Special Report On Emission Scenarios A2 Research Articles

Climate-related economic losses in Taiwan

The objective of this study is to quantify the relationship between CO2 emissions and economic losses under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) A2, A1B and B1. Previous trend is used to formulate predictions with regard to future climate-related hazards and quantify the expected economic consequences for Taiwan. We establish an equation with which to forecast economic losses related to agricultural damage, death toll, and medical expenditures. The results are as follows: 1) according to SRES A2, A1B and B1 projections, cumulative total economic losses of unit CO2 emission between 2013 and 2100 are US$ 75-261/tCO2, US$ 76-215/tCO2, and US$ 75-169/tCO2, respectively; 2) total economic losses related to natural disaster exhibits a strong correlation with GDP between 1991 and 2012, compares to the period from 1971 to 1990 (this is not including the medical expenditure losses in the total economic losses); 3) according to SRES's A1B scenario, predicted total economic losses related to natural disasters are expected to be strongly correlated with GDP between 2013 and 2100.

Assessing the impacts of climate change and tillage practices on stream flow, crop and sediment yields from the Mississippi River Basin

This study evaluated climate change impacts on stream flow, crop and sediment yields from three different tillage systems (conventional, reduced 1–close to conservation, and reduced 2–close to no-till), in the Big Sunflower River Watershed (BSRW) in Mississippi. The Soil and Water Assessment Tool (SWAT) model was applied to the BSRW using observed stream flow and crop yields data. The model was calibrated and validated successfully using monthly stream flow data (2001–2011).The model performances showed the regression coefficient (R2) from 0.72 to 0.82 and Nash–Sutcliffe efficiency index (NSE) from 0.70 to 0.81 for streamflow; R2 from 0.40 to 0.50 and NSE from 0.72 to 0.86 for corn yields; and R2 from 0.43 to 0.59 and NSE from 0.48 to 0.57 for soybeans yields. The Long Ashton Research Station Weather Generator (LARS-WG), was used to generate future climate scenarios. The SRES (Special Report on Emissions Scenarios) A1B, A2, and B1 climate change scenarios of the Intergovernmental Panel on Climate Change (IPCC) were simulated for the mid (2046–2065) and late (2080–2099) century. Model outputs showed slight differences among tillage practices for corn and soybean yields. However, model simulated sediment yield results indicated a large difference among the tillage practices from the corn and soybean crop fields. The simulated future average maximum temperature showed as high as 4.8°C increase in the BSRW. Monthly precipitation patterns will remain un-changed based on simulated future climate scenarios except for an increase in the frequency of extreme rainfall events occurring in the watershed. On average, the effect of climate change and tillage practice together did not show notable changes to the future crop yields. The reduced tillage 2 practices showed the highest responses of erosion control to climate change followed by the reduced tillage 1 and conventional tillage in this study.

Climate change scenarios generated by using GCM outputs and statistical downscaling in an arid region

Two statistical downscaling models, the non-homogeneous hidden Markov model (NHMM) and the Statistical Down–Scaling Model (SDSM) were used to generate future scenarios of both mean and extremes in the Tarim River basin,which were based on nine combined scenarios including three general circulation models (GCMs) (CSIRO30, ECHAM5,and GFDL21) predictor sets and three special report on emission scenarios (SRES) (SRES A1B, SRES A2, and SRESB1). Local climate change scenarios generated from statistical downscaling models was also compared with thatprojected by raw GCMs outputs. The results showed that the magnitude of changes for annual precipitation projected byraw GCMs outputs was greater than that generated by using statistical downscaling model. The difference betweenchanges of annual maximum air temperature projected by statistical downscaling model and raw GCMs outputs was notas significant as that for annual precipitation. In total, the magnitude of these increasing trends projected by bothstatistical downscaling models and raw GCMs outputs was the greatest under SRES A2 scenario and the smallest underB1 scenario, with A1B scenario in–between. Generally, the magnitude of these increasing trends in the period of 2081 to2100 was greater than that in the period of 2046 to 2065. The magnitude of standard deviation changes for dailyprecipitation projected by raw GCMs outputs was greater than that generated by statistical downscaling model undermost of combined scenarios in both periods.

