IPCC A1B Emission Scenario Research Articles

Global warming will affect the maximum potential abundance of boreal plant species

Forecasting the impact of future global warming on biodiversity requires understanding how temperature limits the distribution of species. Here we rely on Liebig's Law of Minimum to estimate the effect of temperature on the maximum potential abundance that a species can attain at a certain location. We develop 95%‐quantile regressions to model the influence of effective temperature sum on the maximum potential abundance of 25 common understory plant species of Finland, along 868 nationwide plots sampled in 1985. Fifteen of these species showed a significant response to temperature sum that was consistent in temperature‐only models and in all‐predictors models, which also included cumulative precipitation, soil texture, soil fertility, tree species and stand maturity as predictors. For species with significant and consistent responses to temperature, we forecasted potential shifts in abundance for the period 2041–2070 under the IPCC A1B emission scenario using temperature‐only models. We predict major potential changes in abundance and average northward distribution shifts of 6–8 km yr−1. Our results emphasize inter‐specific differences in the impact of global warming on the understory layer of boreal forests. Species in all functional groups from dwarf shrubs, herbs and grasses to bryophytes and lichens showed significant responses to temperature, while temperature did not limit the abundance of 10 species. We discuss the interest of modelling the ‘maximum potential abundance’ to deal with the uncertainty in the predictions of realized abundances associated to the effect of environmental factors not accounted for and to dispersal limitations of species, among others. We believe this concept has a promising and unexplored potential to forecast the impact of specific drivers of global change under future scenarios.

Hydrological response to climate change in a high altitude catchment

Different climate models are linked to the coupled river and hydrological model MIKE SHE-MIKE-11 to evaluate the future impact of climate change on hydrology in the Lidder sub basin of the Jhelum Basin. The coupled hydrological model was calibrated against the observed stream flow data at Sheeshnag gauging station. The output of the model in the form of snow cover percentage was validated with the high resolution satellite-based Modis data. The outputs from five different global climate models for IPCC A1B emission scenario for future (2025, 2050, 2075 and 2100) emission scenarios were applied on a hydrological model. It was observed that at the end of 21st century the ET losses in the region is increasing, snow storage component is decreasing which is further causing the runoff in the river to increase at the end of 21st century. The contribution of base flow to the discharge in the Lidder River is increasing under all climate models except for incm3 model.

Hydrological response to climate change in a high altitude catchment

Different climate models are linked to the coupled river and hydrological model MIKE SHE-MIKE-11 to evaluate the future impact of climate change on hydrology in the Lidder sub basin of the Jhelum Basin. The coupled hydrological model was calibrated against the observed stream flow data at Sheeshnag gauging station. The output of the model in the form of snow cover percentage was validated with the high resolution satellite-based Modis data. The outputs from five different global climate models for IPCC A1B emission scenario for future (2025, 2050, 2075 and 2100) emission scenarios were applied on a hydrological model. It was observed that at the end of 21st century the ET losses in the region is increasing, snow storage component is decreasing which is further causing the runoff in the river to increase at the end of 21st century. The contribution of base flow to the discharge in the Lidder River is increasing under all climate models except for incm3 model.

Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas.

We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981-2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981-2010, 2011-2040, and 2041-2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041-2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities.

Methane dynamics in the subarctic tundra: combining stable isotope analyses, plot- and ecosystem-scale flux measurements

Abstract. Methane (CH4) fluxes were investigated in a subarctic Russian tundra site in a multi-approach study combining plot-scale data, ecosystem-scale eddy covariance (EC) measurements, and a fine-resolution land cover classification scheme for regional upscaling. The flux data as measured by the two independent techniques resulted in a seasonal (May–October 2008) cumulative CH4 emission of 2.4 (EC) and 3.7 g CH4 m−2 (manual chambers) for the source area representative of the footprint of the EC instruments. Upon upscaling for the entire study region of 98.6 km2, the chamber measured flux data yielded a regional flux estimate of 6.7 g CH4 m−2 yr−1. Our upscaling efforts accounted for the large spatial variability in the distribution of the various land cover types (LCTs) predominant at our study site. Wetlands with emissions ranging from 34 to 53 g CH4 m−2 yr−1 were the most dominant CH4-emitting surfaces. Emissions from thermokarst lakes were an order of magnitude lower, while the rest of the landscape (mineral tundra) was a weak sink for atmospheric methane. Vascular plant cover was a key factor in explaining the spatial variability of CH4 emissions among wetland types, as indicated by the positive correlation of emissions with the leaf area index (LAI). As elucidated through a stable isotope analysis, the dominant CH4 release pathway from wetlands to the atmosphere was plant-mediated diffusion through aerenchyma, a process that discriminates against 13C-CH4. The CH4 released to the atmosphere was lighter than that in the surface porewater, and δ13C in the emitted CH4 correlated negatively with the vascular plant cover (LAI). The mean value of δ13C obtained here for the emitted CH4, −68.2 ± 2.0 ‰, is within the range of values from other wetlands, thus reinforcing the use of inverse modelling tools to better constrain the CH4 budget. Based on the IPCC A1B emission scenario, a temperature increase of 6.1 °C relative to the present day has been predicted for the European Russian tundra by the end of the 21st Century. A regional warming of this magnitude will have profound effects on the permafrost distribution leading to considerable changes in the regional landscape with a potential for an increase in the areal extent of CH4-emitting wet surfaces.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Impact of future climate change on a genetic plantation of hybrid pine

