Sensitivity of Alpine Snow and Streamflow Regimes to Climate Changes

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Marks, D. G.; Bernhardt, M.

2014-12-01

Understanding the sensitivity of hydrological processes to climate change in alpine areas with snow dominated regimes is of paramount importance as alpine basins show both high runoff efficiency associated with the melt of the seasonal snowpack and great sensitivity of snow processes to temperature change. In this study, meteorological data measured in a selection of alpine headwaters basins including Reynolds Mountain East, Idaho, USA, Wolf Creek, Yukon in Canada, and Zugspitze Mountain, Germany with climates ranging from arctic to continental temperate were used to study the snow and streamflow sensitivity to climate change. All research sites have detailed multi-decadal meteorological and snow measurements. The Cold Regions Hydrological Modelling platform (CRHM) was used to create a model representing a typical alpine headwater basin discretized into hydrological response units with physically based representations of snow redistribution by wind, complex terrain snowmelt energetics and runoff processes in alpine tundra. The sensitivity of snow hydrology to climate change was investigated by changing air temperature and precipitation using weather generating methods based on the change factors obtained from different climate model projections for future and current periods. The basin mean and spatial variability of peak snow water equivalent, sublimation loss, duration of snow season, snowmelt rates, streamflow peak, and basin discharge were assessed under varying climate scenarios and the most sensitive hydrological mechanisms to the changes in the different alpine climates were detected. The results show that snow hydrology in colder alpine climates is more resilient to warming than that in warmer climates, but that compensatory factors to warming such as reduced blowing snow sublimation loss and reduced melt rate should also be assessed when considering climate change impacts on alpine hydrology.

A dynamic, climate-driven model of Rift Valley fever.

PubMed

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

2016-03-31

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

Productivity benefits of warming at regional scale could be offset by detrimental impacts on site level hydrology.

PubMed

Zeng, Qing; Zhang, Yamian; Wen, Li; Li, Zhaxijie; Duo, Hairui; Lei, Guangchun

2017-11-09

Climate change affects the distribution and persistence of wildlife. Broad scale studies have demonstrated that climate change shifts the geographic ranges and phenology of species. These findings are influential for making high level strategies but not practical enough to guide site specific management. In this study, we explored the environment factors affecting the population of Bar-headed Goose in the key breeding site of Qinghai using generalized additive mixed model (GAMM). Our results showed that 1) there were significant increasing trends in climate variables and river flows to the Qinghai Lake; 2) NDVI in the sites decreased significantly despite the regional positive trend induced by the warmer and wetter climate; 3) NDVI at site scale was negatively correlated to lake water level; and 4) the abundance of Bar-headed Goose decreased significantly at all sites. While the abundance was positively related to NDVI at breeding sites, the GAMM revealed an opposite relationship at foraging areas. Our findings demonstrated the multi-facet effects of climate change on population dynamics; and the effect at global/regional scale could be complicated by site level factors.

Risk assessment of agricultural water requirement based on a multi-model ensemble framework, southwest of Iran

NASA Astrophysics Data System (ADS)

Zamani, Reza; Akhond-Ali, Ali-Mohammad; Roozbahani, Abbas; Fattahi, Rouhollah

2017-08-01

Water shortage and climate change are the most important issues of sustainable agricultural and water resources development. Given the importance of water availability in crop production, the present study focused on risk assessment of climate change impact on agricultural water requirement in southwest of Iran, under two emission scenarios (A2 and B1) for the future period (2025-2054). A multi-model ensemble framework based on mean observed temperature-precipitation (MOTP) method and a combined probabilistic approach Long Ashton Research Station-Weather Generator (LARS-WG) and change factor (CF) have been used for downscaling to manage the uncertainty of outputs of 14 general circulation models (GCMs). The results showed an increasing temperature in all months and irregular changes of precipitation (either increasing or decreasing) in the future period. In addition, the results of the calculated annual net water requirement for all crops affected by climate change indicated an increase between 4 and 10 %. Furthermore, an increasing process is also expected regarding to the required water demand volume. The most and the least expected increase in the water demand volume is about 13 and 5 % for A2 and B1 scenarios, respectively. Considering the results and the limited water resources in the study area, it is crucial to provide water resources planning in order to reduce the negative effects of climate change. Therefore, the adaptation scenarios with the climate change related to crop pattern and water consumption should be taken into account.

Scaling and contextualizing climate-conflict nexus in historical agrarian China

NASA Astrophysics Data System (ADS)

Lee, Harry F.

2017-04-01

This study examines climate-conflict nexus in historical agrarian China in multi-scalar and contextualized approach, illustrating what and how socio-political factors could significantly mediate the climate-violent link in pre-industrial society. Previous empirical large-N studies show that violent conflict in historical agrarian society was triggered by climate-induced food scarcity. The relationship was valid in China, Europe, and various geographic regions in the Northern Hemisphere in pre-industrial era. Nevertheless, the observed relationship has only been verified at a macro level (long-term variability of the nexus is emphasized and data over large area are aggregated), and somewhat generalized in nature (only physical environmental factors are controlled). Three inter-related issues remain unresolved: First, the key explanatory variable of violent conflicts may change substantially at different spatio-temporal scales. It is necessary to check whether the climate-conflict nexus is valid at a micro level (about short-term variability of the nexus and data in finer spatial resolution), and explore how the nexus changes along various spatio-temporal dimensions. Second, as the climate-conflict nexus has only been demonstrated in a broad sense, it is necessary to check whether and how the nexus is mediated by local socio-political context. More non-climatic factors pertinent to the cause and distribution of conflicts (e.g., governance, adaptive mechanisms, etc.) should be considered. Third, the methodology applied in the previous studies assumes spatially-independent observations and linear relationship, which may simplify the climate-conflict link. Moreover, the solitary reliance on quantitative methods may neglect those non-quantifiable socio-political dynamics which mediates the climate-conflict nexus. I plan to address the above issues by using disaggregated spatial analysis and in-depth case studies, with close attention to local and temporal differences and non-linear nature of the climate-conflict link. China will be chosen as study area. Study period will be delimited to AD1-1911. This study represents pioneering research which systematically examines the climate-conflict nexus in pre-industrial society over extended period in multi-scalar and contextualized perspective. By comparing and evaluating the climate-conflict link along various spatio-temporal dimensions and in different socio-political context, it may help to deepen the theoretical understanding of, and also resolve the current debate over, the climate-conflict relationship. Given the large potential changes in climatic regimes projected in coming decades, the findings in this study may have important implications for the social impact of climate change in tropical countries that are in some ways similar to pre-industrial society.

Land use allocation model considering climate change impact

NASA Astrophysics Data System (ADS)

Lee, D. K.; Yoon, E. J.; Song, Y. I.

2017-12-01

In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fedorov, Alexey V.

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth systemmore » models, to the stability and variability of the AMOC in past climates.« less

Climate Change Adopted Building Envelope as A Protector of Human Health in the Urban Environment

NASA Astrophysics Data System (ADS)

Januszkiewicz, Krystyna

2017-10-01

Recently, an expanded understanding of building performance acknowledges that all forces acting on buildings (climate, energies, information, and human agents) are not static and fixed, but rather mutable and transient. With the use of parametric and multi-criteria optimization digital tools, buildings’ envelopes can be designed to respond to various requirements. This paper explores the possibilities of architectural design to benefit human conditions, which encompasses mental well-being, environmental quality of life during the Climate Change era. The first part of the paper defines the main factors (such as: lack of green nature and sunlight, noise and pollution) which are influencing the formation of psychological disorder in big cities. The negative impact of these factors is constantly increasing in the time of Climate Change progressing. The second part presents results of the research program undertaken at West Pomeranian University of Technology in Szczecin by author. The program goes on to attempt to solve the problem through architectural design. This study highlights a social problem, such as mental well-being, resulting from urbanization or effects of the climate change, and serves as a useful background for further research on the possibilities of redefining sustainable and human friendly design.

Multi-site precipitation downscaling using a stochastic weather generator

NASA Astrophysics Data System (ADS)

Chen, Jie; Chen, Hua; Guo, Shenglian

2018-03-01

Statistical downscaling is an efficient way to solve the spatiotemporal mismatch between climate model outputs and the data requirements of hydrological models. However, the most commonly-used downscaling method only produces climate change scenarios for a specific site or watershed average, which is unable to drive distributed hydrological models to study the spatial variability of climate change impacts. By coupling a single-site downscaling method and a multi-site weather generator, this study proposes a multi-site downscaling approach for hydrological climate change impact studies. Multi-site downscaling is done in two stages. The first stage involves spatially downscaling climate model-simulated monthly precipitation from grid scale to a specific site using a quantile mapping method, and the second stage involves the temporal disaggregating of monthly precipitation to daily values by adjusting the parameters of a multi-site weather generator. The inter-station correlation is specifically considered using a distribution-free approach along with an iterative algorithm. The performance of the downscaling approach is illustrated using a 10-station watershed as an example. The precipitation time series derived from the National Centers for Environment Prediction (NCEP) reanalysis dataset is used as the climate model simulation. The precipitation time series of each station is divided into 30 odd years for calibration and 29 even years for validation. Several metrics, including the frequencies of wet and dry spells and statistics of the daily, monthly and annual precipitation are used as criteria to evaluate the multi-site downscaling approach. The results show that the frequencies of wet and dry spells are well reproduced for all stations. In addition, the multi-site downscaling approach performs well with respect to reproducing precipitation statistics, especially at monthly and annual timescales. The remaining biases mainly result from the non-stationarity of NCEP precipitation. Overall, the proposed approach is efficient for generating multi-site climate change scenarios that can be used to investigate the spatial variability of climate change impacts on hydrology.

Climate change; Confronting the global experiment

Treesearch

Constance I. Millar

2006-01-01

Earth’s natural climate system is characterized by continually changing climates, with climate regimes that oscillate quasi-cyclically at multiple and nested scales from annual to multi-millennial, and commonly change abruptly. Under naturally changing climates, plant species track changes at all scales in individualistic manner, with plant communities...

Multi-aged Forest: an Optimal Management Strategy for Carbon Sequestration

NASA Astrophysics Data System (ADS)

Yao, L.; Tang, X.; Ma, M.

2017-12-01

Disturbances and climatic changes significantly affect forest ecosystem productivity, water use efficiency (WUE) and carbon (C) flux dynamics. A deep understanding of terrestrial feedbacks to such effects and recovery mechanisms in forests across contrasting climatic regimes is essential to predict future regional/global C and water budgets, which are also closely related to the potential forest management decisions. However, the resilience of multi-aged and even-aged forests to disturbances has been debated for more than 60 years because of technical measurement constraints. Here we evaluated 62 site-years of eddy covariance measurements of net ecosystem production (NEP), evapotranspiration (ET), the estimates of gross primary productivity (GPP), ecosystem respiration (Re) and ecosystem-level WUE, as well as the relationships with environmental controls in three chronosequences of multi- and even-aged coniferous forests covering the Mediterranean, temperate and boreal regions. Age-specific dynamics in multi-year mean annual NEP and WUE revealed that forest age is a key variable that determines the sign and magnitude of recovering forest C source-sink strength from disturbances. However, the trends of annual NEP and WUE across succession stages between two stand structures differed substantially. The successional patterns of NEP exhibited an inverted-U trend with age at the two even-aged chronosequences, whereas NEP of the multi-aged chronosequence increased steadily through time. Meanwhile, site-level WUE of even-aged forests decreased gradually from young to mature, whereas an apparent increase occurred for the same forest age in multi-aged stands. Compared with even-aged forests, multi-aged forests sequestered more CO2 with forest age and maintained a relatively higher WUE in the later succession periods. With regard to the available flux measurements in this study, these behaviors are independent of tree species, stand ages and climate conditions . We also found that distinctly different environmental factors controlled forest C and water fluxes under three climatic regimes.These findings will provide important implications for forest management strategies to mitigate global climate change.

The Fate of the World is in your hands: computer gaming for multi-faceted climate change education

NASA Astrophysics Data System (ADS)

Bedford, D. P.

2015-12-01

Climate change is a multi-faceted (or 'wicked') problem. True climate literacy therefore requires understanding not only the workings of the climate system, but also the current and potential future impacts of climate change and sea level rise on individuals, communities and countries around the world, as noted in the US Global Change Research Program's (2009) Climate Literacy: The Essential Principles of Climate Sciences. The asymmetric nature of climate change impacts, whereby the world's poorest countries have done the least to cause the problem but will suffer disproportionate consequences, has also been widely noted. Education in climate literacy therefore requires an element of ethics in addition to physical and social sciences. As if addressing these multiple aspects of climate change were not challenging enough, polling data has repeatedly shown that many members of the public tend to see climate change as a far away problem affecting people remote from them at a point in the future, but not themselves. This perspective is likely shared by many students. Computer gaming provides a possible solution to the combined problems of, on the one hand, addressing the multi-faceted nature of climate change, and, on the other hand, making the issue real to students. Fate of the World, a game produced by the company Red Redemption, has been used on several occasions in a small (20-30 students) introductory level general education course on global warming at Weber State University. Players are required to balance difficult decisions about energy investment while managing regional political disputes and attempting to maintain minimum levels of development in the world's poorer countries. By providing a realistic "total immersion" experience, the game has the potential to make climate change issues more immediate to players, and presents them with the ethical dilemmas inherent in climate change. This presentation reports on the use of Fate of the World in an educational setting, highlighting student experiences and lessons learned from two attempts to use the game as a tool for teaching the multi-faceted nature of climate change.

Impact of climate, CO2 and land use on terrestrial carbon and water fluxes in China based on a multi-model analysis

NASA Astrophysics Data System (ADS)

Jia, B.; Xie, Z.

2017-12-01

Climate change and anthropogenic activities have been exerting profound influences on ecosystem function and processes, including tightly coupled terrestrial carbon and water cycles. However, their relative contributions of the key controlling factors, e.g., climate, CO2 fertilization, land use and land cover change (LULCC), on spatial-temporal patterns of terrestrial carbon and water fluxes in China are still not well understood due to the lack of ecosystem-level flux observations and uncertainties in single terrestrial biosphere model (TBM). In the present study, we quantified the effect of climate, CO2, and LULCC on terrestrial carbon and water fluxes in China using multi-model simulations for their inter-annual variability (IAV), seasonal cycle amplitude (SCA) and long-term trend during the past five decades (1961-2010). In addition, their relative contributions to the temporal variations of gross primary productivity (GPP), net ecosystem productivity (NEP) and evapotranspiration (ET) were investigated through factorial experiments. Finally, the discussions about the inter-model differences and model uncertainties were presented.

Climate change driven plant-metal-microbe interactions.

PubMed

Rajkumar, Mani; Prasad, Majeti Narasimha Vara; Swaminathan, Sandhya; Freitas, Helena

2013-03-01

Various biotic and abiotic stress factors affect the growth and productivity of crop plants. Particularly, the climatic and/or heavy metal stress influence various processes including growth, physiology, biochemistry, and yield of crops. Climatic changes particularly the elevated atmospheric CO₂ enhance the biomass production and metal accumulation in plants and help plants to support greater microbial populations and/or protect the microorganisms against the impacts of heavy metals. Besides, the indirect effects of climatic change (e.g., changes in the function and structure of plant roots and diversity and activity of rhizosphere microbes) would lead to altered metal bioavailability in soils and concomitantly affect plant growth. However, the effects of warming, drought or combined climatic stress on plant growth and metal accumulation vary substantially across physico-chemico-biological properties of the environment (e.g., soil pH, heavy metal type and its bio-available concentrations, microbial diversity, and interactive effects of climatic factors) and plant used. Overall, direct and/or indirect effects of climate change on heavy metal mobility in soils may further hinder the ability of plants to adapt and make them more susceptible to stress. Here, we review and discuss how the climatic parameters including atmospheric CO₂, temperature and drought influence the plant-metal interaction in polluted soils. Other aspects including the effects of climate change and heavy metals on plant-microbe interaction, heavy metal phytoremediation and safety of food and feed are also discussed. This review shows that predicting how plant-metal interaction responds to altering climatic change is critical to select suitable crop plants that would be able to produce more yields and tolerate multi-stress conditions without accumulating toxic heavy metals for future food security. Copyright © 2012 Elsevier Ltd. All rights reserved.

Policy Coherence and Interplay between Climate Change Adaptation Policies and the Forestry Sector in Nepal.

PubMed

Ranabhat, Sunita; Ghate, Rucha; Bhatta, Laxmi Dutt; Agrawal, Nand Kishor; Tankha, Sunil

2018-06-01

Least Developed Countries are likely to be hit the hardest by climate change and need focused efforts towards adaptation. Nepal recognizes that it needs to integrate climate change adaptation into various policies, but limited understanding of how to make these policies coherent is among the factors that hinder effective adaptation action. This can lead to wasted resources and lost opportunities. This paper applies concepts from policy coherence for development frameworks and policy content analysis to examine coherence in Nepal's climate and forest policies-and discusses the factors hindering effective implementation. The policies are analyzed at the horizontal/external level at three layers-motivation, measures, and planned implementation process. The paper finds that policies are more consistent on motivation level and adaptation measures, but are less coherent on implementation. The National Adaptation Programme of Action (NAPA) is more explicit in identifying institutions, organizations, roles and responsibilities, resource allocation (financial), and a monitoring and evaluation plan for climate change adaptation while other policies such as Climate Change Policy 2011, National Biodiversity Strategy and Action Plan 2014-2020, Forest Policy 2015, and Forest Sector Strategy 2016 have critical gaps in this area. This paper conclude that formulation of a policy, articulating targets, and mobilizing financial resources are in themselves not sufficient to effectively address climate change adaptation. Policy-based legislation is required, together with development of a supportive collaborative multi-stakeholder approach at different levels of governance, backed up by effective, collaborative monitoring and enforcement.

Policy Coherence and Interplay between Climate Change Adaptation Policies and the Forestry Sector in Nepal

NASA Astrophysics Data System (ADS)

Ranabhat, Sunita; Ghate, Rucha; Bhatta, Laxmi Dutt; Agrawal, Nand Kishor; Tankha, Sunil

2018-06-01

Least Developed Countries are likely to be hit the hardest by climate change and need focused efforts towards adaptation. Nepal recognizes that it needs to integrate climate change adaptation into various policies, but limited understanding of how to make these policies coherent is among the factors that hinder effective adaptation action. This can lead to wasted resources and lost opportunities. This paper applies concepts from policy coherence for development frameworks and policy content analysis to examine coherence in Nepal's climate and forest policies—and discusses the factors hindering effective implementation. The policies are analyzed at the horizontal/external level at three layers—motivation, measures, and planned implementation process. The paper finds that policies are more consistent on motivation level and adaptation measures, but are less coherent on implementation. The National Adaptation Programme of Action (NAPA) is more explicit in identifying institutions, organizations, roles and responsibilities, resource allocation (financial), and a monitoring and evaluation plan for climate change adaptation while other policies such as Climate Change Policy 2011, National Biodiversity Strategy and Action Plan 2014-2020, Forest Policy 2015, and Forest Sector Strategy 2016 have critical gaps in this area. This paper conclude that formulation of a policy, articulating targets, and mobilizing financial resources are in themselves not sufficient to effectively address climate change adaptation. Policy-based legislation is required, together with development of a supportive collaborative multi-stakeholder approach at different levels of governance, backed up by effective, collaborative monitoring and enforcement.

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin.

PubMed

Jore, Solveig; Vanwambeke, Sophie O; Viljugrein, Hildegunn; Isaksen, Ketil; Kristoffersen, Anja B; Woldehiwet, Zerai; Johansen, Bernt; Brun, Edgar; Brun-Hansen, Hege; Westermann, Sebastian; Larsen, Inger-Lise; Ytrehus, Bjørnar; Hofshagen, Merete

2014-01-08

Global environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data. We explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 - 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions. Significant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model. Our results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change.

An Interactive Multi-Model for Consensus on Climate Change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kocarev, Ljupco

This project purports to develop a new scheme for forming consensus among alternative climate models, that give widely divergent projections as to the details of climate change, that is more intelligent than simply averaging the model outputs, or averaging with ex post facto weighting factors. The method under development effectively allows models to assimilate data from one another in run time with weights that are chosen in an adaptive training phase using 20th century data, so that the models synchronize with one another as well as with reality. An alternate approach that is being explored in parallel is the automatedmore » combination of equations from different models in an expert-system-like framework.« less

Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge

NASA Astrophysics Data System (ADS)

Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.

2017-01-01

Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.

A multi-paradigm framework to assess the impacts of climate change on end-use energy demand.

PubMed

Nateghi, Roshanak; Mukherjee, Sayanti

2017-01-01

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months.

A multi-paradigm framework to assess the impacts of climate change on end-use energy demand

PubMed Central

Nateghi, Roshanak

2017-01-01

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months. PMID:29155862

Quantitative assessment of the impacts of climate change and human activities on runoff change in a typical karst watershed, SW China.