Climate change scenarios and its impact on water resources of Langtang Khola Basin, Nepal

Abstract. General Circulation Models (GCMs) successfully simulate future climate variability and climate change on a global scale; however, poor spatial resolution constrains their application for impact studies at a regional or a local level. The dynamically downscaled precipitation and temperature data were used for the future climate scenarios prediction for the period 2000–2050s, under the Special Report on Emissions Scenarios (SRES) A2 and A1B scenarios. In addition, rating equation was developed from measured discharge and gauge (stage) height data. The generated precipitation and temperature data from downscale and rating equation was used to run the HBV-Light 3.0 conceptual rainfall–runoff model for the calibration and validation of the model, gauge height was taken in the reference period (1988–2009). In the HBV-Light 3.0, a GAP optimization approach was used to calibrate the observed streamflow. From the precipitation scenarios with SRES A2 and A1B emissions at Kyanging, an increase of precipitation during summer and spring and a decrease during winter and autumn seasons was shown. The model projected annual precipitation for the 2050s of both the A2 and A1B scenarios are 716.4 mm and 703.6 mm, respectively. Such precipitation projections indicate the future increase of precipitation in all seasons except the summer. By the end of the 2050s simulation projects an increase maximum (minimum) discharge of 37.8 m3/s (13.9 m3/s) for A1B scenario and 36.2 m3/s (14.3 m3/s) for A2 scenario. A maximum projected discharge will increase for all seasons except for spring, whereas the minimum will decrease in summer.

Projection of future world water resources under SRES scenarios: an integrated assessment

Changes in water resources availability, as affected by global climate warming, together with changes in water withdrawal, could influence the world water resources stress situation. In this study, we investigate how the world water resources situation will likely change under the Special Report on Emissions Scenarios (SRES) by integrating water withdrawal projections. First, the potential changes in water resources availability are investigated by a multi-model analysis of the ensemble outputs of six general circulation models (GCMs) from organizations worldwide. The analysis suggests that, while climate warming might increase water resources availability to human society, there is a large discrepancy in the size of the water resource depending on the GCM used. Secondly, the changes in water-stressed basins and the number of people living in them are evaluated by two indices at the basin scale. The numbers were projected to increase in the future and possibly to be doubled in the 2050s for the three SRES scenarios A1b, A2 and B1. Finally, the relative impacts of population growth, water use change and climate warming on world water resources are investigated using the global highly water-stressed population as an overall indicator. The results suggest that population and socio-economic development are the major drivers of growing world water resources stress. Even though water availability was projected to increase under different warming scenarios, the reduction of world water stress is very limited. The principal alternative to sustainable governance of world water resources is to improve water-use efficiency globally by effectively reducing net water withdrawal.Editor Z.W. Kundzewicz; Associate editor D. Gerten

Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071–2099) and the base period (1961–1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and hydrological simulations and development of agricultural and hydrological models.

Assessment of future precipitation indices in the Shikoku region using a statistical downscaling model

In this study, we used the statistical downscaling model (SDSM) to estimate mean and extreme precipitation indices under present and future climate conditions for Shikoku, Japan. Specifically, we considered the following mean and extreme precipitation indices: mean daily precipitation, R10 (number of days with precipitation >10 mm/day), R5d (annual maximum precipitation accumulated over 5 days), maximum dry-spell length (MaDSL), and maximum wet-spell length (MaWSL). Initially, we calibrated the SDSM model using the National Center for environmental prediction (NCEP) reanalysis dataset and daily time series of precipitation for ten locations in Shikoku which were acquired from the surface weather observation point dataset. Subsequently, we used the validated SDSM, using data from NCEP and outputs form general circulation models (GCM), to predict future precipitation indices. Specifically, the HadCM3 GCM was run under the special report on emissions scenarios (SRES) A2 and B2 scenarios, and the CGCM3 GCM was run under the SRES A2 and A1B scenarios. The results showed that: (1) the SDSM can reasonably be used to simulate mean and extreme precipitation indices in the Shikoku region; (2) the values of annual R10 were predicated to decrease in the future in northern Shikoku under all climate scenarios; conversely, the values of annual R10 were predicted to increase in the future in the range of 0–15 % in southern and western Shikoku. The values of annual MaDSL were predicted to increase in northern Shikoku, and the values of annual MaWSL were predicted to decrease in northeastern Shikoku; (3) the spatial variation of precipitation indices indicated the potential for an increased occurrence of drought across northeastern Shikoku and an increased occurrence of flood events in the southwestern part of Shikoku, especially under the A2 and A1B scenarios; (4) characteristics of future precipitation may differ between the northern and southern sides of the Shikoku Mountains. Regional variations in extreme precipitation indices were not notably evident in the B2 scenario compared to the other scenarios.

