IPCC A1B Emission Scenario Research Articles

Using the hydrodynamic model DYRESM based on results of a regional climate model to estimate water temperature changes at Lake Ammersee

In order to enhance our research work on the impact of climate change on bodies of water, it is necessary to establish coupled hydrodynamic and ecosystem models that take into account simulated data of climate models. We assume that the coupled hydrodynamic models, along with the regional climate models, can serve to gain further knowledge on the future climatic impact upon lake ecosystems. For this purpose we use the one-dimensional hydrodynamic model DYRESM and the regional climate model REMO and apply them to the pre-Alpine, 83-m deep, currently dimictic Lake Ammersee. The objectives of this study are to calibrate and validate the model DYRESM in order to simulate the vertical thermal distribution in Lake Ammersee and to prepare bias-corrected meteorological data from the model REMO (IPCC A1B scenario) to establish a first hydrodynamic simulation run for the period 2040–2050. The IPCC A1B emission scenario, which assumes a balanced use of all available energy sources in the world, predicts the global mean temperature to increase by about 3K from 1990 to the year 2100. To calibrate and validate the model DYRESM carefully, we used date from 2004–2007 and 1993–1999. When comparing simulated and measured water temperatures regarding the calibration period, we observed small mean absolute errors (0.96–1.61K) and root mean square errors (1.42–1.96K), as well as high coefficients of determination (0.71–0.96) at all depths. We conclude that the hydrodynamic model can be used to identify potential drawbacks of climate change (e.g. extended duration of stratification, higher thermal stability, lack of mixing) on the lake ecosystem by higher water temperatures. In addition this modelling provides the basis for coupled aquatic ecological models.

Wave climate of the Adriatic Sea: a future scenario simulation

Abstract. We present a study on expected wind wave severity changes in the Adriatic Sea for the period 2070–2099 and their impact on extremes. To do so, the phase-averaged spectral wave model SWAN is forced using wind fields computed by the high-resolution regional climate model COSMO-CLM, the climate version of the COSMO meteorological model downscaled from a global climate model running under the IPCC-A1B emission scenario. Namely, the adopted wind fields are given with a horizontal resolution of 14 km and 40 vertical levels, and they are prepared by the Italian Aerospace Research Centre (CIRA). Firstly, in order to infer the wave model accuracy in predicting seasonal variability and extreme events, SWAN results are validated against a control simulation, which covers the period 1965–1994. In particular, numerical predictions of the significant wave height Hs are compared against available in-situ data. Further, a statistical analysis is carried out to estimate changes on wave storms and extremes during the simulated periods (control and future scenario simulations). In particular, the generalized Pareto distribution is used to predict changes of storm peak Hs for frequent and rare storms in the Adriatic Sea. Finally, Borgman's theory is applied to estimate the spatial pattern of the expected maximum wave height Hmax during a storm, both for the present climate and that of the future scenario. Results show a future wave climate in the Adriatic Sea milder than the present climate, even though increases of wave severity can occur locally.

Impact assessment of projected climate change on the hydrological regime in the SE Alps, Upper Soča River basin, Slovenia

According to climate change projections, the Alps will be one of the most affected regions in Europe. A basis for adaptation measures to climate changes is the quantification of the impact. This study investigates the impact of projected climate change on the hydrological cycle in the Upper Soca River basin. It is based on the use of climate model data as input for hydrological modelling. The climatic input data used were generated by a global climate model (IPCC A1B emission scenario) and downscaled for local use. Hydrological modelling was performed using the distributed hydrological model MIKE SHE. The simulated impact was quantified by comparing results of the hydrological modelling for the control period (1971–2000) and different scenario periods (2011–2040, 2041–2070, 2071–2100). The climate projections show an increase in the average temperature (+0.9, +2.3, +3.8°C) and negligible changes in average precipitation amounts in the scenario periods. More distinctive are changes in the temporal pattern of mean monthly values (up to +5.2°C and ±45% for precipitation), which result in warmer and wetter winters and hotter and drier summers in the scenario periods. The projected rise in temperature is reflected in the increased actual evapotranspiration, the reduction of snow amount and summer groundwater recharge. Changes of monthly and period average discharges follow the trends of the meteorological variables. Changes in precipitation patterns have a major influence on the projected hydrological cycle and are the most important source of uncertainty. Estimated extreme flows indicated increased hazards related to floods, especially in the near-future scenario period, while in the far future scenario period, distinctive drought conditions are projected.