PubMed

Wu, Luhua; Wang, Shijie; Bai, Xiaoyong; Luo, Weijun; Tian, Yichao; Zeng, Cheng; Luo, Guangjie; He, Shiyan

2017-12-01

The Yinjiang River watershed is a typical karst watershed in Southwest China. The present study explored runoff change and its responses to different driving factors in the Yinjiang River watershed over the period of 1984 to 2015. The methods of cumulative anomaly, continuous wavelet analysis, Mann-Kendall rank correlation trend test, and Hurst exponent were applied to analyze the impacts of climate change and human activities on runoff change. The contributions of climate change and human activities to runoff change were quantitatively assessed using the comparative method of the slope changing ratio of cumulative quantity (SCRCQ). The following results were obtained: (1) From 1984 to 2015, runoff and precipitation exhibited no-significant increasing trend, whereas evaporation exhibited significant decreasing trend. (2) In the future, runoff, precipitation, and evaporation will exhibit weak anti-persistent feature with different persistent times. This feature indicated that in their persistent times, runoff and precipitation will continuously decline, whereas evaporation will continuously increase. (3) Runoff and precipitation were well-synchronized with abrupt change features and stage characteristics, and exhibited consistent multi-timescale characteristics that were different from that of evaporation. (4) The contribution of precipitation to runoff change was 50%-60% and was considered high and stable. The contribution of evaporation to runoff change was 10%-90% and was variable with a positive or negative effects. The contribution of human activities to runoff change was 20%-60% and exerted a low positive or negative effect. (5) Climatic factors highly contributed to runoff change. By contrast, the contribution of human activities to runoff change was low. The contribution of climatic factors to runoff change was highly variable because of differences among base periods. In conclusion, this paper provides a basic theoretical understanding of the main factors that contribute to runoff change in a karst watershed. Copyright © 2017 Elsevier B.V. All rights reserved.

Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio-economic perspective). In our presentation we will show the cases of Peru and the Philippines, and discuss the implications for agriculture policies and risk management.

Evaluating Urban Resilience to Climate Change: A Multi-Sector Approach (External Review Draft)

EPA Science Inventory

Climate change impacts are diverse, long-term, and not easily predictable. Adapting to climate change requires making context specific and forward-looking decisions regarding a variety of climate change impacts and vulnerabilities when the future is highly uncertain. EPA scientis...

Using High Frequency Monitoring of Environmental Factors to Predict Microcystin Concentrations in a Multi-use, Inland Reservoir

EPA Science Inventory

Cyanobacteria, known as blue-green algae, are photosynthetic bacteria found naturally in marine, freshwater, and estuarine ecosystems. An increase in nutrient input and changes in the climate have contributed to the proliferation of cyanobacteria, forming harmful algal blooms, or...

Energy Switching Threshold for Climatic Benefits

NASA Astrophysics Data System (ADS)

Zhang, X.; Cao, L.; Caldeira, K.

2013-12-01

Climate change is one of the great challenges facing humanity currently and in the future. Its most severe impacts may still be avoided if efforts are made to transform current energy systems (1). A transition from the global system of high Greenhouse Gas (GHG) emission electricity generation to low GHG emission energy technologies is required to mitigate climate change (2). Natural gas is increasingly seen as a choice for transitions to renewable sources. However, recent researches in energy and climate puzzled about the climate implications of relying more energy on natural gas. On one hand, a shift to natural gas is promoted as climate mitigation because it has lower carbon per unit energy than coal (3). On the other hand, the effect of switching to natural gas on nuclear-power and other renewable energies development may offset benefits from fuel-switching (4). Cheap natural gas is causing both coal plants and nuclear plants to close in the US. The objective of this study is to measure and evaluate the threshold of energy switching for climatic benefits. We hypothesized that the threshold ratio of energy switching for climatic benefits is related to GHGs emission factors of energy technologies, but the relation is not linear. A model was developed to study the fuel switching threshold for greenhouse gas emission reduction, and transition from coal and nuclear electricity generation to natural gas electricity generation was analyzed as a case study. The results showed that: (i) the threshold ratio of multi-energy switching for climatic benefits changes with GHGs emission factors of energy technologies. (ii)The mathematical relation between the threshold ratio of energy switching and GHGs emission factors of energies is a curved surface function. (iii) The analysis of energy switching threshold for climatic benefits can be used for energy and climate policy decision support.

A review of multi-risk methodologies for natural hazards: Consequences and challenges for a climate change impact assessment.

PubMed

Gallina, Valentina; Torresan, Silvia; Critto, Andrea; Sperotto, Anna; Glade, Thomas; Marcomini, Antonio

2016-03-01

This paper presents a review of existing multi-risk assessment concepts and tools applied by organisations and projects providing the basis for the development of a multi-risk methodology in a climate change perspective. Relevant initiatives were developed for the assessment of multiple natural hazards (e.g. floods, storm surges, droughts) affecting the same area in a defined timeframe (e.g. year, season, decade). Major research efforts were focused on the identification and aggregation of multiple hazard types (e.g. independent, correlated, cascading hazards) by means of quantitative and semi-quantitative approaches. Moreover, several methodologies aim to assess the vulnerability of multiple targets to specific natural hazards by means of vulnerability functions and indicators at the regional and local scale. The overall results of the review show that multi-risk approaches do not consider the effects of climate change and mostly rely on the analysis of static vulnerability (i.e. no time-dependent vulnerabilities, no changes among exposed elements). A relevant challenge is therefore to develop comprehensive formal approaches for the assessment of different climate-induced hazards and risks, including dynamic exposure and vulnerability. This requires the selection and aggregation of suitable hazard and vulnerability metrics to make a synthesis of information about multiple climate impacts, the spatial analysis and ranking of risks, including their visualization and communication to end-users. To face these issues, climate impact assessors should develop cross-sectorial collaborations among different expertise (e.g. modellers, natural scientists, economists) integrating information on climate change scenarios with sectorial climate impact assessment, towards the development of a comprehensive multi-risk assessment process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Knowledge of and attitudes toward climate change and its effects on health among nursing students: A multi-Arab country study.

PubMed

Felicilda-Reynaldo, Rhea Faye D; Cruz, Jonas Preposi; Alshammari, Farhan; Obaid, Khamees B; Rady, Hanan Ebrahim Abd El Aziz; Qtait, Mohammad; Alquwez, Nahed; Colet, Paolo C

2018-04-01

Climate change and its impact on health continues to receive inadequate attention in the nursing literature, especially in the Arab region. This study explored the knowledge of and attitudes toward climate change and its effect on health among nursing students from four Arab countries. A cross-sectional study was conducted among a convenience sample of 1,059 baccalaureate nursing students from four Arab countries using the New Ecological Paradigm scale and an adapted questionnaire. The findings indicate an average range of attitude toward the environment, with country of residence, type of community, academic-year level, and climate change related variables as significant factors influencing students' attitudes. A moderate level of knowledge about the potential health related impacts of climate change was revealed. Students from Saudi Arabia and Palestinian Territory reported a significantly higher level of knowledge than Egyptian and Iraqi students. Most of the respondents reported that all identified health related effects of climate change have already increased, while more than two-thirds reported that each of the health-related impacts would increase within the next 20 years. The findings underscore the need for more coverage of topics related to climate change and its health-related impacts in nursing education curricula in Arab countries. © 2017 Wiley Periodicals, Inc.

Evaluating the uncertainty of predicting future climate time series at the hourly time scale

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2011-12-01

A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

Soil moisture surpasses elevated CO2 and temperature as a control on soil carbon dynamics in a multi-factor climate change experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garten Jr, Charles T; Classen, Aimee T; Norby, Richard J

2009-01-01

Some single-factor experiments suggest that elevated CO2 concentrations can increase soil carbon, but few experiments have examined the effects of interacting environmental factors on soil carbon dynamics. We undertook studies of soil carbon and nitrogen in a multi-factor (CO2 x temperature x soil moisture) climate change experiment on a constructed old-field ecosystem. After four growing seasons, elevated CO2 had no measurable effect on carbon and nitrogen concentrations in whole soil, particulate organic matter (POM), and mineral-associated organic matter (MOM). Analysis of stable carbon isotopes, under elevated CO2, indicated between 14 and 19% new soil carbon under two different watering treatmentsmore » with as much as 48% new carbon in POM. Despite significant belowground inputs of new organic matter, soil carbon concentrations and stocks in POM declined over four years under soil moisture conditions that corresponded to prevailing precipitation inputs (1,300 mm yr-1). Changes over time in soil carbon and nitrogen under a drought treatment (approximately 20% lower soil water content) were not statistically significant. Reduced soil moisture lowered soil CO2 efflux and slowed soil carbon cycling in the POM pool. In this experiment, soil moisture (produced by different watering treatments) was more important than elevated CO2 and temperature as a control on soil carbon dynamics.« less

Climate and environmental change drives Ixodes ricinus geographical expansion at the northern range margin

PubMed Central

2014-01-01

Background Global environmental change is causing spatial and temporal shifts in the distribution of species and the associated diseases of humans, domesticated animals and wildlife. In the on-going debate on the influence of climate change on vectors and vector-borne diseases, there is a lack of a comprehensive interdisciplinary multi-factorial approach utilizing high quality spatial and temporal data. Methods We explored biotic and abiotic factors associated with the latitudinal and altitudinal shifts in the distribution of Ixodes ricinus observed during the last three decades in Norway using antibodies against Anaplasma phagocytophilum in sheep as indicators for tick presence. Samples obtained from 2963 sheep from 90 farms in 3 ecologically different districts during 1978 – 2008 were analysed. We modelled the presence of antibodies against A. phagocytophilum to climatic-, environmental and demographic variables, and abundance of wild cervids and domestic animals, using mixed effect logistic regressions. Results Significant predictors were large diurnal fluctuations in ground surface temperature, spring precipitation, duration of snow cover, abundance of red deer and farm animals and bush encroachment/ecotones. The length of the growth season, mean temperature and the abundance of roe deer were not significant in the model. Conclusions Our results highlight the need to consider climatic variables year-round to disentangle important seasonal variation, climatic threshold changes, climate variability and to consider the broader environmental change, including abiotic and biotic factors. The results offer novel insight in how tick and tick-borne disease distribution might be modified by future climate and environmental change. PMID:24401487

Carbon Pools in a Temperate Heathland Resist Changes in a Future Climate

NASA Astrophysics Data System (ADS)

Ambus, P.; Reinsch, S.; Nielsen, P. L.; Michelsen, A.; Schmidt, I. K.; Mikkelsen, T. N.

2014-12-01

The fate of recently plant assimilated carbon was followed into ecosystem carbon pools and fluxes in a temperate heathland after a 13CO2 pulse in the early growing season in a 6-year long multi-factorial climate change experiment. Eight days after the pulse, recently assimilated carbon was significantly higher in storage organs (rhizomes) of the grass Deschampsia flexuosa under elevated atmospheric CO2 concentration. Experimental drought induced a pronounced utilization of recently assimilated carbon belowground (roots, microbes, dissolved organic carbon) potentially counterbalancing limited nutrient availability. The fate of recently assimilated carbon was not affected by moderate warming. The full factorial combination of elevated CO2, warming and drought simulating future climatic conditions as expected for Denmark in 2075 did not change short-term carbon turnover significantly compared to ambient conditions. Overall, climate factors interacted in an unexpected way resulting in strong resilience of the heathland in terms of short-term carbon turnover in a future climate.

Climate change impacts: The challenge of quantifying multi-factor causation, multi-component responses, and leveraging from extremes

NASA Astrophysics Data System (ADS)

Field, C. B.

2012-12-01

Modeling climate change impacts is challenging for a variety of reasons. Some of these are related to causation. A weather or climate event is rarely the sole cause of an impact, and, for many impacts, social, economic, cultural, or ecological factors may play a larger role than climate. Other challenges are related to outcomes. Consequences of an event are often most severe when several kinds of responses interact, typically in unexpected ways. Many kinds of consequences are difficult to quantify, especially when they include a mix of market, cultural, personal, and ecological values. In addition, scale can be tremendously important. Modest impacts over large areas present very different challenges than severe but very local impacts. Finally, impacts may respond non-linearly to forcing, with behavior that changes qualitatively at one or more thresholds and with unexpected outcomes in extremes. Modeling these potentially complex interactions between drivers and impacts presents one set of challenges. Evaluating the models presents another. At least five kinds of approaches can contribute to the evaluation of impact models designed to provide insights in multi-driver, multi-responder, multi-scale, and extreme-driven contexts, even though none of these approaches is a complete or "silver-bullet" solution. The starting point for much of the evaluation in this space is case studies. Case studies can help illustrate links between processes and scales. They can highlight factors that amplify or suppress sensitivity to climate drivers, and they can suggest the consequences of intervening at different points. While case studies rarely provide concrete evidence about mechanisms, they can help move a mechanistic case from circumstantial to sound. Novel approaches to data collection, including crowd sourcing, can potentially provide tools and the number of relevant examples to develop case studies as statistically robust data sources. A critical condition for progress in this area is the ability to utilize data of uneven quality and standards. Novel approaches to meta-analysis provide other options for taking advantage of diverse case studies. Techniques for summarizing responses across impacts, drivers, and scales can play a huge role in increasing the value of information from case studies. In some cases, expert elicitation may provide alternatives for identifying mechanisms or for interpreting multi-factor drivers or responses. Especially when designed to focus on a well-defined set of observations, a sophisticated elicitation can establish formal confidence limits on responses that are otherwise difficult to constrain. A final possible approach involves a focus on the mechanisms contributing to an impact, rather than the impact itself. Approaches based on quantified mechanisms are especially appealing in the context of models where the number of interactions makes it difficult to intuitively understand the chain of connections from cause to effect, when actors differ in goals or sensitivities, or when scale affects parts of the system differently. With all of these approaches, useful evidence may not conform to traditional levels of statistical confidence. Some of the biggest challenges in taking advantage of the potential tools will involve defining what constitutes a meaningful evaluation.

Accounting for adaptive capacity and uncertainty in assessments of species’ climate-change vulnerability

USGS Publications Warehouse

Wade, Alisa A.; Hand, Brian K.; Kovach, Ryan; Luikart, Gordon; Whited, Diane; Muhlfeld, Clint C.

2016-01-01

Climate change vulnerability assessments (CCVAs) are valuable tools for assessing species’ vulnerability to climatic changes, yet failure to include measures of adaptive capacity and to account for sources of uncertainty may limit their effectiveness. Here, we provide a more comprehensive CCVA approach that incorporates all three elements used for assessing species’ climate change vulnerability: exposure, sensitivity, and adaptive capacity. We illustrate our approach using case studies of two threatened salmonids with different life histories – anadromous steelhead trout (Oncorhynchus mykiss) and non-anadromous bull trout (Salvelinus confluentus) – within the Columbia River Basin, USA. We identified general patterns of high vulnerability in low-elevation and southernmost habitats for both species. However, vulnerability rankings varied widely depending on the factors (climate, habitat, demographic, and genetic) included in the CCVA and often differed for the two species at locations where they were sympatric. Our findings illustrate that CCVA results are highly sensitive to data inputs and that spatial differences can complicate multi-species conservation. Our results highlight how CCVAs should be considered within a broader conceptual and computational framework for refining hypotheses, guiding research, and comparing plausible scenarios of species’ vulnerability for ongoing and projected climate change.

Health risks of climate change: an assessment of uncertainties and its implications for adaptation policies.

PubMed

Wardekker, J Arjan; de Jong, Arie; van Bree, Leendert; Turkenburg, Wim C; van der Sluijs, Jeroen P

2012-09-19

Projections of health risks of climate change are surrounded with uncertainties in knowledge. Understanding of these uncertainties will help the selection of appropriate adaptation policies. We made an inventory of conceivable health impacts of climate change, explored the type and level of uncertainty for each impact, and discussed its implications for adaptation policy. A questionnaire-based expert elicitation was performed using an ordinal scoring scale. Experts were asked to indicate the level of precision with which health risks can be estimated, given the present state of knowledge. We assessed the individual scores, the expertise-weighted descriptive statistics, and the argumentation given for each score. Suggestions were made for how dealing with uncertainties could be taken into account in climate change adaptation policy strategies. The results showed that the direction of change could be indicated for most anticipated health effects. For several potential effects, too little knowledge exists to indicate whether any impact will occur, or whether the impact will be positive or negative. For several effects, rough 'order-of-magnitude' estimates were considered possible. Factors limiting health impact quantification include: lack of data, multi-causality, unknown impacts considering a high-quality health system, complex cause-effect relations leading to multi-directional impacts, possible changes of present-day response-relations, and difficulties in predicting local climate impacts. Participants considered heat-related mortality and non-endemic vector-borne diseases particularly relevant for climate change adaptation. For possible climate related health impacts characterised by ignorance, adaptation policies that focus on enhancing the health system's and society's capability of dealing with possible future changes, uncertainties and surprises (e.g. through resilience, flexibility, and adaptive capacity) are most appropriate. For climate related health effects for which rough risk estimates are available, 'robust decision-making' is recommended. For health effects with limited societal and policy relevance, we recommend focusing on no-regret measures. For highly relevant health effects, precautionary measures can be considered. This study indicated that analysing and characterising uncertainty by means of a typology can be a very useful approach for selection and prioritization of preferred adaptation policies to reduce future climate related health risks.

Vegetation cover dynamics of the Mongolian semiarid zone according to multi-temporal LANDSAT imagery (the case of Darkhan test range)

NASA Astrophysics Data System (ADS)

Zharnikova, M. A.; Alymbaeva, ZH B.; Ayurzhanaev, A. A.; Garmaev, E. ZH

2016-11-01

At present much attention is given to the spatio-temporal dynamics of plant communities of steppes to assess their response to the current climate changes. In this study, a mapping of a selected modeling polygon was carried out on the basis of data decoding and field surveys of vegetation cover in the semi-arid zone. The resulting large-scale map of actual vegetation reflects the current state of the vegetation cover and its horizontal structure. It is a valuable material for monitoring of changes in the chosen area. With multi-temporal satellite Landsat imagery we consider the vegetation cover dynamics of the test range. To analyze the transformation of the environment by the climatic factors, we compared series of NDVI versus the precipitation and of NDVI versus the temperatures. Then we calculated the degree of correlation between them.

Systems thinking for understanding and predicting regional and local climate change effects on human health & well being: workshop process

EPA Science Inventory

EPA’s Systems Thinking Advisory Team (STAT) was engaged to guide a multi-disciplinary (health officials, modelers, climate change scientists, city planners, ecologists, and architects), multi-agency (EPA, CDC, State and Country officials) team in the use systems thinking, diagram...

Modeling soil respiration and variations of source components using a multi-factor global climate change experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xiongwen; Post, Wilfred M; Norby, Richard J

2011-01-01

Soil respiration is an important component of the global carbon cycle and is highly responsive to changes in soil temperature and moisture. Accurate prediction of soil respiration and its changes under future climatic conditions requires a clear understanding of the processes involved. In spite of this, most current empirical soil respiration models incorporate just few of the underlying mechanisms that may influence its response. In this study, a new partial process-based component model built on source components of soil respiration was tested using data collected from a multi-factor climate change experiment that manipulates CO2 concentrations, temperature and precipitation. These resultsmore » were then compared to results generated using several other established models. The component model we tested performed well across different treatments of global climate change. In contrast, some other models, which worked well predicting ambient environmental conditions, were unable to predict the changes under different climate change treatments. Based on the component model, the relative proportions of heterotrophic respiration (Rh) in the total soil respiration at different treatments varied from 0.33 to 0.85. There is a significant increase in the proportion of Rh under the elevated atmospheric CO2 concentration in comparison ambient conditions. The dry treatment resulted in higher proportion of Rh at elevated CO2 and ambient T than under elevated CO2 and elevated T. Also, the ratios between root growth and root maintenance respiration varied across different treatments. Neither increased temperature nor elevated atmospheric CO2 changed Q10 values significantly, while the average Q10 value at wet sites was significantly higher than it at dry sites. There was a higher possibility of increased soil respiration under drying relative to wetting conditions across all treatments based on monthly data, indicating that soil respiration may also be related to soil moisture at previous time periods. Our results reveal that the extent, time delay and contribution of different source components need to be included into mechanistic/processes-based soil respiration models at corresponding scale.« less

Hydrological changes impacts on annual runoff distribution in seasonally dry basins

NASA Astrophysics Data System (ADS)

Viola, F.; Caracciolo, D.; Feng, X.