Analysis of Future Climate Scenarios over Central Uganda Cattle Corridor

The study employed a Regional Climate Model (RCM), Providing Regional Climates for Impact Studies (PRECIS), to examine the future climate scenarios over the central Uganda cattle corridor districts of Nakaseke and Nakasongola in the near future (2021-2050) and mid-century (2051-2080). The study was guided by two questions: what are the projected temperature and rainfall values for the central Uganda cattle corridor in relation to IPCC Special Report on Emission Scenarios (SRES) A2 and A1B Scenarios for the same periods; how do they compare with the new set of scenarios known as Representative Concentration Pathways (RCPs) in the same area for the same period? The scenarios were obtained using PRECIS software and delta methods using R software according to the AGMIP protocols for SRES and RCP; respectively. Results show both SRES A2 and A1B projecting temperature increases in average monthly, seasonal as well as annual for both near future and mid centuryperiods with A2 showing a mean annual temperature increase of 2.5 to 4.4°C in the near future and 4.5 to 6.0°C in the mid century relative to the 1981-2010 average compared to A1B which shows annual temperature increase of 0.7 -1.7°C in the near future and 1.7-3.5°C in the far future. The same trend is observed for RCP 4.5 and RCP 8.5 but the increments are lower for the RCPs compared to the SRES. Projections for rainfall show a slight increase in annual rainfall in both SRES and RCPs. However more rainfall is projected for the second rainfall season of September to November compared to the usual known season of March to May (MAM). The projections also show a shift in rainfall with the usual dry season of December to February (DJF) now becoming wetter than the 1980-2010 average. This shift is consistent in all the scenarios and has also been observed in other studies done in the region. From the results farmers should be advised to take advantage of the projected increases in rainfall especially.

On the use of regional climate models: Implications of climate change for viticulture in Serbia

Climate projections obtained from the coupled regional climate model EBU–POM (Eta Belgrade University – Princeton Ocean Model) driven by the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES), showed that the vineyard regions of Serbia tend to become warmer and dryer toward the end of 21st century. To evaluate how Serbian viticulture could be affected by a projected climate regime, several climatic variables and agro-climatic indices describing the suitability of a particular area for grapevine production were calculated, after a statistical bias correction was applied to the daily temperature and precipitation data from EBU–POM outputs. Comparison between climatic variables and agro-climatic indices for the reference period 1961–1990 and predicted values for the 2001–2030 period (under the SRES A1B scenario) and the 2071–2100 period (under the SRES A2 scenario) was made for 18 climatological stations placed mostly within, but also outside traditional viticultural regions. According to the obtained change trends it is likely that no significant disturbances in Serbian viticulture will occur over the next few decades, but considerable changes are expected by the end of the 21st century. Warmer and prolonged growing season with greater heat accumulation and longer frost-free period with decline in frost frequency would likely affect the yield and ripening potential of grapes and induce shifts in varietal suitability and wine styles. Projected changes may bring on the need for additional vineyard irrigation, but also open up the possibility that marginal and elevated areas, previously too cool for cultivation of grapevines, become climatically suited for viticulture.

Future impacts of climate change on forest fire danger in northeastern China

Climate warming has a rapid and far-reaching impact on forest fire management in the boreal forests of China. Regional climate model outputs and the Canadian Forest Fire Weather Index (FWI) System were used to analyze changes to fire danger and the fire season for future periods under IPCC Special Report on Emission Scenarios (SRES) A2 and B2, and the data will guide future fire management planning. We used regional climate in China (1961–1990) as our validation data, and the period (1991–2100) was modeled under SRES A2 and B2 through the weather simulated by the regional climate model system (PRECIS). Meteorological data and fire danger were interpolated to 1 km2 by using ANUSPLIN software. The average FWI value for future spring fire seasons under Scenarios A2 and B2 shows an increase over most of the region. Compared with the baseline, FWI averages of spring fire season will increase by −0.40, 0.26 and 1.32 under Scenario A2, and increase by 0.60, 1.54 and 2.56 under Scenario B2 in 2020s, 2050s and 2080s, respectively. FWI averages of autumn fire season also show an increase over most of the region. FWI values increase more for Scenario B2 than for Scenario A2 in the same periods, particularly during the 2050s and 2080s. Average future FWI values will increase under both scenarios for autumn fire season. The potential burned areas are expected to increase by 10% and 18% in spring for 2080s under Scenario A2 and B2, respectively. Fire season will be prolonged by 21 and 26 days under Scenarios A2 and B2 in 2080s respectively.