Future water availability in selected European catchments: a probabilistic assessment of seasonal flows under the IPCC A1B emission scenario using response surfaces

Abstract. A grid-based water balance model is used to quantify exceedance probabilities of high and low stream flow thresholds, and analyse their progression over the course of the 21st century. The analysis is carried out for 18 European river basins using the response surface method in combination with probabilistic projections of climate change, conditional to the IPCC A1B emission scenario up to 2100. According to this study, Nordic basins have the highest probability of high flow threshold violation in Europe, while in Central and Southern European basins, the probability of low flow threshold violation is highest. While the high flow violation occurs mostly during winter, with other seasons being likewise probable, low flow violation only occurs in summer. Some basins are facing an increased stream flow amplitude, having high probabilities for both, high flow and low flow violations.

Sensitivity of natural vegetation to climate change in the Euro-Mediterranean area

This study explores the sensitivity to future climate change of natural vegetation patterns in the Euro-Mediterranean area under the IPCC-A1B emission scenario, using a dynamic vegetation model forced by fully coupled high resolution regional ocean-atmosphere model simula- tions. Our results indicate that a future warmer climate could not only affect the regional terrestrial carbon cycle, but also significantly impact vegetation dynamics. Specifically, by 2021-2050, temper- ate deciduous vegetation is projected to replace boreal and grass vegetation in parts of northeastern Europe, while in North Africa, simulations show a progressive desertification. The changes in domi- nant vegetation are mainly related to the increased drought stress on vegetation and the enhanced fire frequency. As for the carbon cycle, large increases in net primary production (NPP) are found in northern Europe resulting from higher temperature and precipitation, as well as higher atmospheric CO2 levels. In contrast, smaller NPP increases are found in the Mediterranean region, where reduced precipitation and increased temperature leads to an increase in drought years and, hence, water- stress for vegetation.

Climatic Study of Precipitation and Temperature Distribution Over the Alps and the Italian Peninsula, Using the High-Resolution Regional Climate Model COSMO-CLM

This report is concentrated on the High-Resolution Regional Climate Model COSMO-CLM and the climatic and statistical analysis of the model’s results concerning the precipitation and temperature on the Alpine area and the Italian Peninsula. The study represents a first attempt aimed to investigate the impact of climate change in these areas. For this purpose, firstly, an observational database for Italy and the Alpine area was created, which was used for the validation and statistical analysis of the COSMO model results. Then, a climatic analysis was performed for the precipitation and temperature data that derive from two regional climate simulations of the climate of the XX century (control run) using the model Cosmo-CLM and employing for the generation of boundary conditions, respectively, ECHAM4 T106 (~ 120km resolution, 12h time resolution) driving data and ERA40 (~ 120km resolution, 6h time res.). The space resolution of both simulations was 14Km (1/8 with respect to the global model) and the time step 150 sec. The study concerned the Alpine area extending from 2° -20° East and 40° - 52° North, for the time period 1971-2000. Furthermore, precipitation and temperature data output that derived from the regional climate simulation of the Cosmo-CLM model for the period 2000-2100, were studied. For the future simulation, the IPCC A1B emission scenario was employed. The space resolution of the simulation was 14Km (1/8 with respect to the global model) and the time step 150sec. The ECHAM4 global driving data were used. The model output for both time periods were compared in order to detect any potential future changes in the precipitation and temperature spatial distribution over the Alpine area. Finally, due to the still occurring misrepresentation of local climate in regional climate model COSMO-CLM, statistical post processing was applied to overcome this problem leading to qualitatively enhanced climate information. More specifically, in the frame of the activity of the European project TRUST, the statistical bias correction method Quantile Mapping was performed for the local area of Veneto (11.5°-12°E , 45.8°-46.3), in order to compare and analyze the relation of atmospheric parameters from climate model simulations to meteorological observations. The results of the study are presented analytically in following section.