2017-12-01

Runoff is expected to be modified in the next future by climate change as well as by land use change. Given its importance for water supply and ecosystem functioning, it is therefore imperative to develop adaptation strategies and new policies for regional water resources management and planning. To do so, the identification and attribution of natural flow regime shifts as a result of climate and land use changes are of crucial importance. In this context, the Budyko's curve has begun to be widely adopted to separate the contributions of climate and land use changes to the variation of runoff over long-term periods by using the multi-year averages of hydrological variables. In this study, a framework based on Fu's equation is proposed and applied to separate the impacts of climate and land use changes on the future annual runoff distribution in seasonally dry basins, such as those in Mediterranean climates. In particular, this framework improves a recently developed method to obtain annual runoff probability density function (pdf) in seasonally dry basins from annual rainfall and potential evapotranspiration statistics, and from knowledge of the Fu's equation parameter ω. The effect of climate change has been taken into account through the variation of the first order statistics of annual rainfall and potential evapotranspiration, consistent with general circulation models' outputs, while the Fu's equation parameter ω has been changed to represent land use change. The effects of the two factors of change (i.e., climate and land use) on the annual runoff pdf have been first independently and then jointly analyzed, by reconstructing the annual runoff pdfs for the current period and, based on likely scenarios, within the next 100 years. The results show that, for large basins, climate change is the dominant driver of the decline in annual runoff, while land use change is a secondary but important factor.

Complex carbon cycle responses to multi-level warming and supplemental summer rain in the high Arctic.

PubMed

Sharp, Elizabeth D; Sullivan, Patrick F; Steltzer, Heidi; Csank, Adam Z; Welker, Jeffrey M

2013-06-01

The Arctic has experienced rapid warming and, although there are uncertainties, increases in precipitation are projected to accompany future warming. Climate changes are expected to affect magnitudes of gross ecosystem photosynthesis (GEP), ecosystem respiration (ER) and the net ecosystem exchange of CO2 (NEE). Furthermore, ecosystem responses to climate change are likely to be characterized by nonlinearities, thresholds and interactions among system components and the driving variables. These complex interactions increase the difficulty of predicting responses to climate change and necessitate the use of manipulative experiments. In 2003, we established a long-term, multi-level and multi-factor climate change experiment in a polar semidesert in northwest Greenland. Two levels of heating (30 and 60 W m(-2) ) were applied and the higher level was combined with supplemental summer rain. We made plot-level measurements of CO2 exchange, plant community composition, foliar nitrogen concentrations, leaf δ(13) C and NDVI to examine responses to our treatments at ecosystem- and leaf-levels. We confronted simple models of GEP and ER with our data to test hypotheses regarding key drivers of CO2 exchange and to estimate growing season CO2 -C budgets. Low-level warming increased the magnitude of the ecosystem C sink. Meanwhile, high-level warming made the ecosystem a source of C to the atmosphere. When high-level warming was combined with increased summer rain, the ecosystem became a C sink of magnitude similar to that observed under low-level warming. Competition among our ER models revealed the importance of soil moisture as a driving variable, likely through its effects on microbial activity and nutrient cycling. Measurements of community composition and proxies for leaf-level physiology suggest GEP responses largely reflect changes in leaf area of Salix arctica, rather than changes in leaf-level physiology. Our findings indicate that the sign and magnitude of the future High Arctic C budget may depend upon changes in summer rain. © 2013 Blackwell Publishing Ltd.

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

The changing strength and nature of fire-climate relationships in the northern Rocky Mountains, U.S.A., 1902-2008

USGS Publications Warehouse

Littell, Jeremy

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008

PubMed Central

Higuera, Philip E.; Abatzoglou, John T.; Littell, Jeremy S.; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity. PMID:26114580

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008.

PubMed

Higuera, Philip E; Abatzoglou, John T; Littell, Jeremy S; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

An uncertainty-based framework to quantifying climate change impacts on coastal flood vulnerability: case study of New York City.

PubMed

Zahmatkesh, Zahra; Karamouz, Mohammad

2017-10-17

The continued development efforts around the world, growing population, and the increased probability of occurrence of extreme hydrologic events have adversely affected natural and built environments. Flood damages and loss of lives from the devastating storms, such as Irene and Sandy on the East Coast of the USA, are examples of the vulnerability to flooding that even developed countries have to face. The odds of coastal flooding disasters have been increased due to accelerated sea level rise, climate change impacts, and communities' interest to live near the coastlines. Climate change, for instance, is becoming a major threat to sustainable development because of its adverse impacts on the hydrologic cycle. Effective management strategies are thus required for flood vulnerability reduction and disaster preparedness. This paper is an extension to the flood resilience studies in the New York City coastal watershed. Here, a framework is proposed to quantify coastal flood vulnerability while accounting for climate change impacts. To do so, a multi-criteria decision making (MCDM) approach that combines watershed characteristics (factors) and their weights is proposed to quantify flood vulnerability. Among the watershed characteristics, potential variation in the hydrologic factors under climate change impacts is modeled utilizing the general circulation models' (GCMs) outputs. The considered factors include rainfall, extreme water level, and sea level rise that exacerbate flood vulnerability through increasing exposure and susceptibility to flooding. Uncertainty in the weights as well as values of factors is incorporated in the analysis using the Monte Carlo (MC) sampling method by selecting the best-fitted distributions to the parameters with random nature. A number of low impact development (LID) measures are then proposed to improve watershed adaptive capacity to deal with coastal flooding. Potential range of current and future vulnerability to flooding is estimated with and without consideration of climate change impacts and after implementation of LIDs. Results show that climate change has the potential to increase rainfall intensity, flood volume, floodplain extent, and flood depth in the watershed. The results also reveal that improving system resilience by reinforcing the adaptation capacity through implementing LIDs could mitigate flood vulnerability. Moreover, the results indicate the significant effect of uncertainties, arising from the factors' weights as well as climate change, impacts modeling approach, on quantifying flood vulnerability. This study underlines the importance of developing applicable schemes to quantify coastal flood vulnerability for evolving future responses to adverse impacts of climate change.

How do disturbances and climate effects on carbon and water fluxes differ between multi-aged and even-aged coniferous forests?

PubMed

Tang, Xuguang; Li, Hengpeng; Ma, Mingguo; Yao, Li; Peichl, Matthias; Arain, Altaf; Xu, Xibao; Goulden, Michael

2017-12-01

Disturbances and climatic changes significantly affect forest ecosystem productivity, water use efficiency (WUE) and carbon (C) flux dynamics. A deep understanding of terrestrial feedbacks to such effects and recovery mechanisms in forests across contrasting climatic regimes is essential to predict future regional/global C and water budgets, which are also closely related to the potential forest management decisions. However, the resilience of multi-aged and even-aged forests to disturbances has been debated for >60years because of technical measurement constraints. Here we evaluated 62site-years of eddy covariance measurements of net ecosystem production (NEP), evapotranspiration (ET), the estimates of gross primary productivity (GPP), ecosystem respiration (R e ) and ecosystem-level WUE, as well as the relationships with environmental controls in three chronosequences of multi- and even-aged coniferous forests covering the Mediterranean, temperate and boreal regions. Age-specific dynamics in multi-year mean annual NEP and WUE revealed that forest age is a key variable that determines the sign and magnitude of recovering forest C source-sink strength from disturbances. However, the trends of annual NEP and WUE across succession stages between two stand structures differed substantially. The successional patterns of NEP exhibited an inverted-U trend with age at the two even-aged chronosequences, whereas NEP of the multi-aged chronosequence increased steadily through time. Meanwhile, site-level WUE of even-aged forests decreased gradually from young to mature, whereas an apparent increase occurred for the same forest age in multi-aged stands. Compared with even-aged forests, multi-aged forests sequestered more CO 2 with forest age and maintained a relatively higher WUE in the later succession periods. With regard to the available flux measurements in this study, these behaviors are independent of tree species, stand ages and climate conditions. We also found that distinctly different environmental factors controlled forest C and water fluxes under three climatic regimes. Typical weather events such as temperature anomalies or drying-wetting cycles severely affected forest functions. Particularly, a summer drought in the boreal forest resulted in an increased NEP owing to a considerable decrease in R e , but at the cost of greater water loss from deeper groundwater resources. These findings will provide important implications for forest management strategies to mitigate global climate change. Copyright © 2017 Elsevier B.V. All rights reserved.

A multi-model framework for simulating wildlife population response to land-use and climate change

USGS Publications Warehouse

McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

2008-01-01

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Extraordinary range expansion in a common bat: the potential roles of climate change and urbanisation.

PubMed

Ancillotto, L; Santini, L; Ranc, N; Maiorano, L; Russo, D

2016-04-01

Urbanisation and climate change are two global change processes that affect animal distributions, posing critical threats to biodiversity. Due to its versatile ecology and synurbic habits, Kuhl's pipistrelle (Pipistrellus kuhlii) offers a unique opportunity to explore the relative effects of climate change and urbanisation on species distributions. In a climate change scenario, this typically Mediterranean species is expected to expand its range in response to increasing temperatures. We collected 25,132 high-resolution occurrence records from P. kuhlii European range between 1980 and 2013 and modelled the species' distribution with a multi-temporal approach, using three bioclimatic variables and one proxy of urbanisation. Temperature in the coldest quarter of the year was the most important factor predicting the presence of P. kuhlii and showed an increasing trend in the study period; mean annual precipitation and precipitation seasonality were also relevant, but to a lower extent. Although urbanisation increased in recently colonised areas, it had little effect on the species' presence predictability. P. kuhlii expanded its geographical range by about 394 % in the last four decades, a process that can be interpreted as a response to climate change.

Extraordinary range expansion in a common bat: the potential roles of climate change and urbanisation

NASA Astrophysics Data System (ADS)

Ancillotto, L.; Santini, L.; Ranc, N.; Maiorano, L.; Russo, D.

2016-04-01

Urbanisation and climate change are two global change processes that affect animal distributions, posing critical threats to biodiversity. Due to its versatile ecology and synurbic habits, Kuhl's pipistrelle ( Pipistrellus kuhlii) offers a unique opportunity to explore the relative effects of climate change and urbanisation on species distributions. In a climate change scenario, this typically Mediterranean species is expected to expand its range in response to increasing temperatures. We collected 25,132 high-resolution occurrence records from P. kuhlii European range between 1980 and 2013 and modelled the species' distribution with a multi-temporal approach, using three bioclimatic variables and one proxy of urbanisation. Temperature in the coldest quarter of the year was the most important factor predicting the presence of P. kuhlii and showed an increasing trend in the study period; mean annual precipitation and precipitation seasonality were also relevant, but to a lower extent. Although urbanisation increased in recently colonised areas, it had little effect on the species' presence predictability. P. kuhlii expanded its geographical range by about 394 % in the last four decades, a process that can be interpreted as a response to climate change.

The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

NASA Astrophysics Data System (ADS)

Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

2016-04-01

The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the role of the weathering negative feedback mechanism on multi-millennial timescales.

Targeting, out-scaling and prioritising climate-smart interventions in agricultural systems: Lessons from applying a generic framework to the livestock sector in sub-Saharan Africa.

PubMed

Notenbaert, An; Pfeifer, Catherine; Silvestri, Silvia; Herrero, Mario

2017-02-01

As a result of population growth, urbanization and climate change, agricultural systems around the world face enormous pressure on the use of resources. There is a pressing need for wide-scale innovation leading to development that improves the livelihoods and food security of the world's population while at the same time addressing climate change adaptation and mitigation. A variety of promising climate-smart interventions have been identified. However, what remains is the prioritization of interventions for investment and broad dissemination. The suitability and adoption of interventions depends on a variety of bio-physical and socio-economic factors. Also their impacts, when adopted and out-scaled, are likely to be highly heterogeneous. This heterogeneity expresses itself not only spatially and temporally but also in terms of the stakeholders affected, some might win and some might lose. A mechanism that can facilitate a systematic, holistic assessment of the likely spread and consequential impact of potential interventions is one way of improving the selection and targeting of such options. In this paper we provide climate smart agriculture (CSA) planners and implementers at all levels with a generic framework for evaluating and prioritising potential interventions. This entails an iterative process of mapping out recommendation domains, assessing adoption potential and estimating impacts. Through examples, related to livestock production in sub-Saharan Africa, we demonstrate each of the steps and how they are interlinked. The framework is applicable in many different forms, scales and settings. It has a wide applicability beyond the examples presented and we hope to stimulate readers to integrate the concepts in the planning process for climate-smart agriculture, which invariably involves multi-stakeholder, multi-scale and multi-objective decision-making.

Population-level consequences of herbivory, changing climate, and source-sink dynamics on a long-lived invasive shrub.

PubMed

van Klinken, R D; Pichancourt, J B

2015-12-01

Long-lived plant species are highly valued environmentally, economically, and socially, but can also cause substantial harm as invaders. Realistic demographic predictions can guide management decisions, and are particularly valuable for long-lived species where population response times can be long. Long-lived species are also challenging, given population dynamics can be affected by factors as diverse as herbivory, climate, and dispersal. We developed a matrix model to evaluate the effects of herbivory by a leaf-feeding biological control agent released in Australia against a long-lived invasive shrub (mesquite, Leguminoseae: Prosopis spp.). The stage-structured, density-dependent model used an annual time step and 10 climatically diverse years of field data. Mesquite population demography is sensitive to source-sink dynamics as most seeds are consumed and redistributed spatially by livestock. In addition, individual mesquite plants, because they are long lived, experience natural climate variation that cycles over decadal scales, as well as anthropogenic climate change. The model therefore explicitly considered the effects of both net dispersal and climate variation. Herbivory strongly regulated mesquite populations through reduced growth and fertility, but additional mortality of older plants will be required to reach management goals within a reasonable time frame. Growth and survival of seeds and seedlings were correlated with daily soil moisture. As a result, population dynamics were sensitive to rainfall scenario, but population response times were typically slow (20-800 years to reach equilibrium or extinction) due to adult longevity. Equilibrium population densities were expected to remain 5% higher, and be more dynamic, if historical multi-decadal climate patterns persist, the effect being dampened by herbivory suppressing seed production irrespective of preceding rainfall. Dense infestations were unlikely to form under a drier climate, and required net dispersal under the current climate. Seed input wasn't required to form dense infestations under a wetter climate. Each factor we considered (ongoing herbivory, changing climate, and source-sink dynamics) has a strong bearing on how this invasive species should be managed, highlighting the need for considering both ecological context (in this case, source-sink dynamics) and the effect of climate variability at relevant temporal scales (daily, multi-decadal, and anthropogenic) when deriving management recommendations for long-lived species.

Multi-objective optimization for generating a weighted multi-model ensemble

NASA Astrophysics Data System (ADS)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic ensemble mean and may provide reliable future projections.

Study on Net Primary Productivity over Complicated Mountainous Area based on Multi-Source Remote Sensing Data

NASA Astrophysics Data System (ADS)

Guan, X.; Shen, H.; Li, X.; Gan, W.

2017-12-01

Mountainous area hosts approximately a quarter of the global land surface, with complex climate and ecosystem conditions. More knowledge about mountainous ecosystem could highly advance our understanding of the global carbon cycle and climate change. Net Primary Productivity (NPP), the biomass increment of plants, is a widely used ecological indicator that can be obtained by remote sensing methods. However, limited by the defective characteristic of sensors, which cannot be long-term with enough spatial details synchronously, the mountainous NPP was far from being understood. In this study, a multi-sensor fusion framework was applied to synthesize a 1-km NPP series from 1982 to 2014 in mountainous southwest China, where elevation ranged from 76m to 6740m. The validation with field-measurements proved this framework greatly improved the accuracy of NPP (r=0.79, p<0.01). The detailed spatial and temporal analysis indicated that NPP variation trends changed from decreasing to increasing with the ascending elevation, as a result of a warmer and drier climate over the region. The correlation of NPP and temperature varied from negative to positive almost at the same elevation break-point of NPP trends, but the opposite for precipitation. This phenomenon was determined by the altitudinal and seasonally uneven allocation of climatic factors, as well as the downward run-off. What is more, it was indicated that the NPP variation showed three distinct stages at the year break-point of 1992 and 2002 over the region. The NPP in low-elevation area varied almost triple more drastic than the high-elevation area for all the three stages, due to the much greater change rate of precipitation. In summary, this study innovatively conducted a long-term and accurate NPP study on the not understood mountainous ecosystem with multi-source data, the framework and conclusions will be beneficial for the further cognition of global climate change.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

The CSAICLAWPS project: a multi-scalar, multi-data source approach to providing climate services for both modelling of climate change impacts on crop yields and development of community-level adaptive capacity for sustainable food security

NASA Astrophysics Data System (ADS)

Forsythe, N. D.; Fowler, H. J.

2017-12-01

The "Climate-smart agriculture implementation through community-focused pursuit of land and water productivity in South Asia" (CSAICLAWPS) project is a research initiative funded by the (UK) Royal Society through its Challenge Grants programme which is part of the broader UK Global Challenges Research Fund (GCRF). CSAICLAWPS has three objectives: a) development of "added-value" - bias assessed, statistically down-scaled - climate projections for selected case study sites across South Asia; b) investigation of crop failure modes under both present (observed) and future (projected) conditions; and c) facilitation of developing local adaptive capacity and resilience through stakeholder engagement. At AGU we will be presenting both next steps and progress to date toward these three objectives: [A] We have carried out bias assessments of a substantial multi-model RCM ensemble (MME) from the CORDEX South Asia (CORDEXdomain for case studies in three countries - Pakistan, India and Sri Lanka - and (stochastically) produced synthetic time-series for these sites from local observations using a Python-based implementation of the principles underlying the Climate Research Unit Weather Generator (CRU-WG) in order to enable probabilistic simulation of current crop yields. [B] We have characterised present response of local crop yields to climate variability in key case study sites using AquaCrop simulations parameterised based on input (agronomic practices, soil conditions, etc) from smallholder farmers. [C] We have implemented community-based hydro-climatological monitoring in several case study "revenue villages" (panchayats) in the Nainital District of Uttarakhand. The purpose of this is not only to increase availability of meteorological data, but also has the aspiration of, over time, leading to enhanced quantitative awareness of present climate variability and potential future conditions (as projected by RCMs). Next steps in our work will include: 1) future crop yield simulations driven by "perturbation" of synthetic time-series using "change factors from the CORDEX-SA MME; 2) stakeholder dialogues critically evaluating potential strategies at the grassroots (implementation) level to mitigate impacts of climate variability and change on crop yields.

Uncertainties in assessing climate change impacts on the hydrology of Mediterranean basins

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2013-04-01

There is substantial evidence in historical and recent observations that the Mediterranean and neighboring regions are especially vulnerable to the impacts of climate change. Numerous climate projections, stemming from ensembles of global and regional climate models, agree on severe changes in the climate forcing which are likely to exacerbate subsequent ecological, economic and social impacts. Many of these causal connections are closely linked to the general expectation that water availability will decline in the already water-stressed basins of Africa, the Mediterranean region and the Near East, even though considerable regional variances must be expected. Consequently, climate change impacts on water resources are raising concerns regarding their possible management and security implications. Decreasing access to water resources and other related factors could be a cause or a 'multiplier' of tensions within and between countries. Whether security threats arise from climate impacts or options for cooperation evolve does not depend only on the severity of the impacts themselves, but on social, economic, and institutional vulnerabilities or resilience as well as factors that influence local, national and international relations. However, an assessment of vulnerability and risks hinges on natural, socio-economic, and political conditions and responses, all of which are uncertain. Multidisciplinary research is needed to tackle the multi-facet complexity of climate change impacts on water resources in the Mediterranean and neighboring countries. This is particularly true in a region of overall data scarcity and poor data management and exchange structures. The current potential to develop appropriate regional adaptation measures towards climate change impacts suffers heavily from large uncertainties. These spread along a long chain of components, starting from the definition of emission scenarios to global and regional climate modeling to impact models and a subsequent variety of management options and adaptation strategies. Therefore, the 4-year FP7-project CLIMB (Climate induced changes on the hydrology of Mediterranean basins, GA: 244151) includes a major focus on the assessment and quantification of uncertainties. First, CLIMB employs a rigorous climate change model analysis, auditing the Global and Regional Climate Model data available through the ENSEMBLES and PRUDENCE initiatives. The audits lead to select the best regional performers as compared to observed values during the climatic reference period (1971- 2000). Specific bias correction and downscaling procedures are applied to provide the driving inputs and meet the demands of the subsequent impact models, transferring a future climate signal (2041-2070) into hydrological quantities at the catchment or landscape scale. However, very limited quantitative knowledge is as yet available about the role of hydrological model complexity for climate change impact assessment, where predictive power becomes more and more important and raises the demand for process-based and spatially explicit model types. Thus, CLIMB uses hydrological model ensembles to analyze the performance of existing models and works to identify the appropriate level of model complexity, and thus to determine the data specifications required to provide robust results in a climate change context. The presentation focuses on the CLIMB multi-level strategy to uncertainty assessment and highlights latest findings in some of the seven CLIMB case studies. In particular, the presentation will demonstrate the current constraints of hydro-meteorological data availability and processing and searches for solutions that can eventually be provided by integrating hydro-meteorology and ICT research communities.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

PubMed

Junk, J; Ulber, B; Vidal, S; Eickermann, M

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

NASA Astrophysics Data System (ADS)

Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Background sampling and transferability of species distribution model ensembles under climate change

NASA Astrophysics Data System (ADS)

Iturbide, Maialen; Bedia, Joaquín; Gutiérrez, José Manuel

2018-07-01

Species Distribution Models (SDMs) constitute an important tool to assist decision-making in environmental conservation and planning. A popular application of these models is the projection of species distributions under climate change conditions. Yet there are still a range of methodological SDM factors which limit the transferability of these models, contributing significantly to the overall uncertainty of the resulting projections. An important source of uncertainty often neglected in climate change studies comes from the use of background data (a.k.a. pseudo-absences) for model calibration. Here, we study the sensitivity to pseudo-absence sampling as a determinant factor for SDM stability and transferability under climate change conditions, focusing on European wide projections of Quercus robur as an illustrative case study. We explore the uncertainty in future projections derived from ten pseudo-absence realizations and three popular SDMs (GLM, Random Forest and MARS). The contribution of the pseudo-absence realization to the uncertainty was higher in peripheral regions and clearly differed among the tested SDMs in the whole study domain, being MARS the most sensitive - with projections differing up to a 40% for different realizations - and GLM the most stable. As a result we conclude that parsimonious SDMs are preferable in this context, avoiding complex methods (such as MARS) which may exhibit poor model transferability. Accounting for this new source of SDM-dependent uncertainty is crucial when forming multi-model ensembles to undertake climate change projections.