Changes in Spring Snowpack for Selected Basins in the United States for Different Climate-Change Scenarios

Abstract Spring snowpack is an important water resource in many river basins in the United States in areas where snowmelt comprises a large part of the annual runoff. Increasing temperatures will likely reduce snowpacks in the future, resulting in more winter runoff and less available water during the summer low-flow season. As part of the National Climate Change Modeling Project by the U.S. Geological Survey, distributed watershed-model output was analyzed to characterize areal extent and water-equivalent volumes of spring snowpack for a warming climate. The output from seven selected watershed models from the mountainous western United States and one model from coastal Maine in the northeastern United States shows a future of declining spring snowpack. Snow-cover area (SCA) and snow-water equivalent (SWE) were used to compare the spring snowpack for current conditions (2006) with three time periods in the future (2030, 2060, and 2090) using three Intergovernmental Panel on Climate Change (IPCC) emission scenarios published in the 2007 Special Report on Emission Scenarios (SRES): A2, B1, and A1B. Distributed SWE and SCA values were sorted into elevation zones in each basin. The change in spring snowpack over time was greater than the change among different emission scenarios, suggesting that, even for a globally reduced carbon emission scenario, large decreases in SWE are likely to occur. The SRES A2 scenario resulted in the greatest decrease in SWE for six of the basins, and the SRES B1 and A1B scenarios resulted in the greatest decrease in one basin each.

Sensitivity of the southern annular mode to greenhouse gas emission scenarios

The leading mode of southern hemisphere (SH) climatic variability, the southern annular mode (SAM), has recently seen a shift towards its positive phase due to stratospheric ozone depletion and increasing greenhouse gas (GHG) concentrations. Here we examine how sensitive the SAM (defined as the leading empirical orthogonal function of SH sea level pressure anomalies) is to future GHG concentrations. We determine its likely evolution for three intergovernmental panel on climate change (IPCC) special report on emission scenarios (SRES) for austral summer and winter, using a multi-model ensemble of IPCC fourth assessment report models which resolve stratospheric ozone recovery. During the period of summer ozone recovery (2000–2050), the SAM index exhibits weakly negative, statistically insignificant trends due to stratospheric ozone recovery which offsets the positive forcing imposed by increasing GHG concentrations. Thereafter, positive SAM index trends occur with magnitudes that show sensitivity to the SRES scenario utilised, and thus future GHG emissions. Trends are determined to be strongest for SRES A2, followed by A1B and B1, respectively. The winter SAM maintains a similar dependency upon GHG as summer, but over the entire twenty-first century and to a greater extent. We also examine the influence of ozone recovery by comparing results to models that exclude stratospheric ozone recovery. Projections are shown to be statistically different from the aforementioned results, highlighting the importance of ozone recovery in governing SAM-evolution. We therefore demonstrate that the future SAM will depend both upon GHG emissions and stratospheric ozone recovery.

Estimation of changes in characteristics of the climate and carbon cycle in the 21st century accounting for the uncertainty of terrestrial biota parameter values