European black pine (Pinus nigra Arnold) and Japanese red pine (Pinus densiflora Siebold & Zucc.) are nonnative conifers that have been introduced into the United States and have the ability to hybridize with each other and can potentially become an invasive threat. Interspecific hybridization is an important component of applied genetic tree improvement programs. This study retrospectively examined the influence of climate on interannual growth patterns of 12 full-sib families of hybrid pine that were derived from the hybridization of European black pine and Japanese red pine. The hybrids (Pinus nigra × Pinus densiflora) were initially planted in 1982 in southern mid-Michigan at Michigan State University (MSU) Sandhill Research Area. Tree-ring analysis methods (dendrochronology) were used to quantify the influence of climate (i.e., mean temperature and moisture index) on interannual basal area growth rates of the hybrid pine over an 18 year period (1991–2008). The productivity of the 12 full-sib families of hybrid pine were also projected under future climate change in the 21st century based on the IPCC A1B emission scenario. Climatic sensitivities that were identified in the hybrid pine families included high temperature stress in the summer and fall, moisture stress in the summer, winter harshness, and the timing of the start of the growing season. According to projections, by the end of the 21st century, 8 out of the 12 pine families will show significant decreases in growth outside of the historical norm under the temperature-based dendrochronology models, while 4 families will show significant declines under the moisture index models. The results indicate that the hybrid pine families appear to be generally resilient to future changes in moisture, but will likely be extremely vulnerable to future climatic warming, and thus do not appear to be a future invasive threat. This study represents the first dendrochronological examination of hybrid pine in North America.

Thermal stratification of Portuguese reservoirs: potential impact of extreme climate scenarios

Changes in water temperature and stratification dynamics can have a significant effect on hydrodynamics and water quality in reservoirs. Therefore, to assess future climate impacts, projections of three regional climate models for Europe, under the IPCC A1B emission scenario (2081–2100), were used with the CE-QUAL-W2 water quality model to evaluate changes in the thermal regime of 24 Portuguese reservoirs, representing different geographic regions, morphologies, volumes and hydrological regimes. Simulation results were compared with reference simulations for the period 1989–2008 and changes in water temperature and thermal stratification characteristics were evaluated. Future inflow scenarios were estimated from precipitation-runoff non-linear correlations and outflows were estimated considering present water uses, including hydropower, water supply and irrigation. Results suggest a significant increment in the mean water temperature of the reservoirs for the entire water volume and at water surface of 2.3 and 2.5 °C, respectively, associated with a runoff reduction of approximately 23%. Overall, variations in annual stratification patterns are characterized by changes in the mean annual length of stratification anomaly that ranged from −21 to +39 days. Results also show the influence of depth and volume over the reservoir's temperature anomaly, highlighting the importance of future water uses and operation rule curves optimization for reservoirs.

CECILIA Regional Climate Simulations for Future Climate: Analysis of Climate Change Signal

Regional climate models (RCMs) are important tools used for downscaling climate simulations from global scale models. In project CECILIA, two RCMs were used to provide climate change information for regions of Central and Eastern Europe. Models RegCM and ALADIN-Climate were employed in downscaling global simulations from ECHAM5 and ARPEGE-CLIMAT under IPCC A1B emission scenario in periods 2021–2050 and 2071–2100. Climate change signal present in these simulations is consistent with respective driving data, showing similar large-scale features: warming between 0 and 3°C in the first period and 2 and 5°C in the second period with the least warming in northwestern part of the domain increasing in the southeastern direction and small precipitation changes within range of +1 to −1 mm/day. Regional features are amplified by the RCMs, more so in case of the ALADIN family of models.