[Attaching importance to study on acute health risk assessment and adaptation of air pollution and climate change].

PubMed

Shi, X M

2017-03-10

Air pollution and climate change have become key environmental and public health problems around the world, which poses serious threat to human health. How to assess and mitigate the health risks and increase the adaptation of the public have become an urgent topic of research in this area. The six papers in this issue will provide important and rich information on design, analysis method, indicator selection and setting about acute health risk assessment and adaptation study of air pollution and climate change in China, reflecting the advanced conceptions of multi-center and area-specific study and multi-pollutant causing acute effect study. However, the number and type of the cities included in these studies were still limited. In future, researchers should further expand detailed multi-center and multi-area study coverage, conduct area specific predicting and early warning study and strengthen adaptation study.

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

Multi-model attribution of upper-ocean temperature changes using an isothermal approach.

PubMed

Weller, Evan; Min, Seung-Ki; Palmer, Matthew D; Lee, Donghyun; Yim, Bo Young; Yeh, Sang-Wook

2016-06-01

Both air-sea heat exchanges and changes in ocean advection have contributed to observed upper-ocean warming most evident in the late-twentieth century. However, it is predominantly via changes in air-sea heat fluxes that human-induced climate forcings, such as increasing greenhouse gases, and other natural factors such as volcanic aerosols, have influenced global ocean heat content. The present study builds on previous work using two different indicators of upper-ocean temperature changes for the detection of both anthropogenic and natural external climate forcings. Using simulations from phase 5 of the Coupled Model Intercomparison Project, we compare mean temperatures above a fixed isotherm with the more widely adopted approach of using a fixed depth. We present the first multi-model ensemble detection and attribution analysis using the fixed isotherm approach to robustly detect both anthropogenic and natural external influences on upper-ocean temperatures. Although contributions from multidecadal natural variability cannot be fully removed, both the large multi-model ensemble size and properties of the isotherm analysis reduce internal variability of the ocean, resulting in better observation-model comparison of temperature changes since the 1950s. We further show that the high temporal resolution afforded by the isotherm analysis is required to detect natural external influences such as volcanic cooling events in the upper-ocean because the radiative effect of volcanic forcings is short-lived.

Multi-model attribution of upper-ocean temperature changes using an isothermal approach

NASA Astrophysics Data System (ADS)

Weller, Evan; Min, Seung-Ki; Palmer, Matthew D.; Lee, Donghyun; Yim, Bo Young; Yeh, Sang-Wook

2016-06-01

Both air-sea heat exchanges and changes in ocean advection have contributed to observed upper-ocean warming most evident in the late-twentieth century. However, it is predominantly via changes in air-sea heat fluxes that human-induced climate forcings, such as increasing greenhouse gases, and other natural factors such as volcanic aerosols, have influenced global ocean heat content. The present study builds on previous work using two different indicators of upper-ocean temperature changes for the detection of both anthropogenic and natural external climate forcings. Using simulations from phase 5 of the Coupled Model Intercomparison Project, we compare mean temperatures above a fixed isotherm with the more widely adopted approach of using a fixed depth. We present the first multi-model ensemble detection and attribution analysis using the fixed isotherm approach to robustly detect both anthropogenic and natural external influences on upper-ocean temperatures. Although contributions from multidecadal natural variability cannot be fully removed, both the large multi-model ensemble size and properties of the isotherm analysis reduce internal variability of the ocean, resulting in better observation-model comparison of temperature changes since the 1950s. We further show that the high temporal resolution afforded by the isotherm analysis is required to detect natural external influences such as volcanic cooling events in the upper-ocean because the radiative effect of volcanic forcings is short-lived.

Climate induced changes on the hydrology of Mediterranean basins - assessing uncertainties and quantifying risks

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2014-05-01

According to current climate projections, the Mediterranean area is at high risk for severe changes in the hydrological budget and extremes. With innovative scientific measures, integrated hydrological modeling and novel field geophysical field monitoring techniques, the FP7 project CLIMB (Climate Induced Changes on the Hydrology of Mediterranean Basins; GA: 244151) assessed the impacts of climate change on the hydrology in seven basins in the Mediterranean area, in Italy, France, Turkey, Tunisia, Egypt and the Gaza Strip, and quantified uncertainties and risks for the main stakeholders of each test site. Intensive climate model auditing selected four regional climate models, whose data was bias corrected and downscaled to serve as climate forcing for a set of hydrological models in each site. The results of the multi-model hydro-climatic ensemble and socio-economic factor analysis were applied to develop a risk model building upon spatial vulnerability and risk assessment. Findings generally reveal an increasing risk for water resources management in the test sites, yet at different rates and severity in the investigated sectors, with highest impacts likely to occur in the transition months. Most important elements of this research include the following aspects: • Climate change contributes, yet in strong regional variation, to water scarcity in the Mediterranean; other factors, e.g. pollution or poor management practices, are regionally still dominant pressures on water resources. • Rain-fed agriculture needs to adapt to seasonal changes; stable or increasing productivity likely depends on additional irrigation. • Tourism could benefit in shoulder seasons, but may expect income losses in the summer peak season due to increasing heat stress. • Local & regional water managers and water users, lack, as yet, awareness of climate change induced risks; emerging focus areas are supplies of domestic drinking water, irrigation, hydropower and livestock. • Data and knowledge gaps in climate change impact and risk assessment are still widespread and ask for extended and coordinated monitoring programs. In order to discover, visualize and provide access the results of the project, the CLIMB-Portal has been established, serving as a platform for dissemination of project results, including communication and planning for local and regional stakeholders.

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia

2012-01-01

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

Spatiotemporal Exploration of Impacts of Coupled Climate and Socioeconomic Changes on Grassland Ecosystems (Invited)

NASA Astrophysics Data System (ADS)

Xie, Y.

2013-12-01

Although the coupled impacts of climate change and human adaptation on land cover change has been a prime research topic in recent years, a majority of reported efforts are examining the coupled effects of climate and socioeconomic factors qualitatively. Even though some are applying statistical methods, they often look into the impacts of coupled climate variations and socioeconomic transformations on land cover changes in a detached or sequential manner, or they handle socioeconomic influences indirectly through land use changes. Very few of them deal with the coupled effects concurrently through times and cross regions. We assimilate a big dataset of climate change, plant community growth condition, and socioeconomic transformation in Inner Mongolia of China. The study area consists of twelve types of plant communities, reflecting an east-to-west water-temperature gradient from moist meadow-type, to typical steppe-type and then to arid desert-type communities. The enhanced vegetation index (EVI), derived from MODIS at a 250 m resolution and 16-day intervals from May 8 to September 28 during 2000-2010, is adopted as a proxy for vegetation growth. The inter-annual and intra-annual changes of seven climate factors (barometric pressure, humidity, precipitation, sunlight hours, temperature, vapor pressure and wind speed) during the same period are synchronized with the EVI observations. Ten socioeconomic variables (urban population, urban GDP, rural GDP, grain output, livestock, fixed assets investment, local government revenue, per capita net income of farmers and pastoralists, the total length of highways, and rural population) are collected over 34 counties in the study area and during the same period. The GIS-based spatial database approach is adopted to integrate all of the above data into a big spatiotemporal dataset. We develop a multi-controlled panel-data regression model to investigate spatiotemporal changes of vegetation growth and their underlying causes of coupled climate and human impacts. We are able to examine the causal relationships between vegetation growth and coupled climate change and socioeconomic transformation either from the perspective of seasonal, annual, eco-regional, or by-county change, respectively. Most importantly, we can investigate the causal relations concurrently over seasons and years and across administrative or ecological regions. The findings confirm that climate changes and human socioeconomic activities jointly affect vegetation growth and its trajectory of change; these climate and human factors reveal varied levels of impacts (sunshine hour, humidity, vapor, grain production, precipitation, urban-GDP, livestock, and urban population in descending order positively affect vegetation growth, while rural-GDP and rural population negatively do); and the causal relationships show clear seasonal trends, annual fluctuations, and regional disparities, depending on a variety of ecologically and economically varying contextual factors. The potential of applying our model and approach in the Eurasian Steppes is very promising.

A multi-disciplinary approach to evaluate vulnerability and risks of pluvial floods under changing climate: the case study of the municipality of Venice (Italy).

NASA Astrophysics Data System (ADS)

Sperotto, Anna; Torresan, Silvia; Gallina, Valentina; Coppola, Erika; Critto, Andrea; Marcomini, Antonio

2015-04-01

Global climate change is expected to affect the intensity and frequency of extreme events (e.g. heat waves, drought, heavy precipitations events) leading to increasing natural disasters and damaging events (e.g. storms, pluvial floods and coastal flooding) worldwide. Especially in urban areas, disasters risks can be exacerbated by changes in exposure and vulnerability patterns (i.e. urbanization, population growth) and should be addressed by adopting a multi-disciplinary approach. A Regional Risk Assessment (RRA) methodology integrating climate and environmental sciences with bottom-up participative processes was developed and applied to the urban territory of the municipality of Venice in order to evaluate the potential consequences of climate change on pluvial flood risk in urban areas. Based on the consecutive analysis of hazard, exposure, vulnerability and risks, the RRA methodology is a screening risk tool to identify and prioritize major elements at risk (e.g. residential, commercial areas and infrastructures) and to localize sub-areas that are more likely to be affected by flood risk due to heavy precipitation events, in the future scenario (2041-2050). From the early stages of its development and application, the RRA followed a bottom-up approach to select and score site-specific vulnerability factors (e.g. slope, permeability of the soil, past flooded areas) and to consider the requests and perspectives of local stakeholders of the North Adriatic region, by means of interactive workshops, surveys and discussions. The main outputs of the assessment are risk and vulnerability maps and statistics aimed at increasing awareness about the potential effect of climate change on pluvial flood risks and at identifying hot-spot areas where future adaptation actions should be required to decrease physical-environmental vulnerabilities or building resilience and coping capacity of human society to climate change. The overall risk assessment methodology and the results of its application to the territory of the municipality of Venice will be here presented and discussed.

Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective.

PubMed

Sperotto, Anna; Molina, José-Luis; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2017-11-01

The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

Assessing the impacts of climate change and socio-economic changes on flow and phosphorus flux in the Ganga river system.

PubMed

Jin, L; Whitehead, P G; Sarkar, S; Sinha, R; Futter, M N; Butterfield, D; Caesar, J; Crossman, J

2015-06-01

Anthropogenic climate change has impacted and will continue to impact the natural environment and people around the world. Increasing temperatures and altered rainfall patterns combined with socio-economic factors such as population changes, land use changes and water transfers will affect flows and nutrient fluxes in river systems. The Ganga river, one of the largest river systems in the world, supports approximately 10% global population and more than 700 cities. Changes in the Ganga river system are likely to have a significant impact on water availability, water quality, aquatic habitats and people. In order to investigate these potential changes on the flow and water quality of the Ganga river, a multi-branch version of INCA Phosphorus (INCA-P) model has been applied to the entire river system. The model is used to quantify the impacts from a changing climate, population growth, additional agricultural land, pollution control and water transfers for 2041-2060 and 2080-2099. The results provide valuable information about potential effects of different management strategies on catchment water quality.

The CLUVA project: Climate-change scenarios and their impact on urban areas in Africa

NASA Astrophysics Data System (ADS)

Di Ruocco, Angela; Weets, Guy; Gasparini, Paolo; Jørgensen, Gertrud; Lindley, Sarah; Pauleit, Stephan; Vahed, Anwar; Schiano, Pasquale; Kabisch, Sigrun; Vedeld, Trond; Coly, Adrien; Tonye, Emmanuel; Touré, Hamidou; Kombe, Wilbard; Yeshitela, Kumelachew

2013-04-01

CLUVA (CLimate change and Urban Vulnerability in Africa; http://www.cluva.eu/) is a 3 years project, funded by the European Commission in 2010. Its main objective is the estimate of the impacts of climate changes in the next 40 years at urban scale in Africa. The mission of CLUVA is to develop methods and knowledge to assess risks cascading from climate-changes. It downscales IPCC climate projections to evaluate threats to selected African test cities; mainly floods, sea-level rise, droughts, heat waves and desertification. The project evaluates and links: social vulnerability; vulnerability of in-town ecosystems and urban-rural interfaces; vulnerability of urban built environment and lifelines; and related institutional and governance dimensions of adaptation. A multi-scale and multi-disciplinary quantitative, probabilistic, modelling is applied. CLUVA brings together climate experts, risk management experts, urban planners and social scientists with their African counterparts in an integrated research effort focusing on the improvement of the capacity of scientific institutions, local councils and civil society to cope with climate change. The CLUVA approach was set-up in the first year of the project and developed as follows: an ensemble of eight global projections of climate changes is produced for east and west Africa until 2050 considering the new IPCC (International Panel on Climate Changes; http://www.ipcc.ch/) scenarios. These are then downscaled to urban level, where territorial modeling is required to compute hazard effects on the vulnerable physical system (urban ecosystems, informal settlements, lifelines such as transportation and sewer networks) as well as on the social context, in defined time frames, and risk analysis is then employed to assess expected consequences. An investigation of the existing urban planning and governance systems and its interface with climate risks is performed. With the aid of the African partners, the developed approach is currently being applied to selected African case studies: Addis Ababa - Ethiopia; Dar es Salaam - Tanzania, Douala - Cameroun; Ouagadougou - Burkina Faso, St. Louis - Senegal. The poster will illustrate the CLUVA's framework to assess climate-change-related risks at an urban scale in Africa, and will report on the progresses of selected case studies to demonstrate feasibility of a multi-scale and multi-risk quantitative approach for risk management.

Inability of CMIP5 Climate Models to Simulate Recent Multi-decadal Climate Change in the Tropical Pacific.

NASA Astrophysics Data System (ADS)

Power, S.; Delage, F.; Kociuba, G.; Wang, G.; Smith, I.

2017-12-01

Observed 15-year surface temperature trends beginning 1998 or later have attracted a great deal of interest because of an apparent slowdown in the rate of global warming, and contrasts between climate model simulations and observations of such trends. Many studies have addressed the statistical significance of these relatively short trends, whether they indicate a possible bias in models and the implications for global warming generally. Here we analyse historical and projected changes in 38 CMIP5 climate models. All of the models simulate multi-decadal warming in the Pacific over the past half-century that exceeds observed values. This stark difference cannot be fully explained by observed, internal multi-decadal climate variability, even if allowance is made for an apparent tendency for models to underestimate internal multi-decadal variability in the Pacific. We also show that CMIP5 models are not able to simulate the magnitude of the strengthening of the Walker Circulation over the past thirty years. Some of the reasons for these major shortcomings in the ability of models to simulate multi-decadal variability in the Pacific, and the impact these findings have on our confidence in global 21st century projections, will be discussed.

Monitoring and Modeling the Tibetan Plateau's climate system and its impact on East Asia.

PubMed

Ma, Yaoming; Ma, Weiqiang; Zhong, Lei; Hu, Zeyong; Li, Maoshan; Zhu, Zhikun; Han, Cunbo; Wang, Binbin; Liu, Xin

2017-03-13

The Tibetan Plateau is an important water source in Asia. As the "Third Pole" of the Earth, the Tibetan Plateau has significant dynamic and thermal effects on East Asian climate patterns, the Asian monsoon process and atmospheric circulation in the Northern Hemisphere. However, little systematic knowledge is available regarding the changing climate system of the Tibetan Plateau and the mechanisms underlying its impact on East Asia. This study was based on "water-cryosphere-atmosphere-biology" multi-sphere interactions, primarily considering global climate change in relation to the Tibetan Plateau -East Asia climate system and its mechanisms. This study also analyzed the Tibetan Plateau to clarify global climate change by considering multi-sphere energy and water processes. Additionally, the impacts of climate change in East Asia and the associated impact mechanisms were revealed, and changes in water cycle processes and water conversion mechanisms were studied. The changes in surface thermal anomalies, vegetation, local circulation and the atmospheric heat source on the Tibetan Plateau were studied, specifically, their effects on the East Asian monsoon and energy balance mechanisms. Additionally, the relationships between heating mechanisms and monsoon changes were explored.

Monitoring and Modeling the Tibetan Plateau’s climate system and its impact on East Asia

PubMed Central

Ma, Yaoming; Ma, Weiqiang; Zhong, Lei; Hu, Zeyong; Li, Maoshan; Zhu, Zhikun; Han, Cunbo; Wang, Binbin; Liu, Xin

2017-01-01

The Tibetan Plateau is an important water source in Asia. As the “Third Pole” of the Earth, the Tibetan Plateau has significant dynamic and thermal effects on East Asian climate patterns, the Asian monsoon process and atmospheric circulation in the Northern Hemisphere. However, little systematic knowledge is available regarding the changing climate system of the Tibetan Plateau and the mechanisms underlying its impact on East Asia. This study was based on “water-cryosphere-atmosphere-biology” multi-sphere interactions, primarily considering global climate change in relation to the Tibetan Plateau -East Asia climate system and its mechanisms. This study also analyzed the Tibetan Plateau to clarify global climate change by considering multi-sphere energy and water processes. Additionally, the impacts of climate change in East Asia and the associated impact mechanisms were revealed, and changes in water cycle processes and water conversion mechanisms were studied. The changes in surface thermal anomalies, vegetation, local circulation and the atmospheric heat source on the Tibetan Plateau were studied, specifically, their effects on the East Asian monsoon and energy balance mechanisms. Additionally, the relationships between heating mechanisms and monsoon changes were explored. PMID:28287648

A Centroid Model of Species Distribution to Analyize Multi-directional Climate Change Finger Print in Avian Distribution in North America

NASA Astrophysics Data System (ADS)

Huang, Q.; Sauer, J.; Dubayah, R.

2015-12-01

Species distribution shift (or referred to as "fingerprint of climate change") as a primary mechanism to adapt climate change has been of great interest to ecologists and conservation practitioners. Recent meta-analyses have concluded that a wide range of animal and plant species are already shifting their distribution. However majority of the literature has focused on analyzing recent poleward and elevationally upward shift of species distribution. However if measured only in poleward shifts, the fingerprint of climate change will be underestimated significantly. In this study, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. We used the centroid approach to examine large number of species permanent resident species in North America and evaluated the dreiction and magnitude of their shifting distribution. To examine the inferential ability of mean temperature and precipitation, we test a hypothesis based on climate velocity theory that species would be more likely to shift their distribution or would shift with greater magnitude in in regions with high climate change velocity. For species with significant shifts of distribution, we establish a precipitation model and a temperature model to explain their change of abundance at the strata level. Two models which are composed of mean and extreme climate indices respectively are also established to test the influences of changes in gradual and extreme climate trends.

Impacts of climate change on Middle Eastern societies over the last 2700 years: new results from the Gejkar speleothem, Iraq

NASA Astrophysics Data System (ADS)

Flohr, Pascal; Fleitmann, Dominik; Bosomworth, Matt; Cheng, Hai; Sadekov, Aleksey; Matthews, Roger; Matthews, Wendy; Black, Stuart; Edwards, Lawrence

2016-04-01

Climatic and environmental changes are often cited as a major factor for past social, economic, and political changes. This is especially relevant in the semi-arid to arid Middle East, where, however, only few precisely dated, high-resolution climate records are available. Here we present new results from an up to annually resolved stalagmite from Gejkar Cave in the Kurdish Regional Government of Iraq region. Based on Uranium-series dating and annual layer counts, the record dates back ~2700 years, and its annual layer thickness and carbon and oxygen isotope profile appear indicative of precipitation and effective moisture. We also assess if observed decadal to multi-decadal shifts in precipitation are synchronous with socio-economic changes as observed in the archaeological and historical record in the wider Middle East over the last 2000 years, such as the largely prosperous Roman and Byzantine periods, the Seljuq invasion, and the decline of the Ottoman Empire.

