate change effects on the inter-specific competition in a managed Douglasfir/beech mixed forest. • Therefore, we initialised the process-based forest model 4C with published fine root biomass distributions of Douglas-fir/beech stands and a stand composition originating from yield tables to simulate forest growth under regional climate change scenarios for a Dutch and a German site. • The number of days when the tree water demand exceeded the soil water supply was higher for Douglas-fir than for beech. After 45 simulation years the proportion of basal area covered by beech increased from one to seven percent. Beech’s competitive strength is mainly explained by the fine root biomass distributions and is highest under the historic climate and the driest climate change scenarios. Higher net primary production (NPP) under warmer/wetter climate but decreased NPP under warmer/drier conditions confirms Douglas-fir’s high sensitivity to limited water supply. • Simulated climate change does not substantially alter the interaction of the two species but the drought-stressed trees are more susceptible to insects or pathogens. The concept of complementary water use highlights the importance of mixed forest for climate change adaptation.