Modelling wave-driven sediment transport in a changing climate: a case study for northern Adriatic Sea (Italy)

In this paper, we investigate the impact of climate change on coastal sediment transport in a deltaic system in the northern Adriatic Sea, with reference to the period 2070–2099 in the IPCC A1B emission scenario. Wind fields obtained by means of the high-resolution regional climate model Consortium for Small-scale Modelling–Climate Limited-area Modelling were employed for computing wave climate at basin scale by means of the spectral wave model Simulating Waves Nearshore. This was used as a constraint for a nearshore hydromorphodynamic model (MIKE LITPACK), which was applied to a test site on the Po River Delta, located in northern Italy. Relevant sediment transport processes have been studied at storm and decadal time scales in order to capture climate change effects on single events and as an overall trend. The transport rates in the A1B climate change scenario were then compared with the corresponding results of a control analysis (period 1965–1994) representing the actual climate. Although predicted wave climate in the investigated scenario displays an overall decrease in sea severity offshore in the northern Adriatic Sea, the effects of these modifications are modulated during the onshore propagation, with different impacts on sediment transport depending on the considered process and time scale. The strategy presented in this work can find fruitful applications in the long-term modelling of coastal and transitional environments, in which morphology is strongly influenced by sediment transport in the nearshore zone, suggesting a methodological approach for coastal planning and management.

Modelling soil borne fungal pathogens of arable crops under climate change

Soil-borne fungal plant pathogens, agents of crown and root rot, are seldom considered in studies on climate change and agriculture due both to the complexity of the soil system and to the incomplete knowledge of their response to environmental drivers. A controlled chamber set of experiments was carried out to quantify the response of six soil-borne fungi to temperature, and a species-generic model to simulate their response was developed. The model was linked to a soil temperature model inclusive of components able to simulate soil water content also as resulting from crop water uptake. Pathogen relative growth was simulated over Europe using the IPCC A1B emission scenario derived from the Hadley-CM3 global climate model. Climate scenarios of soil temperature in 2020 and 2030 were compared to the baseline centred in the year 2000. The general trend of the response of soil-borne pathogens shows increasing growth in the coldest areas of Europe; however, a larger rate of increase is shown from 2020 to 2030 compared to that of 2000 to 2020. Projections of pathogens of winter cereals indicate a marked increase of growth rate in the soils of northern European and Baltic states. Fungal pathogens of spring sowing crops show unchanged conditions for their growth in soils of the Mediterranean countries, whereas an increase of suitable conditions was estimated for the areals of central Europe which represent the coldest limit areas where the host crops are currently grown. Differences across fungal species are shown, indicating that crop-specific analyses should be ran.

Lake heat content and stability variation due to climate change: coupled regional climate model (REMO)-lake model (DYRESM) analysis

Climate change-derived higher air temperatures and the resulting increase in lake surface temperatures are known to influence the physical, biological and chemical processes of water bodies. By using hydrodynamic lake models coupled with regional climate models the potential future impact of a changing climate can be investigated. The present study hence elucidates limno-physical changes at the peri-Alpine, 83-m deep, currently dimictic Ammersee in southeastern Germany, both to underline the role of lakes as sentinels of climate change and provide a sound basis for further limnological investigations. This was realised by using water temperatures simulated with the hydrodynamic model DYRESM for the period 2041-2050, based on the results of the regional climate model REMO (IPCC A1B emission scenario). Modelling of future heat content resulted in a projected increase in the upper 3 m of the epilimnion from end of March to mid-November, whereas a decrease in future total heat content (January-December) of the entire water column was simulated compared to that observed in 1997-2007. Lake thermal stability is projected to be higher in the period 2041-2050 than in 1985-2007. Stratification is expected to occur earlier and to last longer in the future than the pattern observed in 1985-2007. The future mean May-June depth of the thermocline is simulated to be situated above its past average vertical position, whereas an increase of mean thermocline depth is projected for the beginning of August to October. Furthermore, the mean May-October thickness of the metalimnion is simulated to increase. Additionally, we investigated the sensitivity of these limno-physical results to changes in the model parameter light extinction coefficient which determines how the solar radiation is absorbed by the lake water. The elucidation of physical changes at Ammersee by means of a regional climate model provides a sound basis on which to face the new challenges of lake modelling.