RELATIVE EFFECTS OF OBSERVATIONALLY-NUDGED MODEL METEOROLOGY AND DOWN-SCALED GLOBAL CLIMATE MODEL METEOROLOGY ON BIOGENIC EMISSIONS FOR THE UNITED STATES

EPA Science Inventory

The United States Environmental Protection Agency (USEPA) and National Oceanic and Atmospheric Administration (NOAA) participate in a multi-agency examination of the effects of climate change through the U.S. Climate Change Science Program (CCSP, 2003). The EPA Global Change Rese...

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble

PubMed Central

Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork

2016-01-01

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble.

PubMed

Jiang, Mingkai; Felzer, Benjamin S; Sahagian, Dork

2016-07-18

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950-2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040-2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.

Climate change impact assessment on flow regime by incorporating spatial correlation and scenario uncertainty

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-07-01

Flooding risk is increasing in many parts of the world and may worsen under climate change conditions. The accuracy of predicting flooding risk relies on reasonable projection of meteorological data (especially rainfall) at the local scale. The current statistical downscaling approaches face the difficulty of projecting multi-site climate information for future conditions while conserving spatial information. This study presents a combined Long Ashton Research Station Weather Generator (LARS-WG) stochastic weather generator and multi-site rainfall simulator RainSim (CLWRS) approach to investigate flow regimes under future conditions in the Kootenay Watershed, Canada. To understand the uncertainty effect stemming from different scenarios, the climate output is fed into a hydrologic model. The results showed different variation trends of annual peak flows (in 2080-2099) based on different climate change scenarios and demonstrated that the hydrological impact would be driven by the interaction between snowmelt and peak flows. The proposed CLWRS approach is useful where there is a need for projection of potential climate change scenarios.

Bioclimatic predictors for supporting ecological applications in the conterminous United States

USGS Publications Warehouse

O'Donnel, Michael S.; Ignizio, Drew A.

2012-01-01

The U.S. Geological Survey (USGS) has developed climate indices, referred to as bioclimatic predictors, which highlight climate conditions best related to species physiology. A set of 20 bioclimatic predictors were developed as Geographic Information Systems (GIS) continuous raster surfaces for each year between 1895 and 2009. The Parameter-elevation Regression on Independent Slopes Model (PRISM) and down-scaled PRISM data, which included both averaged multi-year and averaged monthly climate summaries, was used to develop these multi-scale bioclimatic predictors. Bioclimatic predictors capture information about annual conditions (annual mean temperature, annual precipitation, annual range in temperature and precipitation), as well as seasonal mean climate conditions and intra-year seasonality (temperature of the coldest and warmest months, precipitation of the wettest and driest quarters). Examining climate over time is useful when quantifying the effects of climate changes on species' distributions for past, current, and forecasted scenarios. These data, which have not been readily available to scientists, can provide biologists and ecologists with relevant and multi-scaled climate data to augment research on the responses of species to changing climate conditions. The relationships established between species demographics and distributions with bioclimatic predictors can inform land managers of climatic effects on species during decisionmaking processes.

NASA Tools for Climate Impacts on Water Resources

NASA Technical Reports Server (NTRS)

Toll, David; Doorn, Brad

2010-01-01

Climate and environmental change are expected to fundamentally alter the nation's hydrological cycle and water availability. Satellites provide global or near-global coverage using instruments, allowing for consistent, well-calibrated, and equivalent-quality data of the Earth system. A major goal for NASA climate and environmental change research is to create multi-instrument data sets to span the multi-decadal time scales of climate change and to combine these data with those from modeling and surface-based observing systems to improve process understanding and predictions. NASA and Earth science data and analyses will ultimately enable more accurate climate prediction, and characterization of uncertainties. NASA's Applied Sciences Program works with other groups, including other federal agencies, to transition demonstrated observational capabilities to operational capabilities. A summary of some of NASA tools for improved water resources management will be presented.

Albedo feedbacks to future climate via climate change impacts on dryland biocrusts.

PubMed

Rutherford, William A; Painter, Thomas H; Ferrenberg, Scott; Belnap, Jayne; Okin, Gregory S; Flagg, Cody; Reed, Sasha C

2017-03-10

Drylands represent the planet's largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness-changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.

Albedo feedbacks to future climate via climate change impacts on dryland biocrusts

NASA Astrophysics Data System (ADS)

Rutherford, William A.; Painter, Thomas H.; Ferrenberg, Scott; Belnap, Jayne; Okin, Gregory S.; Flagg, Cody; Reed, Sasha C.

2017-03-01

Drylands represent the planet’s largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness—changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.

Albedo feedbacks to future climate via climate change impacts on dryland biocrusts

USGS Publications Warehouse

Rutherford, William A.; Painter, Thomas H.; Ferrenberg, Scott; Belnap, Jayne; Okin, Gregory S.; Flagg, Cody B.; Reed, Sasha C.

2017-01-01

Drylands represent the planet’s largest terrestrial biome and evidence suggests these landscapes have large potential for creating feedbacks to future climate. Recent studies also indicate that dryland ecosystems are responding markedly to climate change. Biological soil crusts (biocrusts) ‒ soil surface communities of lichens, mosses, and/or cyanobacteria ‒ comprise up to 70% of dryland cover and help govern fundamental ecosystem functions, including soil stabilization and carbon uptake. Drylands are expected to experience significant changes in temperature and precipitation regimes, and such alterations may impact biocrust communities by promoting rapid mortality of foundational species. In turn, biocrust community shifts affect land surface cover and roughness—changes that can dramatically alter albedo. We tested this hypothesis in a full-factorial warming (+4 °C above ambient) and altered precipitation (increased frequency of 1.2 mm monsoon-type watering events) experiment on the Colorado Plateau, USA. We quantified changes in shortwave albedo via multi-angle, solar-reflectance measurements. Warming and watering treatments each led to large increases in albedo (>30%). This increase was driven by biophysical factors related to treatment effects on cyanobacteria cover and soil surface roughness following treatment-induced moss and lichen mortality. A rise in dryland surface albedo may represent a previously unidentified feedback to future climate.

Long-term variability in the water budget and its controls in an oak-dominated temperate forest

Treesearch

Jing Xie; Ge Sun; Hou-Sen Chu; Junguo Liu; Steven G. McNulty; Asko Noormets; Ranjeet John; Zutao Ouyang; Tianshan Zha; Haitao Li; Wenbin Guan; Jiquan Chen

2014-01-01

Water availability is one of the key environmental factors that control ecosystem functions in temperate forests. Changing climate is likely to alter the ecohydrology and other ecosystem processes, which affect forest structures and functions. We constructed a multi-year water budget (2004–2010) and quantified environmental controls on an evapotranspiration (ET) in a...

Our Changing Climate: A Brand New Way to Study Climate Science

NASA Astrophysics Data System (ADS)

Brey, J. A.; Kauffman, C.; Geer, I.; Nugnes, K. A.; Mills, E. W.

2014-12-01

Earth's climate is inherently variable, but is currently changing at rates unprecedented in recent Earth history. Human activity plays a major role in this change and is projected to do so well into the future. This is the stance taken in Our Changing Climate, the brand new climate science ebook from the American Meteorological Society (AMS). Our Changing Climate investigates Earth's climate system, explores humans' impact on it, and identifies actions needed in response to climate change. Released in August 2014, Our Changing Climate is the result of a year's worth of intensive research and writing, incorporating the latest scientific understandings of Earth's climate system from reports such as IPCC AR5 and the Third National Climate Assessment. To encourage additional exploration of climate science information, scientific literature, from which chapter content was derived, is cited at the conclusion of each chapter. In addition, Topic In Depth sections appear throughout each chapter and lead to more extensive information related to various topics. For example, a Topic In Depth in Chapter 11 describes the effect of climate extremes on ranching enterprises in Nebraska. Climate science is multi-disciplinary and therefore Our Changing Climate covers a breadth of topics. From understanding basic statistics and geospatial tools used to investigate Earth's climate system to examining the psychological and financial reasons behind climate change denial, the AMS believes that a multi-disciplinary approach is the most effective way to increase climate literacy. Our Changing Climate is part of the AMS Climate Studies course which is intended for undergraduate-level students. Other course materials include an eInvestigations Manual and access to the RealTime Climate Portal, both of which provide weekly activities corresponding to that week's chapter content. The RealTime Climate Portal also has links to climate data as well as societal interactions and climate policy websites to spur further interest. Faculty support materials are also provided. AMS Climate Studies has been licensed by 130 institutions since Fall 2010. Our Changing Climate reveals the impact that each of us has on the climate. With this understanding come choices and actions for a more sustainable future.

Intersections of downscaling, the ethics of climate services, and regional research grand challenges.

NASA Astrophysics Data System (ADS)

Hewitson, B.; Jack, C. D.; Gutowski, W. J., Jr.

2014-12-01

Possibly the leading complication for users of climate information for policy and adaptation is the confusing mix of contrasting data sets that offer widely differing (and often times fundamentally contradictory) indications of the magnitude and direction of past and future regional climate change. In this light, the most pressing scientific-societal challenge is the need to find new ways to understand the sources of conflicting messages from multi-model, multi-method and multi-scale disparities, to develop and implement new analytical methodologies to address this difficulty and so to advance the interpretation and communication of robust climate information to decision makers. Compounding this challenge is the growth of climate services which, in view of the confusing mix of climate change messages, raises serious concerns as to the ethics of communication and dissemination of regional climate change data.The Working Group on Regional Climate (WGRC) of the World Climate Research Program (WCRP) oversees the CORDEX downscaling program which offers a systematic approach to compare the CMIP5 GCMs alongside RCMs and Empirical-statistical (ESD) downscaling within a common experimental design, and which facilitates the evaluation and assessment of the relative information content and sources of error. Using results from the CORDEX RCM and ESD evaluation experiment, and set against the regional messages from the CMIP5 GCMs, we examine the differing messages that arise from each data source. These are then considered in terms of the implications of consequence if each data source were to be independently adopted in a real world use-case scenario. This is then cast in the context of the emerging developments on the distillation dilemma - where the pressing need is for multi-method integration - and how this relates to the WCRP regional research grand challenges.

Grand challenges in understanding the interplay of climate and land changes

DOE PAGES

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; ...

2017-03-28

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Grand challenges in understanding the interplay of climate and land changes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

A scenario framework to explore the future migration and adaptation in deltas: A multi-scale and participatory approach

NASA Astrophysics Data System (ADS)

Kebede, Abiy S.; Nicholls, Robert J.; Allan, Andrew; Arto, Inaki; Cazcarro, Ignacio; Fernandes, Jose A.; Hill, Chris T.; Hutton, Craig W.; Kay, Susan; Lawn, Jon; Lazar, Attila N.; Whitehead, Paul W.

2017-04-01

Coastal deltas are home for over 500 million people globally, and they have been identified as one of the most vulnerable coastal environments during the 21st century. They are susceptible to multiple climatic (e.g., sea-level rise, storm surges, change in temperature and precipitation) and socio-economic (e.g., human-induced subsidence, population and urbanisation changes, GDP growth) drivers of change. These drivers also operate at multiple scales, ranging from local to global and short- to long-term. This highlights the complex challenges deltas face in terms of both their long-term sustainability as well as the well-being of their residents and the health of ecosystems that support the livelihood of large (often very poor) population under uncertain changing conditions. A holistic understanding of these challenges and the potential impacts of future climate and socio-economic changes is central for devising robust adaptation policies. Scenario analysis has long been identified as a strategic management tool to explore future climate change and its impacts for supporting robust decision-making under uncertainty. This work presents the overall scenario framework, methodology, and processes adopted for the development of scenarios in the DECCMA* project. DECCMA is analysing the future of three deltas in South Asia and West Africa: (i) the Ganges-Brahmaputra-Meghna (GBM) delta (Bangladesh/India), (ii) the Mahanadi delta (India), and (iii) the Volta delta (Ghana). This includes comparisons between these three deltas. Hence, the scenario framework comprises a multi-scale hybrid approach, with six levels of scenario considerations: (i) global (climate change, e.g., sea-level rise, temperature change; and socio-economic assumptions, e.g., population and urbanisation changes, GDP growth); (ii) regional catchments (e.g., river flow modelling), (iii) regional seas (e.g., fisheries modelling), (iv) regional politics (e.g., transboundary disputes), (v) national (e.g., socio-economic factors), and (vi) delta-scale (e.g., future adaptation and migration policies) scenarios. The framework includes and combines expert-based and participatory approaches and provides improved specification of the role of scenarios to analyse the future state of adaptation and migration across the three deltas. It facilitates the development of appropriate and consistent endogenous and exogenous scenario futures: (i) at the delta-scale, (ii) across all deltas, and (iii) with wider climate change, environmental change, and adaptation & migration research. Key words: Coastal deltas, sea-level rise, migration and adaptation, multi-scale scenarios, participatory approach *DECCMA (Deltas, Vulnerability & Climate Change: Migration & Adaptation) project is part of the Collaborative ADAPTATION Research Initiative in Africa and Asia (CARIAA), with financial support from the UK Government's Department for International Development (DFID) and the International Development Research Centre (IDRC), Canada.

Projected changes in precipitation intensity and frequency over complex topography: a multi-model perspective

NASA Astrophysics Data System (ADS)

Fischer, Andreas; Keller, Denise; Liniger, Mark; Rajczak, Jan; Schär, Christoph; Appenzeller, Christof

2014-05-01

Fundamental changes in the hydrological cycle are expected in a future warmer climate. This is of particular relevance for the Alpine region, as a source and reservoir of several major rivers in Europe and being prone to extreme events such as floodings. For this region, climate change assessments based on the ENSEMBLES regional climate models (RCMs) project a significant decrease in summer mean precipitation under the A1B emission scenario by the mid-to-end of this century, while winter mean precipitation is expected to slightly rise. From an impact perspective, projected changes in seasonal means, however, are often insufficient to adequately address the multifaceted challenges of climate change adaptation. In this study, we revisit the full matrix of the ENSEMBLES RCM projections regarding changes in frequency and intensity, precipitation-type (convective versus stratiform) and temporal structure (wet/dry spells and transition probabilities) over Switzerland and surroundings. As proxies for raintype changes, we rely on the model parameterized convective and large-scale precipitation components. Part of the analysis involves a Bayesian multi-model combination algorithm to infer changes from the multi-model ensemble. The analysis suggests a summer drying that evolves altitude-specific: over low-land regions it is associated with wet-day frequency decreases of convective and large-scale precipitation, while over elevated regions it is primarily associated with a decline in large-scale precipitation only. As a consequence, almost all the models project an increase in the convective fraction at elevated Alpine altitudes. The decrease in the number of wet days during summer is accompanied by decreases (increases) in multi-day wet (dry) spells. This shift in multi-day episodes also lowers the likelihood of short dry spell occurrence in all of the models. For spring and autumn the combined multi-model projections indicate higher mean precipitation intensity north of the Alps, while a similar tendency is expected for the winter season over most of Switzerland.

Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia

NASA Astrophysics Data System (ADS)

Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

2016-08-01

Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia.

PubMed

Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

2016-08-01

Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

Climate impacts on human livelihoods at 1.5° and 2° of warming

NASA Astrophysics Data System (ADS)

Lissner, Tabea

2017-04-01

The measurement of impacts of climate change on socio-economic systems remains challenging and especially multi-dimensional outcome measures remain scarce. Climate impacts can directly affect many dimensions of human livelihoods, which cannot be addressed by monetary assessments alone. Multi-dimensional measures are essential in order to understand the full range of consequences of climate change and to understand the costs that higher levels of warming may have, not only in economic terms, but also in terms of non-market impacts on human livelihood. The AHEAD framework aims at measuring "Adequate Human livelihood conditions for wEll-being And Development" in a multi-dimensional framework, allowing to focus on resources and conditions which are a requirement to attain well-being. In this contribution we build on previous implementations of AHEAD and focus on differences in climate impacts at 1.5° and 2° of warming in order to improve our understanding of the societal consequences of these different warming levels.

A multi-disciplinary approach for the integrated assessment of water alterations under climate change

NASA Astrophysics Data System (ADS)

Sperotto, Anna; Torresan, Silvia; Molina, Jose Luis; Pulido Velazquez, Manuel; Critto, Andrea; Marcomini, Antonio

2017-04-01

Understanding the co-evolution and interrelations between natural and human pressures on water systems is required to ensure a sustainable management of resources under uncertain climate change conditions. To pursue multi-disciplinary research is therefore necessary to consider the multiplicity of stressors affecting water resources, take into account alternative perspectives (i.e. social, economic and environmental objective and priorities) and deal with uncertainty which characterize climate change scenarios. However, approaches commonly adopted in water quality assessment are predominantly mono-disciplinary, single-stressors oriented and apply concepts and models specific of different academic disciplines (e.g. physics, hydrology, ecology, sociology, economy) which, in fact, seldom shed their conceptual blinders failing to provide truly integrated results. In this context, the paper discusses the benefits and limits of adopting a multi-disciplinary approach where different knowledge domains collaborate and quantitative and qualitative information, coming from multiple conceptual and model-based research, are integrated in a harmonic manner. Specifically, Bayesian Networks are used as meta-modelling tool for structuring and combining the probabilistic information available in existing hydrological models, climate change and land use projections, historical observations and expert opinion. The developed network allows to perform a stochastic multi-risk assessment considering the interlacing between climate (i.e. irregularities in water regime) and land use changes (i.e. agriculture, urbanization) and their cascading impacts on water quality parameters (i.e. nutrients loadings). Main objective of the model is the development of multi-risk scenarios to assess and communicate the probability of not meeting a "Good chemical water status" over future timeframe taking into account projected climatic and not climatic conditions. The outcomes are finally used to identify tradeoffs between different water uses and perspectives, thus promoting the implementation of best practices for adaptation and management with ancillary co-benefits and cross-sectoral implications (i.e. tourism, fishing, biodiversity). Some preliminary results, describing the application of the model in the Dese-Zero river estuary, one of the main tributaries of the Venice Lagoon in Italy, will be here presented and discussed.

Adapting crop rotations to climate change in regional impact modelling assessments.

PubMed

Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

2018-03-01

The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used to develop improved regional impact assessments for situations where multi-crop rotations better represent predominant agricultural systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Modelling impacts of climate change on arable crop diseases: progress, challenges and applications.

PubMed

Newbery, Fay; Qi, Aiming; Fitt, Bruce Dl

2016-08-01

Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembles in climate change modelling and crop modelling is contributing towards measures of uncertainty in climate change impact projections but other aspects of uncertainty remain largely unexplored. Impact assessments are still concentrated on few crops and few diseases but are beginning to investigate arable crop disease dynamics at the landscape level. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tracing Multi-Scale Climate Change at Low Latitude from Glacier Shrinkage

NASA Astrophysics Data System (ADS)

Moelg, T.; Cullen, N. J.; Hardy, D. R.; Kaser, G.

2009-12-01

Significant shrinkage of glaciers on top of Africa's highest mountain (Kilimanjaro, 5895 m a.s.l.) has been observed between the late 19th century and the present. Multi-year data from our automatic weather station on the largest remaining slope glacier at 5873 m allow us to force and verify a process-based distributed glacier mass balance model. This generates insights into energy and mass fluxes at the glacier-atmosphere interface, their feedbacks, and how they are linked to atmospheric conditions. By means of numerical atmospheric modeling and global climate model simulations, we explore the linkages of the local climate in Kilimanjaro's summit zone to larger-scale climate dynamics - which suggests a causal connection between Indian Ocean dynamics, mesoscale mountain circulation, and glacier mass balance. Based on this knowledge, the verified mass balance model is used for backward modeling of the steady-state glacier extent observed in the 19th century, which yields the characteristics of local climate change between that time and the present (30-45% less precipitation, 0.1-0.3 hPa less water vapor pressure, 2-4 percentage units less cloud cover at present). Our multi-scale approach provides an important contribution, from a cryospheric viewpoint, to the understanding of how large-scale climate change propagates to the tropical free troposphere. Ongoing work in this context targets the millennium-scale relation between large-scale climate and glacier behavior (by downscaling precipitation), and the possible effects of regional anthropogenic activities (land use change) on glacier mass balance.

Multi-scale controls of historical forest-fire regimes: new insights from fire-scar networks

Treesearch

Donald A. Falk; Emily K. Heyerdahl; Peter M. Brown; Calvin Farris; Peter Z. Fule; Donald McKenzie; Thomas W. Swetnam; Alan H. Taylor; Megan L. Van Horne

2011-01-01

Anticipating future forest-fire regimes under changing climate requires that scientists and natural resource managers understand the factors that control fire across space and time. Fire scars—proxy records of fires, formed in the growth rings of long-lived trees—provide an annually accurate window into past low-severity fire regimes. In western North America, networks...

