Ensemble Modeling of the Baltic Sea Ecosystem to Provide Scenarios for Management

We present a multi-model ensemble study for the Baltic Sea, and investigate the combined impact of changing climate, external nutrient supply, and fisheries on the marine ecosystem. The applied regional climate system model contains state-of-the-art component models for the atmosphere, sea ice, ocean, land surface, terrestrial and marine biogeochemistry, and marine food-web. Time-dependent scenario simulations for the period 1960–2100 are performed and uncertainties of future projections are estimated. In addition, reconstructions since 1850 are carried out to evaluate the models sensitivity to external stressors on long time scales. Information from scenario simulations are used to support decision-makers and stakeholders and to raise awareness of climate change, environmental problems, and possible abatement strategies among the general public using geovisualization. It is concluded that the study results are relevant for the Baltic Sea Action Plan of the Helsinki Commission.     

Simulating uncertainty in climate-pest models with fuzzy numbers

Inputs in climate-pest models are commonly expressed as point estimates ('crisp' numbers), which implies perfect knowledge of the system in study. In reality, however, all model inputs harbor some level of uncertainty. This is particularly true for climate change impact assessments where the inputs (i.e., climate projections) are highly uncertain. In this study, uncertainties in climate projections were expressed as 'fuzzy' numbers; these are uncertain numbers for which one knows that there is a range of possible values and that some values are 'more possible' than others. A generic pest risk model incorporating the combined effects of temperature, soil moisture, and cold stress was implemented in a fuzzy spreadsheet environment and run with three climate scenarios: (1) present climate (control run); (2) crisp climate change; and (3) fuzzy climate change. Under the crisp climate change scenario, winter and summer temperatures and precipitation were altered using best estimates (averaged predictions from the 1995 assessment report of the Intergovernmental Panel on Climate Change [IPCC]). Under the fuzzy scenario, climate changes were expressed as triangular fuzzy numbers, utilizing the extremes (lowest and highest predictions from the IPCC report) in addition to the best estimates. Under each scenario, environmental favorability was calculated for six locations in two geographical regions (Central North America and Southern Europe) with two hypothetical pest species having temperate or mediterranean climate requirements. Simulations with the crisp climate change scenario suggested only minor changes in overall environmental favorability compared with the control run. When simulations were conducted with the fuzzy climate change scenario, however, important changes in environmental favorability emerged, particularly in Southern Europe. In that region, the possibility of considerably increased winter precipitation led to increased values of environmental favorability. However, the simulations also showed that this result harbored a very broad range of possible outcomes. The results support the notion that uncertainty in climate change projections must be reduced before reliable impact assessments can be achieved.     

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countries with more limited commitments. In the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.     

Increase in summer European ozone amounts due to climate change

The local and regional distribution of pollutants is significantly influenced by weather patterns and variability along with the spatial patterns of emissions. Therefore, climatic changes which affect local meteorological conditions can alter air quality. We use the regional air quality model CHIMERE driven by meteorological fields from regional climate change simulations to investigate changes in summer ozone mixing ratios over Europe under increased greenhouse gas (GHG) forcing. Using three 30-year simulation periods, we find that daily peak ozone amounts as well as average ozone concentrations substantially increase during summer in future climate conditions. This is mostly due to higher temperatures and reduced cloudiness and precipitation over Europe and it leads to a higher number of ozone events exceeding information and warning thresholds. Our results show a pronounced regional variability, with the largest effects of climate change on ozone concentrations occurring over England, Belgium, Germany and France. The temperature-driven increase in biogenic emissions appears to enhance the ozone production and isoprene was identified as the most important chemical factor in the ozone sensitivity. We also find that summer ozone levels in future climate projections are similar to those found during the exceptionally warm and dry European summer of 2003. Our simulations suggest that in future climate conditions summer ozone might pose a much more serious threat to human health, agriculture and natural ecosystems in Europe, so that the effects of climate trends on pollutant amounts should be considered in future emission control measures.     

Modeling Nutrient Transports and Exchanges of Nutrients Between Shallow Regions and the Open Baltic Sea in Present and Future Climate

We quantified horizontal transport patterns and the net exchange of nutrients between shallow regions and the open sea in the Baltic proper. A coupled biogeochemical-physical circulation model was used for transient simulations 1961-2100. The model was driven by regional downscaling of the IPCC climate change scenario A1B from two global General Circulation Models in combination with two nutrient load scenarios. Modeled nutrient transports followed mainly the large-scale internal water circulation and showed only small circulation changes in the future projections. The internal nutrient cycling and exchanges between shallow and deeper waters became intensified, and the internal removal of phosphorus became weaker in the warmer future climate. These effects counteracted the impact from nutrient load reductions according to the Baltic Sea Action Plan. The net effect of climate change and nutrient reductions was an increased net import of dissolved inorganic phosphorus to shallow areas in the Baltic proper.     