The role of climate and emission changes in future air quality over southern Canada and northern Mexico

Abstract. Potential impacts of global climate and emissions changes on regional air quality over southern (western and eastern) Canada and northern Mexico are examined by comparing future summers' (i.e., 2049–2051) average regional O3 and PM2.5 concentrations with historic concentrations (i.e., 2000–2002 summers). Air quality modeling was conducted using CMAQ and meteorology downscaled from the GISS-GCM using MM5. Emissions for North America are found using US EPA, Mexican and Canadian inventories and projected emissions following CAIR and IPCC A1B emissions scenario. Higher temperatures for all sub-regions and regional changes in mixing height, insolation and precipitation are forecast in the 2049-2051 period. Future emissions are calculated to be lower over both Canadian sub-regions, but higher over northern Mexico. Global climate change, alone, is predicted to affect PM2.5 concentrations more than O3 for the projections used in this study: average daily maximum eight (8) hour O3 (M8hO3) concentrations are estimated to be slightly different in all examined sub-regions while average PM2.5 concentrations are estimated to be higher over both Canadian sub-regions (8% over western and 3% over eastern) but 11% lower over northern Mexico. More days are forecast where M8hO3 concentrations are over 75 ppb in all examined sub-regions but the number of days where PM2.5 concentration will be over 15 μg/m3 is projected higher only over western Canada. Climate change combined with the projected emissions lead to greater change in pollutant concentrations: average M8hO3 concentrations are simulated to be 6% lower over western Canada and 8% lower over eastern Canada while average PM2.5 concentrations are simulated to be 5% lower over western Canada and 11% lower over eastern Canada. Although future emissions over northern Mexico are projected higher, pollutant concentrations are simulated to be lower due to US emissions reductions. Global climate change combined with the projected emissions will decrease average M8hO3 4% and PM2.5 17% over northern Mexico. Significant reductions in the number of days where M8hO3 concentrations are over 75 ppb and PM2.5 concentration over 15 μg/m3 are also projected with a significant reduction in peak values.

Impacts of global climate change and emissions on regional ozone and fine particulate matter concentrations over the United States

Simulated future summers (i.e., 2049–2051) and annual (i.e., 2050) average regional O3 and PM2.5 concentrations over the United States are compared with historic (i.e., 2000–2002 summers and all of 2001) levels to investigate the potential impacts of global climate change and emissions on regional air quality. Meteorological inputs to the CMAQ chemical transport model are developed by downscaling the GISS Global Climate Model simulations using an MM5‐based regional climate model. Future‐year emissions for North America are developed by growing the U.S. EPA CAIR inventory, Mexican and Canadian emissions and by using the IMAGE model with the IPCC A1B emissions scenario that is also used in projecting future climate. Reductions of more than 50% in NOX and SO2 emissions are forecast. Impacts of global climate change alone on regional air quality are small compared to impacts from emission control‐related reductions, although increases in pollutant concentrations due to stagnation and other factors are found. The combined effect of climate change and emission reductions lead to a 20% decrease (regionally varying from −11% to −28%) in the mean summer maximum daily 8‐hour ozone levels (M8hO3) over the United States. Mean annual PM2.5 concentrations are estimated to be 23% lower (varies from −9% to −32%). Major reductions in sulfate, nitrate and ammonium PM2.5 components combined with the limited reduction in organic carbon suggests that organic carbon will be the dominant component of PM2.5 mass in the future. Regionally, the eastern United States benefits more than the rest of the regions from reductions in both M8hO3 and PM2.5, because of both spatial variations in the meteorological and emissions changes. Reduction in the higher M8hO3 concentrations is also estimated for all subregions and fewer days with M8hO3 above the air quality standards in urban sites with Atlanta in the southeast benefiting most.