[Lake eutrophication modeling in considering climatic factors change: a review].

PubMed

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

Predicting the Impact of Climate Change on Threatened Species in UK Waters

PubMed Central

Jones, Miranda C.; Dye, Stephen R.; Fernandes, Jose A.; Frölicher, Thomas L.; Pinnegar, John K.; Warren, Rachel; Cheung, William W. L.

2013-01-01

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina). PMID:23349829

Predicting the impact of climate change on threatened species in UK waters.

PubMed

Jones, Miranda C; Dye, Stephen R; Fernandes, Jose A; Frölicher, Thomas L; Pinnegar, John K; Warren, Rachel; Cheung, William W L

2013-01-01

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina).

Multi-objective Optimization for the Robust Performance of Drinking Water Treatment Plants under Climate Change and Climate Extremes

NASA Astrophysics Data System (ADS)

Raseman, W. J.; Kasprzyk, J. R.; Rosario-Ortiz, F.; Summers, R. S.; Stewart, J.; Livneh, B.

2016-12-01

To promote public health, the United States Environmental Protection Agency (US EPA), and similar entities around the world enact strict laws to regulate drinking water quality. These laws, such as the Stage 1 and 2 Disinfectants and Disinfection Byproducts (D/DBP) Rules, come at a cost to water treatment plants (WTPs) which must alter their operations and designs to meet more stringent standards and the regulation of new contaminants of concern. Moreover, external factors such as changing influent water quality due to climate extremes and climate change, may force WTPs to adapt their treatment methods. To grapple with these issues, decision support systems (DSSs) have been developed to aid WTP operation and planning. However, there is a critical need to better address long-term decision making for WTPs. In this poster, we propose a DSS framework for WTPs for long-term planning, which improves upon the current treatment of deep uncertainties within the overall potable water system including the impact of climate on influent water quality and uncertainties in treatment process efficiencies. We present preliminary results exploring how a multi-objective evolutionary algorithm (MOEA) search can be coupled with models of WTP processes to identify high-performing plans for their design and operation. This coupled simulation-optimization technique uses Borg MOEA, an auto-adaptive algorithm, and the Water Treatment Plant Model, a simulation model developed by the US EPA to assist in creating the D/DBP Rules. Additionally, Monte Carlo sampling methods were used to study the impact of uncertainty of influent water quality on WTP decision-making and generate plans for robust WTP performance.

Warming reduces carbon losses from grassland exposed to elevated atmospheric carbon dioxide.

PubMed

Pendall, Elise; Heisler-White, Jana L; Williams, David G; Dijkstra, Feike A; Carrillo, Yolima; Morgan, Jack A; Lecain, Daniel R

2013-01-01

The flux of carbon dioxide (CO2) between terrestrial ecosystems and the atmosphere may ameliorate or exacerbate climate change, depending on the relative responses of ecosystem photosynthesis and respiration to warming temperatures, rising atmospheric CO2, and altered precipitation. The combined effect of these global change factors is especially uncertain because of their potential for interactions and indirectly mediated conditions such as soil moisture. Here, we present observations of CO2 fluxes from a multi-factor experiment in semi-arid grassland that suggests a potentially strong climate - carbon cycle feedback under combined elevated [CO2] and warming. Elevated [CO2] alone, and in combination with warming, enhanced ecosystem respiration to a greater extent than photosynthesis, resulting in net C loss over four years. The effect of warming was to reduce respiration especially during years of below-average precipitation, by partially offsetting the effect of elevated [CO2] on soil moisture and C cycling. Carbon losses were explained partly by stimulated decomposition of soil organic matter with elevated [CO2]. The climate - carbon cycle feedback observed in this semiarid grassland was mediated by soil water content, which was reduced by warming and increased by elevated [CO2]. Ecosystem models should incorporate direct and indirect effects of climate change on soil water content in order to accurately predict terrestrial feedbacks and long-term storage of C in soil.

Warming Reduces Carbon Losses from Grassland Exposed to Elevated Atmospheric Carbon Dioxide

PubMed Central

Pendall, Elise; Heisler-White, Jana L.; Williams, David G.; Dijkstra, Feike A.; Carrillo, Yolima; Morgan, Jack A.; LeCain, Daniel R.

2013-01-01

The flux of carbon dioxide (CO2) between terrestrial ecosystems and the atmosphere may ameliorate or exacerbate climate change, depending on the relative responses of ecosystem photosynthesis and respiration to warming temperatures, rising atmospheric CO2, and altered precipitation. The combined effect of these global change factors is especially uncertain because of their potential for interactions and indirectly mediated conditions such as soil moisture. Here, we present observations of CO2 fluxes from a multi-factor experiment in semi-arid grassland that suggests a potentially strong climate – carbon cycle feedback under combined elevated [CO2] and warming. Elevated [CO2] alone, and in combination with warming, enhanced ecosystem respiration to a greater extent than photosynthesis, resulting in net C loss over four years. The effect of warming was to reduce respiration especially during years of below-average precipitation, by partially offsetting the effect of elevated [CO2] on soil moisture and C cycling. Carbon losses were explained partly by stimulated decomposition of soil organic matter with elevated [CO2]. The climate – carbon cycle feedback observed in this semiarid grassland was mediated by soil water content, which was reduced by warming and increased by elevated [CO2]. Ecosystem models should incorporate direct and indirect effects of climate change on soil water content in order to accurately predict terrestrial feedbacks and long-term storage of C in soil. PMID:23977180

Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

USDA-ARS?s Scientific Manuscript database

Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

Analysis of Present Day and Future OH and Methane Lifetime in the ACCMIP Simulations

NASA Technical Reports Server (NTRS)

Voulgarakis, A.; Naik, V.; Lamarque, J. -F.; Shindell, D. T.; Young, P. J.; Prather, M. J.; Wild, O.; Field, R. D.; Bergmann, D.; Cameron-Smith P.;

75 FR 27990 - Mid-Atlantic Fishery Management Council (MAFMC); Public Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-19

... presentation on Climate Change and Responses in a Coupled Marine System; the Mid-Atlantic surfclam (MASC) model is being developed as part of a multi-disciplinary study looking at adaptation to climate change in a...

Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

NASA Astrophysics Data System (ADS)

Böttinger, Michael; Eyring, Veronika; Lauer, Axel; Meier-Fleischer, Karin

2017-04-01

Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason, E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S., and Williams, K. D.: ESMValTool (v1.0) - a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP, Geosci. Model Dev., 9, 1747-1802, doi:10.5194/gmd-9-1747-2016, 2016.

Plant developmental responses to climate change.

PubMed

Gray, Sharon B; Brady, Siobhan M

2016-11-01

Climate change is multi-faceted, and includes changing concentrations of greenhouse gases in the atmosphere, rising temperatures, changes in precipitation patterns, and increasing frequency of extreme weather events. Here, we focus on the effects of rising atmospheric CO 2 concentrations, rising temperature, and drought stress and their interaction on plant developmental processes in leaves, roots, and in reproductive structures. While in some cases these responses are conserved across species, such as decreased root elongation, perturbation of root growth angle and reduced seed yield in response to drought, or an increase in root biomass in shallow soil in response to elevated CO 2 , most responses are variable within and between species and are dependent on developmental stage. These variable responses include species-specific thresholds that arrest development of reproductive structures, reduce root growth rate and the rate of leaf initiation and expansion in response to elevated temperature. Leaf developmental responses to elevated CO 2 vary by cell type and by species. Variability also exists between C 3 and C 4 species in response to elevated CO 2 , especially in terms of growth and seed yield stimulation. At the molecular level, significantly less is understood regarding conservation and variability in molecular mechanisms underlying these traits. Abscisic acid-mediated changes in cell wall expansion likely underlie reductions in growth rate in response to drought, and changes in known regulators of flowering time likely underlie altered reproductive transitions in response to elevated temperature and CO 2 . Genes that underlie most other organ or tissue-level responses have largely only been identified in a single species in response to a single stress and their level of conservation is unknown. We conclude that there is a need for further research regarding the molecular mechanisms of plant developmental responses to climate change factors in general, and that this lack of data is particularly prevalent in the case of interactive effects of multiple climate change factors. As future growing conditions will likely expose plants to multiple climate change factors simultaneously, with a sum negative influence on global agriculture, further research in this area is critical. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

MISST: The Multi-Sensor Improved Sea Surface Temperature Project

DTIC Science & Technology

2009-06-01

climate change studies, fisheries management, and a wide range of other applications. Measurements are taken by several satellites carrying infrared and...TEMPERATURE PROJECT ABSTRACT. Sea surface temperature (SST) measurements are vital to global weather prediction, climate change studies, fisheries management...important variables related to the global ocean-atmosphere system. It is a key indicator of climate change , is widely applied to studies of upper

Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

USGS Publications Warehouse

Renwick, Katherine M.; Curtis, Caroline; Kleinhesselink, Andrew R.; Schlaepfer, Daniel R.; Bradley, Bethany A.; Aldridge, Cameron L.; Poulter, Benjamin; Adler, Peter B.

2018-01-01

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

When climate science became climate politics: British media representations of climate change in 1988.

PubMed

Jaspal, Rusi; Nerlich, Brigitte

2014-02-01

Climate change has become a pressing environmental concern for scientists, social commentators and politicians. Previous social science research has explored media representations of climate change in various temporal and geographical contexts. Through the lens of Social Representations Theory, this article provides a detailed qualitative thematic analysis of media representations of climate change in the 1988 British broadsheet press, given that this year constitutes an important juncture in this transition of climate change from the domain of science to that of the socio-political sphere. The following themes are outlined: (i) "Climate change: a multi-faceted threat"; (ii) "Collectivisation of threat"; (iii) "Climate change and the attribution of blame"; and (iv) "Speculative solutions to a complex socio-environmental problem." The article provides detailed empirical insights into the "starting-point" for present-day disputes concerning climate change and lays the theoretical foundations for tracking the continuities and discontinuities characterising social representations of climate change in the future.

Forecasting regional grassland and shrubland responses to directional changes in climate using multi-year dry or wet periods

USDA-ARS?s Scientific Manuscript database

Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Although air temperatures are increasing, the magnitude and direction of change in precipitation (increase or decrease) are uncertain for many sites. Given that water availability is the primary driver...

Forecasting regional grassland and shrubland responses to directional changes in climate using multi-year dry or wet period

USDA-ARS?s Scientific Manuscript database

Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Although air temperatures are increasing, the magnitude and direction of change in precipitation (increase or decrease) are uncertain for many sites. Given that water availability is the primary driver...

Synchronous multi-decadal climate variability of the whole Pacific areas revealed in tree rings since 1567

NASA Astrophysics Data System (ADS)

Fang, Keyan; Cook, Edward; Guo, Zhengtang; Chen, Deliang; Ou, Tinghai; Zhao, Yan

2018-02-01

Oceanic and atmospheric patterns play a crucial role in modulating climate variability from interannual to multi-decadal timescales by causing large-scale co-varying climate changes. The brevity of the existing instrumental records hinders the ability to recognize climate patterns before the industrial era, which can be alleviated using proxies. Unfortunately, proxy based reconstructions of oceanic and atmospheric modes of the past millennia often have modest agreements with each other before the instrumental period, raising questions about the robustness of the reconstructions. To ensure the stability of climate signals in proxy data through time, we first identified tree-ring datasets from distant regions containing coherent variations in Asia and North America, and then interpreted their climate information. We found that the multi-decadal covarying climate patterns of the middle and high latitudinal regions around the northern Pacific Ocean agreed quite well with the climate reconstructions of the tropical and southern Pacific areas. This indicates a synchronous variability at the multi-decadal timescale of the past 430 years for the entire Pacific Ocean. This pattern is closely linked to the dominant mode of the Pacific sea surface temperature (SST) after removing the warming trend. This Pacific multi-decadal SST variability resembles the Interdecadal Pacific Oscillation.

Uncertainty of future projections of species distributions in mountainous regions.

PubMed

Tang, Ying; Winkler, Julie A; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution.

Uncertainty of future projections of species distributions in mountainous regions

PubMed Central

Tang, Ying; Viña, Andrés; Liu, Jianguo; Zhang, Yuanbin; Zhang, Xiaofeng; Li, Xiaohong; Wang, Fang; Zhang, Jindong; Zhao, Zhiqiang

2018-01-01

Multiple factors introduce uncertainty into projections of species distributions under climate change. The uncertainty introduced by the choice of baseline climate information used to calibrate a species distribution model and to downscale global climate model (GCM) simulations to a finer spatial resolution is a particular concern for mountainous regions, as the spatial resolution of climate observing networks is often insufficient to detect the steep climatic gradients in these areas. Using the maximum entropy (MaxEnt) modeling framework together with occurrence data on 21 understory bamboo species distributed across the mountainous geographic range of the Giant Panda, we examined the differences in projected species distributions obtained from two contrasting sources of baseline climate information, one derived from spatial interpolation of coarse-scale station observations and the other derived from fine-spatial resolution satellite measurements. For each bamboo species, the MaxEnt model was calibrated separately for the two datasets and applied to 17 GCM simulations downscaled using the delta method. Greater differences in the projected spatial distributions of the bamboo species were observed for the models calibrated using the different baseline datasets than between the different downscaled GCM simulations for the same calibration. In terms of the projected future climatically-suitable area by species, quantification using a multi-factor analysis of variance suggested that the sum of the variance explained by the baseline climate dataset used for model calibration and the interaction between the baseline climate data and the GCM simulation via downscaling accounted for, on average, 40% of the total variation among the future projections. Our analyses illustrate that the combined use of gridded datasets developed from station observations and satellite measurements can help estimate the uncertainty introduced by the choice of baseline climate information to the projected changes in species distribution. PMID:29320501

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with a recently published study on the TOE for mean and heavy precipitation trends in Europe. In some regions trends emerge only late in the 21st century or even later, suggesting that in these regions adaptation to internal variability rather than to climate change is required. Yet in other regions the climate change signal is strong, urging for timely adaptation. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

Some factors associated with change in patient-centredness of student nurses during the Common Foundation Programme in Nursing.

PubMed

Rolfe, G

1994-10-01

This longitudinal study examines the changes in patient-centredness of a group of student nurses during their Common Foundation Programme in Nursing, and attempts to explore some of the social, psychological and educational factors which might be associated with such change. The Patient-centredness Multi-choice Questionnaire (PMQX) was administered to a sample of 267 student nurses on commencement and completion of their Common Foundation Programme in Nursing, and significant positive as well as negative changes in PMQX scores were found, although the mean scores for the sample were unchanged. A number of factors were found to be associated with high levels of patient-centredness on commencement of the course, including marital status, age, and radicalism. Positive change in patient-centredness during the CFP was associated with a variety of variables such as class size, a student-centred climate and a tenderminded attitude. Other factors, such as psychological stability and extroversion, were associated with both increase and decrease in patient-centredness during the CFP.

Climate Change Impact Uncertainties for Maize in Panama: Farm Information, Climate Projections, and Yield Sensitivities

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Cecil, L. Dewayne; Horton, Radley M.; Gordon, Roman; McCollum, Raymond (Brown, Douglas); Brown, Douglas; Killough, Brian; Goldberg, Richard; Greeley, Adam P.; Rosenzweig, Cynthia

2011-01-01

We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO (sub 2) concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors is reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields. Uncertainty around General Circulation Model (GCM)s' projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large inter-annual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the important uncertainties behind the selection of climate change metrics and their performance against more complex process-based crop model simulations, revealing a danger in relying only on long-term mean quantities for crop impact assessment.

Central Tropical Pacific Variability And ENSO Response To Changing Climate Boundary Conditions: Evidence From Individual Line Island Foraminifera

NASA Astrophysics Data System (ADS)

Rustic, G. T.; Polissar, P. J.; Ravelo, A. C.; White, S. M.

2017-12-01

The El Niño Southern Oscillation (ENSO) plays a dominant role in Earth's climate variability. Paleoceanographic evidence suggests that ENSO has changed in the past, and these changes have been linked to large-scale climatic shifts. While a close relationship between ENSO evolution and climate boundary conditions has been predicted, testing these predictions remains challenging. These climate boundary conditions, including insolation, the mean surface temperature gradient of the tropical Pacific, global ice volume, and tropical thermocline depth, often co-vary and may work together to suppress or enhance the ocean-atmosphere feedbacks that drive ENSO variability. Furthermore, suitable paleo-archives spanning multiple climate states are sparse. We have aimed to test ENSO response to changing climate boundary conditions by generating new reconstructions of mixed-layer variability from sedimentary archives spanning the last three glacial-interglacial cycles from the Central Tropical Pacific Line Islands, where El Niño is strongly expressed. We analyzed Mg/Ca ratios from individual foraminifera to reconstruct mixed-layer variability at discrete time intervals representing combinations of climatic boundary conditions from the middle Holocene to Marine Isotope Stage (MIS) 8. We observe changes in the mixed-layer temperature variability during MIS 5 and during the previous interglacial (MIS 7) showing significant reductions in ENSO amplitude. Differences in variability during glacial and interglacial intervals are also observed. Additionally, we reconstructed mixed-layer and thermocline conditions using multi-species Mg/Ca and stable isotope measurements to more fully characterize the state of the Central Tropical Pacific during these intervals. These reconstructions provide us with a unique view of Central Tropical Pacific variability and water-column structure at discrete intervals under varying boundary climate conditions with which to assess factors that shape ENSO variability.

Multi-disciplinary assessments of climate change impacts on agriculture to support adaptation decision making in developing countries

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Many existing climate change impact studies, carried out by academic researchers, are disconnected from decision making processes of stakeholders. On the other hand many climate change adaptation projects in developing countries lack a solid evidence base of current and future climate impacts as well as vulnerabilities assessment at different scales. In order to fill this information gap, FAO has developed and implemented a tool "MOSAICC (Modelling System for Agricultural Impacts of Climate Change)" in several developing countries such as Morocco, the Philippines and Peru, and recently in Malawi and Zambia. MOSAICC employs a multi-disciplinary assessment approach to addressing climate change impacts and adaptation planning in the agriculture and food security sectors, and integrates five components from different academic disciplines: 1. Statistical downscaling of climate change projections, 2. Yield simulation of major crops at regional scale under climate change, 3. Surface hydrology simulation model, 4. Macroeconomic model, and 5. Forestry model. Furthermore MOSAICC has been developed as a capacity development tool for the national scientists so that they can conduct the country assessment themselves, using their own data, and reflect the outcome into the national adaptation policies. The outputs are nation-wide coverage, disaggregated at sub-national level to support strategic planning, investments and decisions by national policy makers. MOSAICC is designed in such a way to promote stakeholders' participation and strengthen technical capacities in developing countries. The paper presents MOSAICC and projects that used MOSAICC as a tool with case studies from countries.

Disentangling the relative role of climate change on tree growth in an extreme Mediterranean environment.

PubMed

Madrigal-González, Jaime; Andivia, Enrique; Zavala, Miguel A; Stoffel, Markus; Calatayud, Joaquín; Sánchez-Salguero, Raúl; Ballesteros-Cánovas, Juan

2018-06-14

Climate change can impair ecosystem functions and services in extensive dry forests worldwide. However, attribution of climate change impacts on tree growth and forest productivity is challenging due to multiple inter-annual patterns of climatic variability associated with atmospheric and oceanic circulations. Moreover, growth responses to rising atmospheric CO 2 , namely carbon fertilization, as well as size ontogenetic changes can obscure the climate change signature as well. Here we apply Structural Equation Models (SEM) to investigate the relative role of climate change on tree growth in an extreme Mediterranean environment (i.e., extreme in terms of the combination of sandy-unconsolidated soils and climatic aridity). Specifically, we analyzed potential direct and indirect pathways by which different sources of climatic variability (i.e. warming and precipitation trends, the North Atlantic Oscillation, [NAO]; the Mediterranean Oscillation, [MOI]; the Atlantic Mediterranean Oscillation, [AMO]) affect aridity through their control on local climate (in terms of mean annual temperature and total annual precipitation), and subsequently tree productivity, in terms of basal area increments (BAI). Our results support the predominant role of Diameter at Breast Height (DHB) as the main growth driver. In terms of climate, NAO and AMO are the most important drivers of tree growth through their control of aridity (via effects of precipitation and temperature, respectively). Furthermore and contrary to current expectations, our findings also support a net positive role of climate warming on growth over the last 50 years and suggest that impacts of climate warming should be evaluated considering multi-annual and multi-decadal periods of local climate defined by atmospheric and oceanic circulation in the North Atlantic. Copyright © 2018 Elsevier B.V. All rights reserved.