Patterns of crop cover under future climates

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.     

Climate change impact assessment on Northeast China’s grain production

The international community is paying more attention to climate change because a consensus has been reached that climate change has an adverse effect not only on the environment but also on agriculture. Therefore, in this study, present and future climate datasets (obtained from general circulation models) including atmospheric carbon concentration were used to assess the impact of climate change on grain production for an important base of China (Northeast). An empirical model has been developed using climate and other additional variables (effective irrigation area, fertilizer, and labor force) to assess the effect of climate change on grain production. The results revealed that maximum temperature is a key climate determinant in grain production of the study area. Atmospheric carbon concentration showed a significant impact on grain outputs in most of the cases. During the analysis, it was observed that precipitation displayed a declining trend while an effective irrigation area showed positive non-significant contribution to grain production. Analysis based on different representative concentration pathways exhibited that maximum temperature may contribute negatively to grain production in the future. Overall, the analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.

     

Effect of climate change on air quality

Air quality is strongly dependent on weather and is therefore sensitive to climate change. Recent studies have provided estimates of this climate effect through correlations of air quality with meteorological variables, perturbation analyses in chemical transport models (CTMs), and CTM simulations driven by general circulation model (GCM) simulations of 21st-century climate change. We review these different approaches and their results. The future climate is expected to be more stagnant, due to a weaker global circulation and a decreasing frequency of mid-latitude cyclones. The observed correlation between surface ozone and temperature in polluted regions points to a detrimental effect of warming. Coupled GCM–CTM studies find that climate change alone will increase summertime surface ozone in polluted regions by 1–10 ppb over the coming decades, with the largest effects in urban areas and during pollution episodes. This climate penalty means that stronger emission controls will be needed to meet a given air quality standard. Higher water vapor in the future climate is expected to decrease the ozone background, so that pollution and background ozone have opposite sensitivities to climate change. The effect of climate change on particulate matter (PM) is more complicated and uncertain than for ozone. Precipitation frequency and mixing depth are important driving factors but projections for these variables are often unreliable. GCM–CTM studies find that climate change will affect PM concentrations in polluted environments by ±0.1–1 μg m^?3 over the coming decades. Wildfires fueled by climate change could become an increasingly important PM source. Major issues that should be addressed in future research include the ability of GCMs to simulate regional air pollution meteorology and its sensitivity to climate change, the response of natural emissions to climate change, and the atmospheric chemistry of isoprene. Research needs to be undertaken on the effect of climate change on mercury, particularly in view of the potential for a large increase in mercury soil emissions driven by increased respiration in boreal ecosystems.     

Future climate scenarios and rainfall--runoff modelling in the Upper Gallego catchment (Spain)

Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall-runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system.     

Climate change: potential impact on plant diseases

Global climate has changed since pre-industrial times. Atmospheric CO(2), a major greenhouse gas, has increased by nearly 30% and temperature has risen by 0.3 to 0.6 degrees C. The intergovernmental panel on climate change predicts that with the current emission scenario, global mean temperature would rise between 0.9 and 3.5 degrees C by the year 2100. There are, however, many uncertainties that influence these predictions. Despite the significance of weather on plant diseases, comprehensive analysis of how climate change will influence plant diseases that impact primary production in agricultural systems is presently unavailable. Evaluation of the limited literature in this area suggests that the most likely impact of climate change will be felt in three areas: in losses from plant diseases, in the efficacy of disease management strategies and in the geographical distribution of plant diseases. Climate change could have positive, negative or no impact on individual plant diseases. More research is needed to obtain base-line information on different disease systems. Most plant disease models use different climatic variables and operate at a different spatial and temporal scale than do the global climate models. Improvements in methodology are necessary to realistically assess disease impacts at a global scale.     

Introducing an integrated climate change perspective in POPs modelling, monitoring and regulation

This paper presents a review on the implications of climate change on the monitoring, modelling and regulation of persistent organic pollutants (POPs). Current research gaps are also identified and discussed.Long-term data sets are essential to identify relationships between climate fluctuations and changes in chemical species distribution. Reconstructing the influence of climatic changes on POPs environmental behaviour is very challenging in some local studies, and some insights can be obtained by the few available dated sediment cores or by studying POPs response to inter-annual climate fluctuations. Knowledge gaps and future projections can be studied by developing and applying various modelling tools, identifying compounds susceptibility to climate change, local and global effects, orienting international policies.Long-term monitoring strategies and modelling exercises taking into account climate change should be considered when devising new regulatory plans in chemicals management.     