Projected changes in mean and extreme precipitation indices over India using PRECIS

The impact of global warming on the characteristics of mean and extremes of rainfall over India is investigated using a high resolution regional climate model PRECIS developed by Hadley Centre, UK. Five simulations of PRECIS made using the lateral boundary conditions from a suite of Perturbed Physics Ensembles (PPE) generated using Hadley Center Coupled Model (HadCM3) for Quantifying Uncertainty in Model Predictions (QUMP) project corresponding to IPCC A1B emission scenario have been analyzed here for this purpose. The projected changes depict seasonally dependent fine scale structure in response to the topographic forcing and changes in circulation, especially along the west coast and North East (NE) region of India towards the end of the 21st century i.e. 2080s (2071–2098). Analysis of the extreme precipitation indices indicates an increase in the intensity of rainfall on wet days towards 2080s under A1B scenario. Changes in extreme precipitation events and dry spells suggest not only shifts, but also a substantial increase in the spread of the precipitation distribution, with an increased probability of the occurrence of events conducive to both floods and droughts. The projected changes in various precipitation extremes show a large regional variability. Total rainfall on very heavy rainy days (R95p) is projected to increase by around 40–50% over the central parts of the country. The number of rainy days >10mm (R10) may increase by 10–20% over west coast, east central India and northeastern parts while over northwest and rain shadow region they may increase by 40–50%. The consecutive dry days (CDDs) may decrease by 10–20% over Indo-Gangetic plain, however over west coast there may not be any significant change. The CDDs are projected to rise by 10–20% over west central and peninsular India. The precipitation per wet day (SDII) may be more intense by 10–40% over the entire land mass, however there may not be any significant change over south peninsular India.

Climate Change Impacts of Ozone on Morbidity in Vulnerable Populations across the Life Stages in 2050, Mecklenburg County, North Carolina, USA

Background: Climate- and emissions-related changes in ozone concentrations will likely impact both morbidity and mortality; these changes may have greater effects on vulnerable populations such as children and older adults. Aims: 1) Estimate the climate- and emissions-related impacts on ozone-related cardiopulmonary morbidity burden from 2006-2011 to 2048-2050 in Mecklenburg County, North Carolina (NC), an urban county in Southeastern United States with over 900,000 residents. 2) Assess the sensitivity of results to alternate population growth and age structure scenarios. Methods: We obtained respiratory and cardiovascular emergency department (ED) visit data from Mecklenburg County for April-October 2006-2011 from the NC Disease Event Tracking and Epidemiologic Collection Tool surveillance system. We estimate baseline ozone-morbidity associations with a time-series model of merged daily ozone monitor data and ED visit counts. We generate projected ozone concentration grids (12km) for 2048-2050 with the Community Multi-scale Air Quality (CMAQ) chemistry transport model using the IPCC A1B emissions scenario and assuming emission changes from anthropogenic sources only . We use a health impact assessment framework to estimate the projected changes in ED visits and the influence of alternate demographic scenarios in 2050. Results: 39,515 eligible ED visits (19,812 cardiovascular, 19,703 respiratory) occurred during the 2006-2011 baseline study period, with mean daily count of 31.5 (SD 7.6). Daily maximum 8-hour average ozone concentrations ranged from 3 to 127 ppb, with median of 51 ppb; May-August 2050 ozone projections indicate decreasing ozone levels, with a median of 36 ppb and range of 18-62 ppb. Baseline associations, projected health impacts, and sensitivity to alternate demographic scenarios will be presented. Conclusions: Climate change, air quality regulation, and population dynamics will likely alter future demand for ED services. These projections can be used to inform local public health preparedness and support continued air pollution mitigation.