Multilevel Multi-Informant Structure of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan

2014-01-01

The Authoritative School Climate Survey was designed to provide schools with a brief assessment of 2 key characteristics of school climate--disciplinary structure and student support--that are hypothesized to influence 2 important school climate outcomes--student engagement and prevalence of teasing and bullying in school. The factor structure of…

Impact of socio-demographic factors on the mitigating actions for climate change: a path analysis with mediating effects of attitudinal variables.

PubMed

Masud, Muhammad Mehedi; Akhatr, Rulia; Nasrin, Shamima; Adamu, Ibrahim Mohammed

2017-12-01

Socio-demographic factors play a significant role in increasing the individual's climate change awareness and in setting a favorable individual attitude towards its mitigation. To better understand how the adversative effects of climate change can be mitigated, this study attempts to investigate the impact of socio-demographic factors on the mitigating actions of the individuals (MAOI) on climate change. Qualitative data were collected from a face-to-face survey of 360 respondents in the Kuala Lumpur region of Malaysia through a close-ended questionnaire. Analysis was conducted on the mediating effects of attitudinal variables through the path model by using the SEM. Findings indicate that the socio-demographic factors such as gender, age, education, income, and ethnicity can greatly influence the individual's awareness, attitude, risk perception, and knowledge of climate change issues. The results drawn from this study also revealed that the attitudinal factors act as a mediating effect between the socio-demographic factors and the MAOI, thereby, indicating that both the socio-demographic factors and the attitudinal factors have significant effects on the MAOI towards climate change. The outcome of this study can help policy makers and other private organizations to decide on the appropriate actions to take in managing climate change effects. These actions which encompass improving basic climate change education and making the public more aware of the local dimensions of climate change are important for harnessing public engagement and support that can also stimulate climate change awareness and promote mitigating actions to n protect the environment from the impact of climate change.

LGM permafrost distribution: how well can the latest PMIP multi-model ensembles reconstruct?

NASA Astrophysics Data System (ADS)

Saito, K.; Sueyoshi, T.; Marchenko, S.; Romanovsky, V.; Otto-Bliesner, B.; Walsh, J.; Bigelow, N.; Hendricks, A.; Yoshikawa, K.

2013-03-01

Global-scale frozen ground distribution during the Last Glacial Maximum (LGM) was reconstructed using multi-model ensembles of global climate models, and then compared with evidence-based knowledge and earlier numerical results. Modeled soil temperatures, taken from Paleoclimate Modelling Intercomparison Project Phase III (PMIP3) simulations, were used to diagnose the subsurface thermal regime and determine underlying frozen ground types for the present-day (pre-industrial; 0 k) and the LGM (21 k). This direct method was then compared to the earlier indirect method, which categorizes the underlying frozen ground type from surface air temperature, applied to both the PMIP2 (phase II) and PMIP3 products. Both direct and indirect diagnoses for 0 k showed strong agreement with the present-day observation-based map, although the soil temperature ensemble showed a higher diversity among the models partly due to varying complexity of the implemented subsurface processes. The area of continuous permafrost estimated by the multi-model analysis was 25.6 million km2 for LGM, in contrast to 12.7 million km2 for the pre-industrial control, whereas seasonally, frozen ground increased from 22.5 million km2 to 32.6 million km2. These changes in area resulted mainly from a cooler climate at LGM, but other factors as well, such as the presence of huge land ice sheets and the consequent expansion of total land area due to sea-level change. LGM permafrost boundaries modeled by the PMIP3 ensemble-improved over those of the PMIP2 due to higher spatial resolutions and improved climatology-also compared better to previous knowledge derived from the geomorphological and geocryological evidences. Combinatorial applications of coupled climate models and detailed stand-alone physical-ecological models for the cold-region terrestrial, paleo-, and modern climates will advance our understanding of the functionality and variability of the frozen ground subsystem in the global eco-climate system.

A multi-disciplinary approach for the integrated assessment of multiple risks in delta areas.

NASA Astrophysics Data System (ADS)

Sperotto, Anna; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2016-04-01

The assessment of climate change related risks is notoriously difficult due to the complex and uncertain combinations of hazardous events that might happen, the multiplicity of physical processes involved, the continuous changes and interactions of environmental and socio-economic systems. One important challenge lies in predicting and modelling cascades of natural and man -made hazard events which can be triggered by climate change, encompassing different spatial and temporal scales. Another regard the potentially difficult integration of environmental, social and economic disciplines in the multi-risk concept. Finally, the effective interaction between scientists and stakeholders is essential to ensure that multi-risk knowledge is translated into efficient adaptation and management strategies. The assessment is even more complex at the scale of deltaic systems which are particularly vulnerable to global environmental changes, due to the fragile equilibrium between the presence of valuable natural ecosystems and relevant economic activities. Improving our capacity to assess the combined effects of multiple hazards (e.g. sea-level rise, storm surges, reduction in sediment load, local subsidence, saltwater intrusion) is therefore essential to identify timely opportunities for adaptation. A holistic multi-risk approach is here proposed to integrate terminology, metrics and methodologies from different research fields (i.e. environmental, social and economic sciences) thus creating shared knowledge areas to advance multi risk assessment and management in delta regions. A first testing of the approach, including the application of Bayesian network analysis for the assessment of impacts of climate change on key natural systems (e.g. wetlands, protected areas, beaches) and socio-economic activities (e.g. agriculture, tourism), is applied in the Po river delta in Northern Italy. The approach is based on a bottom-up process involving local stakeholders early in different stages of the multi-risk assessment process (i.e. identification of objectives, collection of data, definition of risk thresholds and indicators). The results of the assessment will allow the development of multi-risk scenarios enabling the evaluation and prioritization of risk management and adaptation options under changing climate conditions.

Regional Climate Change Hotspots over Africa

NASA Astrophysics Data System (ADS)

Anber, U.

2009-04-01

Regional Climate Change Index (RCCI), is developed based on regional mean precipitation change, mean surface air temperature change, and change in precipitation and temperature interannual variability. The RCCI is a comparative index designed to identify the most responsive regions to climate change, or Hot- Spots. The RCCI is calculated for Seven land regions over North Africa and Arabian region from the latest set of climate change projections by 14 global climates for the A1B, A2 and B1 IPCC emission scenarios. The concept of climate change can be approaches from the viewpoint of vulnerability or from that of climate response. In the former case a Hot-Spot can be defined as a region for which potential climate change impacts on the environment or different activity sectors can be particularly pronounced. In the other case, a Hot-Spot can be defined as a region whose climate is especially responsive to global change. In particular, the characterization of climate change response-based Hot-Spot can provide key information to identify and investigate climate change Hot-Spots based on results from multi-model ensemble of climate change simulations performed by modeling groups from around the world as contributions to the Assessment Report of Intergovernmental Panel on Climate Change (IPCC). A Regional Climate Change Index (RCCI) is defined based on four variables: change in regional mean surface air temperature relative to the global average temperature change ( or Regional Warming Amplification Factor, RWAF ), change in mean regional precipitation ( , of present day value ), change in regional surface air temperature interannual variability ( ,of present day value), change in regional precipitation interannual variability ( , of present day value ). In the definition of the RCCI it is important to include quantities other than mean change because often mean changes are not the only important factors for specific impacts. We thus also include inter annual variability, which is critical for many activity sectors, such as agriculture and water management. The RCCI is calculated for the above mentioned set of global climate change simulations and is inter compared across regions to identify climate change, Hot- Spots, that is regions with the largest values of RCCI. It is important to stress that, as will be seen, the RCCI is a comparative index, that is a small RCCI value does not imply a small absolute change, but only a small climate response compared to other regions. The models used are: CCMA-3-T47 CNRM-CM3 CSIRO-MK3 GFDL-CM2-0 GISS-ER INMCM3 IPSL-CM4 MIROC3-2M MIUB-ECHO-G MPI-ECHAM5 MRI-CGCM2 NCAR-CCSM3 NCAR-PCM1 UKMO-HADCM3 Note that the 3 IPCC emission scenarios, A1B, B1 and A2 almost encompass the entire IPCC scenario range, the A2 being close to the high end of the range, the B1 close to the low end and the A1B lying toward the middle of the range. The model data are obtained from the IPCC site and are interpolated onto a common 1 degree grid to facilitate intercomparison. The RCCI is here defined as in Giorgi (2006), except that the entire yea is devided into two six months periods, D J F M A M and J J A S O N. RCCI=[n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]D...M + [n(∆P)＋n(∆σP)+n(RWAF)+n(∆σT)]J…N (1)

Korean Early Childhood Educators' Multi-Dimensional Teacher Self-Efficacy and ECE Center Climate and Depression Severity in Teachers as Contributing Factors

ERIC Educational Resources Information Center

Kim, Yeon Ha; Kim, Yang Eun

2010-01-01

This study investigated profiles of South Korean early childhood educators' teacher self-efficacy and contributing factors to teacher self-efficacy. The contributing factors were examined with a focus on early childhood education (ECE) center climate and depression severity in teachers as well as teacher and classroom characteristics. The results…

Assessment of the Effect of Climate Change on Grain Yields in China

NASA Astrophysics Data System (ADS)

Chou, J.

2006-12-01

The paper elaborates the social background and research background; makes clear what the key scientific issues need to be resolved and where the difficulties are. In the research area of parasailing the grain yield change caused by climate change, massive works have been done both in the domestic and in the foreign. It is our upcoming work to evaluate how our countrywide climate change information provided by this pattern influence our economic and social development; and how to make related policies and countermeasures. the main idea in this paper is that the grain yield change is by no means the linear composition of social economy function effect and the climatic change function effect. This paper identifies the economic evaluation object, proposes one new concept - climate change output. The grain yields change affected by the social factors and the climatic change working together. Climate change influences the grain yields by the non ¨C linear function from both climate change and social factor changes, not only by climate change itself. Therefore, in my paper, the appraisal object is defined as: The social factors change based on actual social changing situations; under the two kinds of climate change situation, the invariable climate change situation and variable climate change situation; the difference of grain yield outputs is called " climate change output ", In order to solve this problem, we propose a method to analyze and imitate on the historical materials. Giving the condition that the climate is invariable, the social economic factor changes cause the grain yield change. However, this grain yield change is a tentative quantity index, not an actual quantity number. So we use the existing historical materials to exam the climate change output, based on the characteristic that social factor changes greater in year than in age, but the climate factor changes greater in age than in year. The paper proposes and establishes one economy - climate model (C-D-C model) to appraise the grain yield change caused by the climatic change. Also the preliminary test on this model has been done. In selection of the appraisal methods, we take the C-D production function model, which has been proved more mature in the economic research, as our fundamental model. Then, we introduce climate index (arid index) to the C-D model to develop one new model. This new model utilizes the climatic change factor in the economical model to appraise how the climatic change influence the grain yield change. The new way of appraise should have the better application prospect. The economy - climate model (The C-D-C model) has been applied on the eight Chinese regions that we divide; it has been proved satisfactory in its feasibility, rationality and the application prospect. So we can provide the theoretical fundamentals for policy-making under the more complex and uncertain climate change. Therefore, we open a new possible channel for the global climate change research moving toward the actual social, economic life.

A practical scale for Multi-Faceted Organizational Health Climate Assessment.

PubMed

Zweber, Zandra M; Henning, Robert A; Magley, Vicki J

2016-04-01

The current study sought to develop a practical scale to measure 3 facets of workplace health climate from the employee perspective as an important component of a healthy organization. The goal was to create a short, usable yet comprehensive scale that organizations and occupational health professionals could use to determine if workplace health interventions were needed. The proposed Multi-faceted Organizational Health Climate Assessment (MOHCA) scale assesses facets that correspond to 3 organizational levels: (a) workgroup, (b) supervisor, and (c) organization. Ten items were developed and tested on 2 distinct samples, 1 cross-organization and 1 within-organization. Exploratory and confirmatory factor analyses yielded a 9-item, hierarchical 3-factor structure. Tests confirmed MOHCA has convergent validity with related constructs, such as perceived organizational support and supervisor support, as well as discriminant validity with safety climate. Lastly, criterion-related validity was found between MOHCA and health-related outcomes. The multi-faceted nature of MOHCA provides a scale that has face validity and can be easily translated into practice, offering a means for diagnosing the shortcomings of an organization or workgroup's health climate to better plan health and well-being interventions. (c) 2016 APA, all rights reserved).

Multi objective climate change impact assessment using multi downscaled climate scenarios

NASA Astrophysics Data System (ADS)

Rana, Arun; Moradkhani, Hamid

2016-04-01

Global Climate Models (GCMs) are often used to downscale the climatic parameters on a regional and global scale. In the present study, we have analyzed the changes in precipitation and temperature for future scenario period of 2070-2099 with respect to historical period of 1970-2000 from a set of statistically downscaled GCM projections for Columbia River Basin (CRB). Analysis is performed using 2 different statistically downscaled climate projections namely the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, totaling to 40 different scenarios. Analysis is performed on spatial, temporal and frequency based parameters in the future period at a scale of 1/16th of degree for entire CRB region. Results have indicated in varied degree of spatial change pattern for the entire Columbia River Basin, especially western part of the basin. At temporal scales, winter precipitation has higher variability than summer and vice-versa for temperature. Frequency analysis provided insights into possible explanation to changes in precipitation.

Towards bridging the gap between climate change projections and maize producers in South Africa

NASA Astrophysics Data System (ADS)

Landman, Willem A.; Engelbrecht, Francois; Hewitson, Bruce; Malherbe, Johan; van der Merwe, Jacobus

2018-05-01

Multi-decadal regional projections of future climate change are introduced into a linear statistical model in order to produce an ensemble of austral mid-summer maximum temperature simulations for southern Africa. The statistical model uses atmospheric thickness fields from a high-resolution (0.5° × 0.5°) reanalysis-forced simulation as predictors in order to develop a linear recalibration model which represents the relationship between atmospheric thickness fields and gridded maximum temperatures across the region. The regional climate model, the conformal-cubic atmospheric model (CCAM), projects maximum temperatures increases over southern Africa to be in the order of 4 °C under low mitigation towards the end of the century or even higher. The statistical recalibration model is able to replicate these increasing temperatures, and the atmospheric thickness-maximum temperature relationship is shown to be stable under future climate conditions. Since dry land crop yields are not explicitly simulated by climate models but are sensitive to maximum temperature extremes, the effect of projected maximum temperature change on dry land crops of the Witbank maize production district of South Africa, assuming other factors remain unchanged, is then assessed by employing a statistical approach similar to the one used for maximum temperature projections.

Using Nitrogen Stable Isotope Tracers to Track Climate Change Impacts on Coastal Salt Marshes

EPA Science Inventory

Climate change impacts on coastal salt marshes are predicted to be complex and multi-faceted. In addition to rising sea level and warmer water temperatures, regional precipitation patterns are also expected to change. At least in the Northeast and Mid-Atlantic U.S., more severe s...

Multi-scale model of the U.S. transportation energy market for policy assessment.

DOT National Transportation Integrated Search

2013-06-01

Across the globe, issues related to energy, its sources, uses, and impacts on climate change are at the forefront : of political and environmental debates (e.g., the 2012 United Nations Climate Change Conference at Doha, : http://unfccc.int). Current...

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

Ecosystem composition changes over the past millennium: model simulations and comparison with paleoecological observations

NASA Astrophysics Data System (ADS)

Liu, Y.; Rollinson, C.; Dietze, M.; McLachlan, J. S.; Poulter, B.; Quaife, T. L.; Raiho, A.; Ricciuto, D. M.; Schaefer, K. M.; Steinkamp, J.; Moore, D. J.

2015-12-01

Over multi-decadal to multi-centennial timescales, ecosystem function and carbon storage is largely influenced by vegetation composition. The predictability of ecosystem responses to climate change thus depends on the understanding of long-term community dynamics. Our study aims to quantify the influence of the most relevant ecological factors that control plant distribution and abundance, in contemporary terrestrial biosphere models and in paleo-records, and constrain the model processes and parameters with paleoecological data. We simulated vegetation changes at 6 sites in the northeastern United States over the past 1160 years using 7 terrestrial biosphere models and variations (CLM4.5-CN, ED2, ED2-LU, JULES-TRIFFID, LINKAGES, LPJ-GUESS, LPJ-wsl) driven by common paleoclimatic drivers. We examined plant growth, recruitment, and mortality (including other carbon turnover) of the plant functional types (PFTs) in the models, attributed the responses to three major factors (climate, competition, and disturbance), and estimated the relative effect of each factor. We assessed the model responses against plant-community theories (bioclimatic limits, niche difference, temporal variation and storage effect, and disturbance). We found that vegetation composition were sensitive to realized niche differences (e.g. differential growth response) among PFTs. Because many models assume unlimited dispersal and sometimes recruitment, the "storage effect" constantly affects community composition. Fire was important in determining the ecosystem composition, yet the vegetation to fire feedback was weak in the models. We also found that vegetation-composition changes in the simulations were driven to a much greater degree by growth as opposed to by turnover/mortality, when compared with those in paleoecological records. Our work suggest that 1) for forecasting slow changes in vegetation composition, we can use paleo-data to better quantify the realized niches of PFTs and associated uncertainties, and 2) for predicting abrupt changes in vegetation composition, we need to better implement processes of dynamic turnover and fire in current ecosystem models.

Assessment of hi-resolution multi-ensemble statistical downscaling regional climate scenarios over Japan

NASA Astrophysics Data System (ADS)

Dairaku, K.

2017-12-01

The Asia-Pacific regions are increasingly threatened by large scale natural disasters. Growing concerns that loss and damages of natural disasters are projected to further exacerbate by climate change and socio-economic change. Climate information and services for risk assessments are of great concern. Fundamental regional climate information is indispensable for understanding changing climate and making decisions on when and how to act. To meet with the needs of stakeholders such as National/local governments, spatio-temporal comprehensive and consistent information is necessary and useful for decision making. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 37 GCMs (RCP8.5) and a statistical downscaling (Bias Corrected Spatial Disaggregation (BCSD)) to investigate uncertainty of projected change associated with structural differences of the GCMs for the periods of historical climate (1950-2005) and near future climate (2026-2050). Statistical downscaling regional climate scenarios show good performance for annual and seasonal averages for precipitation and temperature. The regional climate scenarios show systematic underestimate of extreme events such as hot days of over 35 Celsius and annual maximum daily precipitation because of the interpolation processes in the BCSD method. Each model projected different responses in near future climate because of structural differences. The most of CMIP5 37 models show qualitatively consistent increase of average and extreme temperature and precipitation. The added values of statistical/dynamical downscaling methods are also investigated for locally forced nonlinear phenomena, extreme events.

Spatiotemporal distribution and variation of GPP in the Greater Khingan Mountains from 1982 to 2015

NASA Astrophysics Data System (ADS)

Hu, L.; Fan, W.; Liu, S.; Ren, H.; Xu, X.

2017-12-01

GPP (Gross Primary Productivity) is an important index to reflect the productivity of plants because it refers to the organic accumulated by green plants on land through assimilating the carbon dioxide in the atmosphere by photosynthesis and a serial of physiological processes in plants. Therefore, GPP plays a significant role in studying the carbon sink of terrestrial ecosystem and plants' reaction to global climate change. Remote sensing provides an efficient way to estimate GPP at regional and global scales and its products can be used to monitor the spatiotemporal variation of terrestrial ecosystem.As the Greater Khingan Mountains is the only bright coniferous forest of cool temperate zone in China and accounts for about 30% of the forest in China. This region is sensitive to climate change, but its forest coverage presented a significant variation due to fire disasters, excessive deforestation and so on. Here, we aimed at studying the variation pattern of GPP in the Greater Khingan Mountains and further found impact factors for the change in order to improve the understanding of what have and will happen on plants and carbon cycle under climate change.Based on GPP product from the GLASS program, we first studied spatial distribution of plants in the Greater Khingan Mountains from 1982 to 2015. With a linear regression model, seasonal and inter-annual GPP variability were explored on pixel and regional scale. We analyzed some climatic factors (e.g. temperature and precipitation) and terrain in order to find the driven factors for the GPP variations. The Growing Season Length (GSL) was also regarded as a factor and was retrieved from GIMMS 3g NDVI datasets using dynamic threshold method. We found that GPP in study area linearly decreased with the increasing elevation. Both annual accumulated GPP (AAG) and maximum daily GPP (during mid-June to mid-July) gained obvious improvement over the past 34 years under climate warming and drying (Fig.1 and Fig.2). Further studies showed temperature had positive correlation with GPP while precipitation had negative effect; Moreover, multi-regression results reflected that temperature rather than precipitation was the dominant climatic factor for plants in study area. The extension of GSL also increased the AAG.

The impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Williams, P.; Abatzoglou, J. T.