Atmospheric composition change: Climate–Chemistry interactions

Chemically active climate compounds are either primary compounds like methane (CH₄), removed by oxidation in the atmosphere, or secondary compounds like ozone (O₃), sulfate and organic aerosols, both formed and removed in the atmosphere. Man-induced climate–chemistry interaction is a two-way process: Emissions of pollutants change the atmospheric composition contributing to climate change through the aforementioned climate components, and climate change, through changes in temperature, dynamics, the hydrological cycle, atmospheric stability, and biosphere-atmosphere interactions, affects the atmospheric composition and oxidation processes in the troposphere. Here we present progress in our understanding of processes of importance for climate–chemistry interactions, and their contributions to changes in atmospheric composition and climate forcing. A key factor is the oxidation potential involving compounds like O₃ and the hydroxyl radical (OH). Reported studies represent both current and future changes. Reported results include new estimates of radiative forcing based on extensive model studies of chemically active climate compounds like O₃, and of particles inducing both direct and indirect effects. Through EU projects like ACCENT, QUANTIFY, and the AeroCom project, extensive studies on regional and sector-wise differences in the impact on atmospheric distribution are performed. Studies have shown that land-based emissions have a different effect on climate than ship and aircraft emissions, and different measures are needed to reduce the climate impact. Several areas where climate change can affect the tropospheric oxidation process and the chemical composition are identified. This can take place through enhanced stratospheric–tropospheric exchange of ozone, more frequent periods with stable conditions favoring pollution build up over industrial areas, enhanced temperature induced biogenic emissions, methane releases from permafrost thawing, and enhanced concentration through reduced biospheric uptake. During the last 5–10 years, new observational data have been made available and used for model validation and the study of atmospheric processes. Although there are significant uncertainties in the modeling of composition changes, access to new observational data has improved modeling capability. Emission scenarios for the coming decades have a large uncertainty range, in particular with respect to regional trends, leading to a significant uncertainty range in estimated regional composition changes and climate impact.     

Climatic sensitivity of temperate forests

Climatic change and associated global changes are of major interest to foresters, both in terms of forest ecology and of future forest production. Predicting the likely effects of global change on forests is extremely difficult due to the critical lack of information on regional changes in meteorological factors relevant to forests. However, existing models of forest production and forest distribution fail to take adequate account of what is already known. Climate and carbon dioxide concentrations have shown substantial changes over the last 100 years. Although the rate of change is likely to increase, recent proposed and implemented control strategies, together with better climatic models, are tending to suggest that the rate of change will be less than initially thought. This means that past changes may provide an increasingly useful source of information. In particular, information on the impact on forests of both long-term climate change and short-term climatic events is rapidly increasing. Such information should be built into future forest response models.     

Mapping Human Dimensions of Climate Change Research in the Canadian Arctic

This study maps current understanding and research trends on the human dimensions of climate change (HDCC) in the eastern and central Canadian Arctic. Developing a systematic literature review methodology, 117 peer reviewed articles are identified and examined using quantitative and qualitative methods. The research highlights the rapid expansion of HDCC studies over the last decade. Early scholarship was dominated by work documenting Inuit observations of climate change, with research employing vulnerability concepts and terminology now common. Adaptation studies which seek to identify and evaluate opportunities to reduce vulnerability to climate change and take advantage of new opportunities remain in their infancy. Over the last 5 years there has been an increase social science-led research, with many studies employing key principles of community-based research. We currently have baseline understanding of climate change impacts, adaptation, and vulnerability in the region, but key gaps are evident. Future research needs to target significant geographic disparities in understanding, consider risks and opportunities posed by climate change outside of the subsistence hunting sector, complement case study research with regional analyses, and focus on identifying and characterizing sustainable and feasible adaptation interventions.     