ensemble simulations with the A.M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences (IAP RAS) climate model (CM) for the 21st century are analyzed taking into account anthropogenic forcings in accordance with the Special Report on Emission Scenarios (SRES) A2, A1B, and B1, whereas agricultural land areas were assumed to change in accordance with the Land Use Harmonization project scenarios. Different realizations within these ensemble experiments were constructed by varying two governing parameters of the terrestrial carbon cycle. The ensemble simulations were analyzed with the use of Bayesian statistics, which makes it possible to suppress the influence of unrealistic members of these experiments on their results. It is established that, for global values of the main characteristics of the terrestrial carbon cycle, the SRES scenarios used do not differ statistically from each other, so within the framework of the model, the primary productivity of terrestrial vegetation will increase in the 21st century from 74 ± 1 to 102 ± 13 PgC yr−1 and the carbon storage in terrestrial vegetation will increase from 511 ± 8 to 611 ± 8 PgC (here and below, we indicate the mean ± standard deviations). The mutual compensation of changes in the soil carbon stock in different regions will make global changes in the soil carbon storage in the 21st century statistically insignificant. The global CO2 uptake by terrestrial ecosystems will increase in the first half of the 21st century, whereupon it will decrease. The uncertainty interval of this variable in the middle (end) of the 21st century will be from 1.3 to 3.4 PgC yr−1 (from 0.3 to 3.1 PgC yr−1). In most regions, an increase in the net productivity of terrestrial vegetation (especially outside the tropics), the accumulation of carbon in this vegetation, and changes in the amount of soil carbon stock (with the total carbon accumulation in soils of the tropics and subtropics and the regions of both accumulation and loss of soil carbon at higher latitudes) will be robust within the ensemble in the 21st century, as will the CO2 uptake from the atmosphere only by terrestrial ecosystems located at extratropical latitudes of Eurasia, first and foremost by the Siberian taiga. However, substantial differences in anthropogenic emissions between the SRES scenarios in the 21st century lead to statistically significant differences between these scenarios in the carbon dioxide uptake by the ocean, the carbon dioxide content in the atmosphere, and changes in the surface air temperature. In particular, according to the SRES A2 (A1B, B1) scenario, in 2071–2100 the carbon flux from the atmosphere to the ocean will be 10.6 ± 0.6 PgC yr−1 (8.3 ± 0.5, 5.6 ± 0.3 PgC yr−1), and the carbon dioxide concentration in the atmosphere will reach 773 ± 28 ppmv (662 ± 24, 534 ± 16 ppmv) by 2100. The annual mean warming in 2071–2100 relatively to 1961–1990 will be 3.19 ± 0.09 K (2.52 ± 0.08, 1.84 ± 0.06 K).

Probabilistic evaluation of climate change impacts on paddy rice productivity in Japan

Projecting the impacts of climate change includes various uncertainties from physical, biophysical, and socioeconomic processes. Providing a more comprehensive impact projection that better represents the uncertainties is a priority research issue. We used an ensemble-based projection approach that accounts for the uncertainties in climate projections associated with general circulation models (GCMs) and biophysical and empirical parameter values in a crop model. We applied the approach to address the paddy rice yield change in Japan in the 2050s (2046–2065) and 2090s (2081–2100) relative to the 1990s (1981–2000). Seventeen climate projections, nine (eight) climate projections performed by seven (six) GCMs conditional on the Special Report on Emission Scenarios (SRES) A1B (A2), were included in this projection. In addition, 50 sets of biophysical and empirical parameter values of a large-scale process-based crop model for irrigated paddy rice were included to represent the uncertainties of crop parameter values. The planting windows, cultivation practices, and crop cultivars in the future were assumed to be the same as the level in the baseline period (1990s). The resulting probability density functions conditioned on SRES A1B and A2 indicate projected median yield changes of + 17.2% and + 26.9% in Hokkaido, the northern part of Japan, in the 2050s and 2090s with 90% probability intervals of (− 5.2%, + 40.3%) and (+ 6.3%, + 51.2%), relative to the 1990s mean yield, respectively. The corresponding values in Aichi, on the Pacific side of Western Japan, are 2.2% and − 0.8%, with 90% probability intervals of (− 15.0%, + 14.9%) and (− 33.4%, + 17.9%), respectively. We also provided geographical maps of the probability that the future 20-year mean yield will decrease and that the future standard deviation of yield for 20 years will increase. Finally, we investigated the relative contributions of the climate projection and crop parameter values to the uncertainty in projecting yield change in the 2090s. The choice of GCM yielded a relatively larger spread of projected yield changes than that of the other factors. The choice of crop parameter values could be more important than that of GCM in a specific prefecture.

Effects of land cover change on the tropical circulation in a GCM

Multivariate statistics are used to investigate sensitivity of the tropical atmospheric circulation to scenario-based global land cover change (LCC), with the largest changes occurring in the tropics. Three simulations performed with the fully coupled Parallel Climate Model (PCM) are compared: (1) a present day control run; (2) a simulation with present day land cover and Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 greenhouse gas (GHG) projections; and (3) a simulation with SRES A2 land cover and GHG projections. Dimensionality of PCM data is reduced by projection onto a priori specified eigenvectors, consisting of Rossby and Kelvin waves produced by a linearized, reduced gravity model of the tropical circulation. A Hotelling T 2 test is performed on projection amplitudes. Effects of LCC evaluated by this method are limited to diabatic heating. A statistically significant and recurrent signal is detected for 33% of all tests performed for various combinations of parameters. Taking into account uncertainties and limitations of the present methodology, this signal can be interpreted as a Rossby wave response to prescribed LCC. The Rossby waves are shallow, large-scale motions, trapped at the equator and most pronounced in boreal summer. Differences in mass and flow fields indicate a shift of the tropical Walker circulation patterns with an anomalous subsidence over tropical South America.