Impact of Climate Change Effects on Contamination of Cereal Grains with Deoxynivalenol

Climate change is expected to aggravate feed and food safety problems of crops; however, quantitative estimates are scarce. This study aimed to estimate impacts of climate change effects on deoxynivalenol contamination of wheat and maize grown in the Netherlands by 2040. Quantitative modelling was applied, considering both direct effects of changing climate on toxin contamination and indirect effects via shifts in crop phenology. Climate change projections for the IPCC A1B emission scenario were used for the scenario period 2031-2050 relative to the baseline period of 1975-1994. Climatic data from two different global and regional climate model combinations were used. A weather generator was applied for downscaling climate data to local conditions. Crop phenology models and prediction models for DON contamination used, each for winter wheat and grain maize. Results showed that flowering and full maturity of both wheat and maize will advance with future climate. Flowering advanced on average 5 and 11 days for wheat, and 7 and 14 days for maize (two climate model combinations). Full maturity was on average 10 and 17 days earlier for wheat, and 19 and 36 days earlier for maize. On the country level, contamination of wheat with deoxynivalenol decreased slightly, but not significantly. Variability between regions was large, and individual regions showed a significant increase in deoxynivalenol concentrations. For maize, an overall decrease in deoxynivalenol contamination was projected, which was significant for one climate model combination, but not significant for the other one. In general, results disagree with previous reported expectations of increased feed and food safety hazards under climate change. This study illustrated the relevance of using quantitative models to estimate the impacts of climate change effects on food safety, and of considering both direct and indirect effects when assessing climate change impacts on crops and related food safety hazards.

Contemporary trends and future changes in freshwater ice conditions: inference from temperature indices

This study examines current trends and future changes in five daily air-temperature derived proxy indices for freshwater ice regimes. The indices are autumn 0 °C isotherm date (autumn I0), spring 0 °C isotherm date (spring I0), winter duration (WD), maximum annual accumulated freezing degree-days (AFDD), and mid-winter thaw frequency. A total of 127 meteorological stations distributed across Fennoscandia (Norway, Sweden, and Finland) have been used to derive the indices for the contemporary period 1961–2010. Results show overall trends towards later autumn I0 and stronger trends towards earlier spring I0. Altogether, WD was shortened by a regional average of −5.2 ± 2.9 days per decade, the reduction being significant at 5% level in 71 stations. AFDD decreased in all the 127 stations with a regional average of −57 ± 35 °C-days per decade. The impact of future warming on the indices was investigated using climate signals from the IPCC's A1B emissions scenario. The results showed that WD will shorten by an average of 36 days in 2041–2070 and by an average of 51 days in 2071–2100. The ecological and socio-economic impacts of the observed and future changes in the indices are qualitatively evaluated.

The effects of aggressive mitigation on steric sea level rise and sea ice changes

With an increasing political focus on limiting global warming to less than 2 � C above pre-industrial levels it is vital to understand the consequences of these targets on key parts of the climate system. Here, we focus on changes in sea level and sea ice, comparing twenty-first century pro- jections with increased greenhouse gas concentrations (using the mid-range IPCC A1B emissions scenario) with those under a mitigation scenario with large reductions in emis- sions (the E1 scenario). At the end of the twenty-first century, the global mean steric sea level rise is reduced by about a third in the mitigation scenario compared with the A1B scenario. Changes in surface air temperature are found to be poorly correlated with steric sea level changes. While the projected decreases in sea ice extent during the first half of the twenty-first century are independent of the season or scenario, especially in the Arctic, the seasonal cycle of sea ice extent is amplified. By the end of the century the Arctic becomes sea ice free in September in the A1B scenario in most models. In the mitigation scenario the ice does not disappear in the majority of models, but is reduced by 42 % of the present September extent. Results for Antarctic sea ice changes reveal large initial biases in the models and a sig- nificant correlation between projected changes and the initial extent. This latter result highlights the necessity for further refinements in Antarctic sea ice modelling for more reliable projections of future sea ice.

Climate change impact assessment on Veneto and Friuli plain groundwater. Part I: An integrated modeling approach for hazard scenario construction