Organizing For Risk Oriented Climate Alteration Research

The ubiquity in effects and complexity of modern environmental issues requires careful consideration of focused research to insure that answers to key policy oriented questions are obtained. Broad-based, unstructured research programs have proven to be inefficient instruments for characterizing risks from environmental stress. Both the expense and the importance of timeliness of information preclude a traditional “bottom-up” approach to research. Instead, a more “top-down” organized approach that links the natural and socioeconomic sciences has advantages to support environmental risk assessment and research prioritization of climate alteration. Early examples of analysis using an integrating framework for risk assessment focus on the need for research on human interactions and the environmental damage function in addition to the basic earth sciences. Nonlinearities in environmental impact of climate change, and uncertainties in the extent of growth of energy efficiencies, are seen to be key unknowns in the risk assessment of climate alternatives. To date, earth science research has not been structured well for environmental risk assessment of the climate change question. The U.S. national research program aimed at risk assessment of climate alteration is examined as an example. The examination suggests that the present conceptual plan falls short of an optimum structure derived from exploitation of an integrating framework, even though it is rich in scientific strength and diversity. To strengthen its public value and accessibility, the research program could account in its planning for prioritized needs defined by an integrating analysis for risk assessment and management.     

Bias correction of regional climate model simulations for the impact assessment of the climate change in Egypt

This study projected the future temperature change for Egypt during the late of this century (2071–2100) for three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5), by correcting regional climate model (RCM) simulations of average, maximum, and minimum daily temperature with reference to observed data of 26 stations. Four commonly used methods of bias correction have been applied and evaluated: linear scaling, variance scaling, and theoretical and empirical quantile mapping. The compromise programing results of the applied evaluation criteria show that the best method is the variance scaling, and thus it was applied to transfer the correction factor to the projections. All temperature indices are expected to increase significantly under all scenarios and reach the highest record by the end of the century, i.e., the expected increase in average, maximum, and minimum temperature ranges between 4.08–7.41 °C, 4.55–7.89 °C, and 3.88–7.23 °C, respectively. The largest temperature rise will occur in the summer, with the highest increase in the maximum (minimum) temperature of 10.9 °C (10 °C) in July and August under RCP8.5. The maximum (minimum) winter temperature, on the other hand, will drop by a maximum of 2 °C (1.35 °C) under RCP2.6. The Western Desert and Upper Egypt are the regions most affected by climate change, while the northern region of Egypt is the least affected. These findings would help in impact assessment and adaptation strategies and encourage further investigation to evaluate various climate models in order to obtain a comprehensive assessment of the climate change impacts on different hydrometeorological processes in Egypt.

     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Hydrological change--climate change impact simulations for Sweden

Climate change resulting from the enhanced greenhouse effect is expected to give rise to changes in hydrological systems. This hydrological change, as with the change in climate variables, will vary regionally around the globe. Impact studies at local and regional scales are needed to assess how different regions will be affected. This study focuses on assessment of hydrological impacts of climate change over a wide range of Swedish basins. Different methods of transferring the signal of climate change from climate models to hydrological models were used. Several hydrological model simulations using regional climate model scenarios from Swedish Regional Climate Modelling Programme (SWECLIM) are presented. A principal conclusion is that subregional impacts to river flow vary considerably according to whether a basin is in northern or southern Sweden. Furthermore, projected hydrological change is just as dependent on the choice of the global climate model used for regional climate model boundary conditions as the choice of anthropogenic emissions scenario.     

Terrestrial water cycle and the impact of climate change

The terrestrial water cycle and the impact of climate change are critical for agricultural and natural ecosystems. In this paper, we assess both by running a macro-scale water balance model under a baseline condition and 2 General Circulation Model (GCM)-based climate change scenarios. The results show that in 2021-2030, water demand will increase worldwide due to climate change. Water shortage is expected to worsen in western Asia, the Arabian Peninsula, northern and southern Africa, northeastern Australia, southwestern North America, and central South America. A significant increase in surface runoff is expected in southern Asia and a significant decrease is expected in northern South America. These changes will have implications for regional environment and socioeconomics.     

Global networking for assessment of impacts of global change on plant pests

Global change encompasses changes in atmospheric composition, climate and climate variability, and land cover and land use. The occurrence of these changes and their interactive effects on biological systems are worldwide; thus, an effective global change research and impact assessment program must be based on international and interdisciplinary research and communication. With this in mind, several collaborative research networks with a focus on global change have been established in the biological sciences. They include the Global Change and Terrestrial Ecosystems (GCTE) Core Project of the International Geosphere-Biosphere Programme (IGBP) which aims to predict the effects of global change on terrestrial ecosystems, including agriculture and production forestry. Because of the importance of plant pests (arthropods, microbial pathogens, weeds) as yield-reducing factors in agriculture and as early indicators of global change, GCTE initiated a network Activity on "Global Change Impacts on Pests, Diseases and Weeds" with the overall goal of developing a predictive capability for impact assessment and adaptation. The network's specific objectives, contributing research projects, initial results and future challenges are discussed.