A new method to estimate air-quality levels using a synoptic-regression approach. Part II: Future O 3 concentrations

Using the synoptic-regression based approach developed in Part I of this research, this study estimates future maximum 8 hourly mean O 3 levels (m8hO 3) using three future SRES (Special Report on Emission) scenarios for a rural background area situated in The Netherlands. The statistical downscaling tool was used to downscale the Atmospheric–Ocean Coupled General Circulation Model (AOGCM) ECHAM5-MPI/OM for the present-day 20 Century (20C) control run (1991–2000) and the future SRES scenarios A2, A1B and B1 for two periods (2051–2060 and 2091–2100). First, the statistical downscaling tool is evaluated in terms of downscaled m8hO 3 levels for the present-day climate, using a long record of observed m8hO 3 concentrations. It was found that a bias correction is needed and this bias correction is then further used to estimate future m8hO 3 concentrations. Under the various SRES scenarios, the overall mean m8hO 3 increases with 2.5–6.5 and 6.1–10.9 μg m −3, for the 2051–2060 and 2091–2100 period respectively, which is about 20% of the present-day 10-year average. This effect is enhanced when considering the summer season only, with a range of increase between the different future scenarios of 5.4–12.5 μg m −3 and 13.4–26 μg m −3 (for 2051–2060 and 2091–2100 respectively) against a present-day summer average of 73.5 μg m −3. An increase in maximum temperature and shortwave radiation, associated with a decrease in cloud cover under the various future scenarios are the main drivers of ozone increase. A comparison with August 2003 shows the physical plausibility of our results and reflects that the extreme summer of 2003 might show a close resemblance to future European summers in terms of m8hO 3 and meteorological characteristics.

SIMULATION AND ANALYSIS ON FUTURE CARBON BALANCE OF THREE DECIDUOUS FORESTS IN BEIJING MOUNTAIN AREA, WARM TEMPERATE ZONE OF CHINA

Aims Climate change is expected to cause changes of carbon cycling in forest ecosystems, and prediction research suggests there is dramatic spatial heterogeneity and uncertainty in responses of carbon balance of forest ecosystems to climate change. The goals of our research were to predict and analyze impacts of climate change on the carbon cycling of warm temperate forests in Beijing mountain area in the next 100 years and to understand the heterogeneity and uncertainty on the ecosystem scale with LPJ-GUESS model. Methods The ecosystem model was used to learn how forest ecosystem productivity and carbon bal-ance change in a long-term time scale and to learn about differences of carbon balance among various ecosystems by comparing ecosystem components of carbon balance. The dynamic vegetation model (LPJ-GUESS), used for the first time in China and driven by A2 and B2 greenhouse gas emission sce-narios of the Special Report on Emissions Scenarios (SRES) of IPCC, projected climate change impacts on carbon balance for three typical warm temperate forest ecosystems (oak, birch and Chinese pine forests) in the Dongling Mountain area of Beijing, China. Important findings Net ecosystem primary productivity (NPP) and heterotrophic respiration (Rh) will increase in the three forests, and the A2 scenario was associated with larger changes in NPP and Rh than the B2 scenario. Because of differences in species composition among the forests, increases in NPP and Rh were different and changes in net ecosystem exchange (NEE) were different among the forests: oakforest switched from a sink to a small source of carbon, birch forest remained as a smaller sink of carbon, and Chinese pine forest became a larger carbon sink over the next 100 years. Also, carbon biomass will generally increase in the forests by 2100. Comparing SRES A2 with B2, there was larger carbon storage in the relative lower emission scenario (B2). Projected differences in carbon balance among these forests in the same area were more dependent on species composition than climate factors (A2 and B2 scenarios) under future climate change.