Climate change impacts on water resources, particularly groundwater, is a highly debated topic worldwide, triggering international attention and interest from both researchers and policy makers due to its relevant link with European water policy directives (e.g. 2000/60/EC and 2007/118/EC) and related environmental objectives. The understanding of long-term impacts of climate variability and change is therefore a key challenge in order to address effective protection measures and to implement sustainable management of water resources.This paper presents the modeling approach adopted within the Life+ project TRUST (Tool for Regional-scale assessment of groUndwater Storage improvement in adaptation to climaTe change) in order to provide climate change hazard scenarios for the shallow groundwater of high Veneto and Friuli Plain, Northern Italy. Given the aim to evaluate potential impacts on water quantity and quality (e.g. groundwater level variation, decrease of water availability for irrigation, variations of nitrate infiltration processes), the modeling approach integrated an ensemble of climate, hydrologic and hydrogeologic models running from the global to the regional scale.Global and regional climate models and downscaling techniques were used to make climate simulations for the reference period 1961–1990 and the projection period 2010–2100. The simulation of the recent climate was performed using observed radiative forcings, whereas the projections have been done prescribing the radiative forcings according to the IPCC A1B emission scenario. The climate simulations and the downscaling, then, provided the precipitation, temperatures and evapo-transpiration fields used for the impact analysis. Based on downscaled climate projections, 3 reference scenarios for the period 2071–2100 (i.e. the driest, the wettest and the mild year) were selected and used to run a regional geomorphoclimatic and hydrogeological model. The final output of the model ensemble produced information about the potential variations of the water balance components (e.g. river discharge, groundwater level and volume) due to climate change. Such projections were used to develop potential hazard scenarios for the case study area, to be further applied within climate change risk assessment studies for groundwater resources and associated ecosystems.This paper describes the models' chain and the methodological approach adopted in the TRUST project and analyzes the hazard scenarios produced in order to investigate climate change risks for the case study area.

Marine downscaling of a future climate scenario in the North Sea and possible effects on dinoflagellate harmful algal blooms

Two hydrodynamic and ecological models were used to investigate the effects of climate change—according to the IPCC A1b emission scenario – on the primary productivity of the North Sea and on harmful algal blooms. Both models were forced with atmospheric fields from a regional downscaling of General Circulation Models to compare two sets of 20-year simulations representative of present climate (1984–2004) conditions and of the 2040s. Both models indicated a general warming of the North Sea by up to 0.8°C and a slight freshening by the 2040s. The models suggested that the eastern North Sea would be subjected to more temperature and salinity changes than the western part. In addition, the ecological modules of the models indicated that the warming up of the sea would result in a slightly earlier spring bloom. The one model that also computes the distribution of four different phytoplankton groups suggests an increase in the abundance of dinoflagellates, whereas the abundance of diatoms, flagellates and Phaeocystis sp. remains comparable to current levels, or decrease. Assuming that Dinophysis spp. would experience a similar increase in abundance as the modelled group of dinoflagellates, it is hypothesised that blooms of Dinophysis spp. may occur more frequently in the North Sea by 2040. However, implications for shellfish toxicity remain unclear.

Climate change impact assessment in Veneto and Friuli Plain groundwater. Part II: A spatially resolved regional risk assessment

Climate change impact assessment on water resources has received high international attention over the last two decades, due to the observed global warming and its consequences at the global to local scale. In particular, climate-related risks for groundwater and related ecosystems pose a great concern to scientists and water authorities involved in the protection of these valuable resources. The close link of global warming with water cycle alterations encourages research to deepen current knowledge on relationships between climate trends and status of water systems, and to develop predictive tools for their sustainable management, copying with key principles of EU water policy. Within the European project Life+ TRUST (Tool for Regional-scale assessment of groundwater Storage improvement in adaptation to climaTe change), a Regional Risk Assessment (RRA) methodology was developed in order to identify impacts from climate change on groundwater and associated ecosystems (e.g. surface waters, agricultural areas, natural environments) and to rank areas and receptors at risk in the high and middle Veneto and Friuli Plain (Italy). Based on an integrated analysis of impacts, vulnerability and risks linked to climate change at the regional scale, a RRA framework complying with the Sources–Pathway–Receptor–Consequence (SPRC) approach was defined. Relevant impacts on groundwater and surface waters (i.e. groundwater level variations, changes in nitrate infiltration processes, changes in water availability for irrigation) were selected and analyzed through hazard scenario, exposure, susceptibility and risk assessment. The RRA methodology used hazard scenarios constructed through global and high resolution model simulations for the 2071–2100 period, according to IPCC A1B emission scenario in order to produce useful indications for future risk prioritization and to support the addressing of adaptation measures, primarily Managed Artificial Recharge (MAR) techniques. Relevant outcomes from the described RRA application highlighted that potential climate change impacts will occur with different extension and magnitude in the case study area. Particularly, qualitative and quantitative impacts on groundwater will occur with more severe consequences in the wettest and in the driest scenario (respectively). Moreover, such impacts will likely have little direct effects on related ecosystems – croplands, forests and natural environments – lying along the spring area (about 12% of croplands and 2% of natural environments at risk) while more severe consequences will indirectly occur on natural and anthropic systems through the reduction in quality and quantity of water availability for agricultural and other uses (about 80% of agricultural areas and 27% of groundwater bodies at risk).