Assessment of Climate Change Impact on the Inflow and Outflow of Two Agricultural Reservoirs in Korea

This study assessed the impact of potential future climate change on the inflow to an agricultural reservoir and its downstream streamflow from reservoir operation for paddy irrigation using SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. For a 366.5 km2 watershed that includes two agricultural reservoirs located in the upper middle part of South Korea, the SLURP model was calibrated using six years (1998-2003) of daily streamflow records and validated using three years (2004-2006) of streamflow data, before the future analysis. The CCCma CGCM2 data of the SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (Intergovernmental Panel on Climate Change) was adopted for the future climate condition, and then the change factor method was used to downscale the future weather data through bias-correction. In addition, the future land covers were predicted with a modified CA (cellular automata)-Markov technique using a time series of Landsat land cover data, and the future vegetation information was predicted by linear regression between the monthly NDVI (normalized difference vegetation index) from NOAA AVHRR (advanced very high resolution radiometer) images and the monthly mean temperature data. The results for the future impact on reservoir storage showed that it would not have recovered to 100% by the end of the year (December) because of a decrease in precipitation and an increase in evaporation from July to September. Therefore, this reduced reservoir storage could bring a spring drought that causes an insufficient guarantee of water for rice paddy transplanting at the end of May. The future impact on the monthly streamflow of the watershed showed that the future streamflow for the three months of April, May, and June would increase because of a future increase in precipitation, and that the future streamflow for the next three months (July, August, and September) would decrease because of a future decrease in precipitation and increase in temperature. Considering the future decrease in the summer and autumn streamflows, the reservoir operation has to be more conservative when supplying water for paddy irrigation during this period and in the decision making process for reservoir releases during storm events.

Mesh Climate Change Data of Japan Ver.2 for Climate Change Impact Assessments Under IPCC SRES A1B and A2

The Intergovernmental Panel on Climate Change (IPCC) published the Fourth Assessment Report (AR4) in 2007 and stated that recent climate change and variation are induced by increases in the atmospheric greenhouse gases (GHG) concentration due to anthropogenic activities. The report includes the results of impact assessments on a wide range of sectors. These assessments have been conducted based on future climate projections, which refer to aspects of the future climate evaluated by Atmosphere-Ocean Coupled General Circulation Models (CGCMs). The projection data used in the AR4 are archived under the Program for Climate Model Diagnosis and Intercomparison (PCMDI) promoted by the U.S. Department of Energy. We interpolated the projection data around Japan and constructed a dataset entitled the “Mesh climate change data of Japan Ver. 2” for the climate change impact study. Nine projections performed by seven models under the A1B and A2 of the Special Report on Emissions Scenarios (SRES) were implemented for the dataset. They consist of mesh data with a size of 7.5′ in longitude and 5.0′ in latitude, i.e. approximately 10×10 km (45″ in longitude and 30″ in latitude, approximately 1×1 km, for one high-resolution model). The dataset includes five climatic elements, i.e. the daily mean, maximum, and minimum surface air temperatures, daily total precipitation, and daily accumulated shortwave radiation for three periods, 1981-2000, 2046-2065, and 2081-2100. This article describes the details concerning the construction and characteristics of the data.

U.S. Ozone Air Quality under Changing Climate and Anthropogenic Emissions

We examined future ozone (O3) air quality in the United States (U.S.) under changing climate and anthropogenic emissions worldwide by performing global climate-chemistry simulations, utilizing various combinations of present (1990s) and future (Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 2050s) climates, and present and future (2050s; IPCC SRES A2 and B1) anthropogenic emissions. The A2 climate scenario is employed here because it lies at the upper extreme of projected climate change for the 21st century. To examine the sensitivity of U.S. O3 to regional emissions increases (decreases), the IPCC SRES A2 and B1 scenarios, which have overall higher and lower O3-precursor emissions for the U.S., respectively, have been chosen. We find that climate change, by itself, significantly worsens the severity and frequency of high-O3 events ("episodes") over most locations in the U.S., with relatively small changes in average O3 air quality. These high-O3 increases due to climate change alone will erode moderately the gains made under a U.S. emissions reduction scenario (e.g., B1). The effect of climate change on high- and average-O3 increases with anthropogenic emissions. Insofar as average O3 air quality is concerned, changes in U.S. anthropogenic emissions will play the most important role in attaining (or not) near-term U.S. O3 air quality standards. However, policy makers must plan appropriately for O3 background increases due to projected increases in global CH4 abundance and non-U.S. anthropogenic emissions, as well as potential local enhancements that they could cause. These findings provide strong incentives for more-than-planned emissions reductions at locations that are currently O3-nonattainment.