2016-12-01

Increased forest fire activity across the western United States (US) in recent decades has contributed to widespread forest mortality, carbon emissions, periods of degraded air quality, and substantial fire suppression expenditures. The increase in forest fire activity has likely been enabled by a number of factors including the legacy of fire suppression and human settlement, changes in suppression policies, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western US. Anthropogenic increases in temperature and vapor pressure deficit have significantly enhanced fuel aridity across western US forests over the past several decades. Comparing observational climate records to records recalculated after removal of modeled anthropogenic trends, we find that anthropogenic climate change accounted for approximately 55% of observed increases in the eight-metric mean fuel aridity during 1979-2015 across western US forests. This implicates anthropogenic climate change as an important driver of observed increases in fuel aridity, and also highlights the importance of natural multi-decadal climate variability in influencing trends in forest fire potential on the timescales of human lives. Based on a very strong (R2 = 0.76) and mechanistically reasonable relationship between interannual variability in the eight-metric mean fuel aridity and forest-fire area in the western US, we estimate that anthropogenic increases in fuel aridity contributed to an additional 4.2 million ha (95% confidence range: 2.7-6.5 million ha) of forest fire area during 1984-2015, nearly doubling the total forest fire area expected in the absence of anthropogenic climate change. The relationship between annual forest fire area and fuel aridity is exponential and the proportion of total forest area burned in a given year has grown rapidly over the past 32 years. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a chronic driver of increased forest fire activity and should continue to do so where fuels are not limiting.

Structural and Psycho-Social Limits to Climate Change Adaptation in the Great Barrier Reef Region

PubMed Central

Evans, Louisa S.; Hicks, Christina C.; Adger, W. Neil; Barnett, Jon; Perry, Allison L.; Fidelman, Pedro; Tobin, Renae

2016-01-01

Adaptation, as a strategy to respond to climate change, has limits: there are conditions under which adaptation strategies fail to alleviate impacts from climate change. Research has primarily focused on identifying absolute bio-physical limits. This paper contributes empirical insight to an emerging literature on the social limits to adaptation. Such limits arise from the ways in which societies perceive, experience and respond to climate change. Using qualitative data from multi-stakeholder workshops and key-informant interviews with representatives of the fisheries and tourism sectors of the Great Barrier Reef region, we identify psycho-social and structural limits associated with key adaptation strategies, and examine how these are perceived as more or less absolute across levels of organisation. We find that actors experience social limits to adaptation when: i) the effort of pursuing a strategy exceeds the benefits of desired adaptation outcomes; ii) the particular strategy does not address the actual source of vulnerability, and; iii) the benefits derived from adaptation are undermined by external factors. We also find that social limits are not necessarily more absolute at higher levels of organisation: respondents perceived considerable opportunities to address some psycho-social limits at the national-international interface, while they considered some social limits at the local and regional levels to be effectively absolute. PMID:26960200

Structural and Psycho-Social Limits to Climate Change Adaptation in the Great Barrier Reef Region.

PubMed

Evans, Louisa S; Hicks, Christina C; Adger, W Neil; Barnett, Jon; Perry, Allison L; Fidelman, Pedro; Tobin, Renae

2016-01-01

Adaptation, as a strategy to respond to climate change, has limits: there are conditions under which adaptation strategies fail to alleviate impacts from climate change. Research has primarily focused on identifying absolute bio-physical limits. This paper contributes empirical insight to an emerging literature on the social limits to adaptation. Such limits arise from the ways in which societies perceive, experience and respond to climate change. Using qualitative data from multi-stakeholder workshops and key-informant interviews with representatives of the fisheries and tourism sectors of the Great Barrier Reef region, we identify psycho-social and structural limits associated with key adaptation strategies, and examine how these are perceived as more or less absolute across levels of organisation. We find that actors experience social limits to adaptation when: i) the effort of pursuing a strategy exceeds the benefits of desired adaptation outcomes; ii) the particular strategy does not address the actual source of vulnerability, and; iii) the benefits derived from adaptation are undermined by external factors. We also find that social limits are not necessarily more absolute at higher levels of organisation: respondents perceived considerable opportunities to address some psycho-social limits at the national-international interface, while they considered some social limits at the local and regional levels to be effectively absolute.

Integrating Climate Projections into Multi-Level City Planning: A Texas Case Study

NASA Astrophysics Data System (ADS)

Hayhoe, K.; Gelca, R.; Baumer, Z.; Gold, G.

2016-12-01

Climate change impacts on energy and water are a serious concern for many cities across the United States. Regional projections from the National Assessment process, or state-specific efforts as in California and Delaware, are typically used to quantify impacts at the regional scale. However, these are often insufficient to provide information at the scale of decision-making for an individual city. Here, we describe a multi-level approach to developing and integrating usable climate information into planning, using a case study from the City of Austin in Texas, a state where few official climate resources are available. Spearheaded by the Office of Sustainability in collaboration with Austin Water, the first step was to characterize observed trends and future projections of how global climate change might affect Austin's current climate. The City then assembled a team of city experts, consulting engineers, and climate scientists to develop a methodology to assess impacts on regional hydrology as part of its Integrated Water Resource Plan, Austin's 100-year water supply and demand planning effort, an effort which included calculating a range of climate indicators and developing and evaluating a new approach to generating climate inputs - including daily streamflow and evaporation - for existing water availability models. This approach, which brings together a range of public, private, and academic experts to support a stakeholder-initiated planning effort, provides concrete insights into the critical importance of multi-level, long-term engagement for development and application of actionable climate science at the local to regional scale.

A Multi-Model Framework to Achieve Consistent Evaluation of Climate Change Impacts in the United States

NASA Astrophysics Data System (ADS)

Sarofim, M. C.; Martinich, J.; Waldhoff, S.; DeAngelo, B. J.; McFarland, J.; Jantarasami, L.; Shouse, K.; Crimmins, A.; Li, J.

2014-12-01

The Climate Change Impacts and Risk Analysis (CIRA) project establishes a new multi-model framework to systematically assess the physical impacts, economic damages, and risks from climate change. The primary goal of this framework is to estimate the degree to which climate change impacts and damages in the United States are avoided or reduced in the 21st century under multiple greenhouse gas (GHG) emissions mitigation scenarios. The first phase of the CIRA project is a modeling exercise that included two integrated assessment models and 15 sectoral models encompassing five broad impacts sectors: water resources, electric power, infrastructure, human health, and ecosystems. Three consistent socioeconomic and climate scenarios are used to analyze the benefits of global GHG mitigation targets: a reference scenario and two policy scenarios with total radiative forcing targets in 2100 of 4.5 W/m2 and 3.7 W/m2. In this exercise, the implications of key uncertainties are explored, including climate sensitivity, climate model, natural variability, and model structures and parameters. This presentation describes the motivations and goals of the CIRA project; the design and academic contribution of the first CIRA modeling exercise; and briefly summarizes several papers published in a special issue of Climatic Change. The results across impact sectors show that GHG mitigation provides benefits to the United States that increase over time, the effects of climate change can be strongly influenced by near-term policy choices, adaptation can reduce net damages, and impacts exhibit spatial and temporal patterns that may inform mitigation and adaptation policy discussions.

The Agriculture Model Intercomparison and Improvement Project (AgMIP) (Invited)

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2010-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation exercise for historical model intercomparison and future climate change conditions with participation of multiple crop and world agricultural trade modeling groups around the world. The goals of AgMIP are to improve substantially the characterization of risk of hunger and world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Historical period results will spur model improvement and interaction among major modeling groups, while future period results will lead directly to tests of adaptation and mitigation strategies across a range of scales. AgMIP will consist of a multi-scale impact assessment utilizing the latest methods for climate and agricultural scenario generation. Scenarios and modeling protocols will be distributed on the web, and multi-model results will be collated and analyzed to ensure the widest possible coverage of agricultural crops and regions. AgMIP will place regional changes in agricultural production in a global context that reflects new trading opportunities, imbalances, and shortages in world markets resulting from climate change and other driving forces for food supply. Such projections are essential inputs from the Vulnerability, Impacts, and Adaptation (VIA) research community to the Intergovernmental Panel on Climate Change Fifth Assessment (AR5), now underway, and the UN Framework Convention on Climate Change. They will set the context for local-scale vulnerability and adaptation studies, supply test scenarios for national-scale development of trade policy instruments, provide critical information on changing supply and demand for water resources, and elucidate interactive effects of climate change and land use change. AgMIP will not only provide crucially-needed new global estimates of how climate change will affect food supply and hunger in the agricultural regions of the world, but it will also build the capabilities of developing countries to estimate how climate change will affect their supply and demand for food.

Evaluating Climate Causation of Conflict in Darfur Using Multi-temporal, Multi-resolution Satellite Image Datasets With Novel Analyses

NASA Astrophysics Data System (ADS)

Brown, I.; Wennbom, M.

2013-12-01

Climate change, population growth and changes in traditional lifestyles have led to instabilities in traditional demarcations between neighboring ethic and religious groups in the Sahel region. This has resulted in a number of conflicts as groups resort to arms to settle disputes. Such disputes often centre on or are justified by competition for resources. The conflict in Darfur has been controversially explained by resource scarcity resulting from climate change. Here we analyse established methods of using satellite imagery to assess vegetation health in Darfur. Multi-decadal time series of observations are available using low spatial resolution visible-near infrared imagery. Typically normalized difference vegetation index (NDVI) analyses are produced to describe changes in vegetation ';greenness' or ';health'. Such approaches have been widely used to evaluate the long term development of vegetation in relation to climate variations across a wide range of environments from the Arctic to the Sahel. These datasets typically measure peak NDVI observed over a given interval and may introduce bias. It is furthermore unclear how the spatial organization of sparse vegetation may affect low resolution NDVI products. We develop and assess alternative measures of vegetation including descriptors of the growing season, wetness and resource availability. Expanding the range of parameters used in the analysis reduces our dependence on peak NDVI. Furthermore, these descriptors provide a better characterization of the growing season than the single NDVI measure. Using multi-sensor data we combine high temporal/moderate spatial resolution data with low temporal/high spatial resolution data to improve the spatial representativity of the observations and to provide improved spatial analysis of vegetation patterns. The approach places the high resolution observations in the NDVI context space using a longer time series of lower resolution imagery. The vegetation descriptors derived are evaluated using independent high spatial resolution datasets that reveal the pattern and health of vegetation at metre scales. We also use climate variables to support the interpretation of these data. We conclude that the spatio-temporal patterns in Darfur vegetation and climate datasets suggest that labelling the conflict a climate-change conflict is inaccurate and premature.

Elevated air temperature alters an old-field insect community in a multi-factor climate change experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Villalpando, Sean; Williams, Ray; Norby, Richard J

To address how multiple, interacting climate drivers may affect plant-insect community associations, we sampled the insect community from a constructed old-field plant community grown under simultaneous [CO2], temperature, and water manipulation. Insects were identified to morphospecies, assigned to feeding guilds and abundance, richness and evenness quantified. Warming significantly increased Order Thysanoptera abundance and reduced overall morphospecies richness and evenness. Non-metric multidimensional scaling clearly supported the effect of warming on insect community composition. Reductions in richness for herbivores and parasitoids suggest trophic-level effects within the insect community. Analysis of dominant insects demonstrated the effects of warming were limited to a relativelymore » small number of morphospecies. Reported reductions in whole-community foliar N at elevated [CO2] unexpectedly did not result in any effects on herbivores. These results demonstrate climatic warming may alter certain insect communities via effects on insect species most responsive to higher temperature, contributing to a change in community structure.« less

The relationship between Arctic sea ice and the Atlantic meridional overturning circulation in a warming climate

NASA Astrophysics Data System (ADS)

Liu, W.; Fedorov, A. V.

2017-12-01

A recent study (Sevellec, Fedorov, Liu 2017, Nature Climate Change) has suggested that Arctic sea ice decline can lead to a slow-down of the Atlantic meridional overturning circulation (AMOC). Here, we build on this previous work and explore the relationship between Arctic sea ice and the AMOC in climate models. We find that the current Arctic sea ice decline can contribute about 40% to the AMOC weakening over the next 60 years. This effect is related to the warming and freshening of the upper ocean in the Arctic, and the subsequent spread of generated buoyancy anomalies downstream where they affect the North Atlantic deep convection sites and hence the AMOC on multi-decadal timescales. The weakening of the AMOC and its poleward heat transport, in turn, sustains the "Warming Hole" - a region in the North Atlantic with anomalously weak (or even negative) warming trends. We discuss the key factors that control this robust AMOC response to changes in Arctic sea ice.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

Development of probabilistic regional climate scenario in East Asia

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Ishizaki, N. N.

2015-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in East Asia (CORDEX-EA and Japan), the probability distribution of 2m air temperature was estimated by using developed regression model. The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. Probabilistic climate information in present (1969-1998) and future (2069-2098) climate was developed using CMIP3 SRES A1b scenarios 21 models and the observation data (CRU_TS3.22 & University of Delaware in CORDEX-EA, NIAES AMeDAS mesh data in Japan). The prototype of probabilistic information in CORDEX-EA and Japan represent the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Appropriate combination of statistical methods and optimization of climate ensemble experiments using multi-General Circulation Models (GCMs) and multi-regional climate models (RCMs) ensemble downscaling experiments are investigated.

The last Deglaciation in the Mediterranean region: a multi-archives synthesis

NASA Astrophysics Data System (ADS)

Bazin, Lucie; Siani, Giuseppe; Landais, Amaelle; Bassinot, Frank; Genty, Dominique; Govin, Aline; Michel, Elisabeth; Nomade, Sebastien; Waelbroeck, Claire

2016-04-01

Multiple proxies record past climatic changes in different climate archives. These proxies are influenced by different component of the climate system and bring complementary information on past climate variability. The major limitation when combining proxies from different archives comes from the coherency of their chronologies. Indeed, each climate archives possess their own dating methods, not necessarily coherent with each other's. Consequently, when we want to assess the latitudinal changes and mechanisms behind a climate event, we often have to rely on assumptions of synchronisation between the different archives, such as synchronous temperature changes during warming events (Austin and Hibbert 2010). Recently, a dating method originally developed to produce coherent chronologies for ice cores (Datice,Lemieux-Dudon et al., 2010) has been adapted in order to integrate different climate archives (ice cores, sediment cores and speleothems (Lemieux-Dudon et al., 2015, Bazin et al., in prep)). In this presentation we present the validation of this multi-archives dating tool with a first application covering the last Deglaciation in the Mediterranean region. For this experiment, we consider the records from Monticchio, the MD90-917, Tenaghi Philippon and Lake Orhid sediment cores as well as continuous speleothems from Sofular, Soreq and La Mine caves. Using the Datice dating tool, and with the identification of common tephra layers between the cores considered, we are able to produce a multi-archives coherent chronology for this region, independently of any climatic assumption. Using this common chronological framework, we show that the usual climatic synchronisation assumptions are not valid over this region for the last glacial-interglacial transition. Finally, we compare our coherent Mediterranean chronology with Greenland ice core records in order to discuss the sequence of events of the last Deglaciation between these two regions.

Assessment of the uncertainty in future projection for summer climate extremes over the East Asia

NASA Astrophysics Data System (ADS)

Park, Changyong; Min, Seung-Ki; Cha, Dong-Hyun

2017-04-01

Future projections of climate extremes in regional and local scales are essential information needed for better adapting to climate changes. However, future projections hold larger uncertainty factors arising from internal and external processes which reduce the projection confidence. Using CMIP5 (Coupled Model Intercomparison Project Phase 5) multi-model simulations, we assess uncertainties in future projections of the East Asian temperature and precipitation extremes focusing on summer. In examining future projection, summer mean and extreme projections of the East Asian temperature and precipitation would be larger as time. Moreover, uncertainty cascades represent wider scenario difference and inter-model ranges with increasing time. A positive mean-extreme relation is found in projections for both temperature and precipitation. For the assessment of uncertainty factors for these projections, dominant uncertainty factors from temperature and precipitation change as time. For uncertainty of mean and extreme temperature, contributions of internal variability and model uncertainty declines after mid-21st century while role of scenario uncertainty grows rapidly. For uncertainty of mean precipitation projections, internal variability is more important than the scenario uncertainty. Unlike mean precipitation, extreme precipitation shows that the scenario uncertainty is expected to be a dominant factor in 2090s. The model uncertainty holds as an important factor for both mean and extreme precipitation until late 21st century. The spatial changes for the uncertainty factors of mean and extreme projections generally are expressed according to temporal changes of the fraction of total variance from uncertainty factors in many grids of the East Asia. ACKNOWLEDGEMENTS The research was supported by the Korea Meteorological Administration Research and Development program under grant KMIPA 2015-2083 and the National Research Foundation of Korea Grant funded by the Ministry of Science, ICT and Future Planning of Korea (NRF-2016M3C4A7952637) for its support and assistant in completion of the study.

Quantification of physical and economic impacts of climate change on public infrastructure in Alaska and benefits of global greenhouse gas mitigation

NASA Astrophysics Data System (ADS)

Melvin, A. M.; Larsen, P.; Boehlert, B.; Martinich, J.; Neumann, J.; Chinowsky, P.; Schweikert, A.; Strzepek, K.

2015-12-01

Climate change poses many risks and challenges for the Arctic and sub-Arctic, including threats to infrastructure. The safety and stability of infrastructure in this region can be impacted by many factors including increased thawing of permafrost soils, reduced coastline protection due to declining arctic sea ice, and changes in inland flooding. The U.S. Environmental Protection Agency (EPA) is coordinating an effort to quantify physical and economic impacts of climate change on public infrastructure across the state of Alaska and estimate how global greenhouse gas (GHG) mitigation may avoid or reduce these impacts. This research builds on the Climate Change Impacts and Risk Analysis (CIRA) project developed for the contiguous U.S., which is described in an EPA report released in June 2015. We are using a multi-model analysis focused primarily on the impacts of changing permafrost, coastal erosion, and inland flooding on a range of infrastructure types, including transportation (e.g. roads, airports), buildings and harbors, energy sources and transmission, sewer and water systems, and others. This analysis considers multiple global GHG emission scenarios ranging from a business as usual future to significant global action. These scenarios drive climate projections through 2100 spanning a range of outcomes to capture variability amongst climate models. Projections are being combined with a recently developed public infrastructure database and integrated into a version of the Infrastructure Planning Support System (IPSS) we are modifying for use in the Arctic and sub-Arctic region. The IPSS tool allows for consideration of both adaptation and reactive responses to climate change. Results of this work will address a gap in our understanding of climate change impacts in Alaska, provide estimates of the physical and economic damages we may expect with and without global GHG mitigation, and produce important insights about infrastructure vulnerabilities in response to warming at northern latitudes.

A Multi-Sector Assessment of the Effects of Climate Change at the Energy-Water-Land Nexus in the US

NASA Astrophysics Data System (ADS)

McFarland, J.; Sarofim, M. C.; Martinich, J.

2017-12-01

Rising temperatures and changing precipitation patterns due to climate change are projected to alter many sectors of the US economy. A growing body of research has examined these effects in the energy, water, and agricultural sectors. Rising summer temperatures increase the demand for electricity. Changing precipitation patterns effect the availability of water for hydropower generation, thermo-electric cooling, irrigation, and municipal and industrial consumption. A combination of changes to temperature and precipitation alter crop yields and cost-effective farming practices. Although a significant body of research exists on analyzing impacts to individual sectors, fewer studies examine the effects using a common set of assumptions (e.g., climatic and socio-economic) within a coupled modeling framework. The present analysis uses a multi-sector, multi-model framework with common input assumptions to assess the projected effects of climate change on energy, water, and land-use in the United States. The analysis assesses the climate impacts for across 5 global circulation models for representative concentration pathways (RCP) of 8.5 and 4.5 W/m2. The energy sector models - Pacific Northwest National Lab's Global Change Assessment Model (GCAM) and the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) - show the effects of rising temperature on energy and electricity demand. Electricity supply in ReEDS is also affected by the availability of water for hydropower and thermo-electric cooling. Water availability is calculated from the GCM's precipitation using the US Basins model. The effects on agriculture are estimated using both a process-based crop model (EPIC) and an agricultural economic model (FASOM-GHG), which adjusts water supply curves based on information from US Basins. The sectoral models show higher economic costs of climate change under RCP 8.5 than RCP 4.5 averaged across the country and across GCM's.

Multi-Decadal Coastal Behavioural States From A Fusion Of Geohistorical Conceptual Modelling With 2-D Morphodynamic Modelling

NASA Astrophysics Data System (ADS)

Goodwin, I. D.; Mortlock, T.

2016-02-01

Geohistorical archives of shoreline and foredune planform geometry provides a unique evidence-based record of the time integral response to coupled directional wave climate and sediment supply variability on annual to multi-decadal time scales. We develop conceptual shoreline modelling from the geohistorical shoreline archive using a novel combination of methods, including: LIDAR DEM and field mapping of coastal geology; a decadal-scale climate reconstruction of sea-level pressure, marine windfields, and paleo-storm synoptic type and frequency, and historical bathymetry. The conceptual modelling allows for the discrimination of directional wave climate shifts and the relative contributions of cross-shore and along-shore sand supply rates at multi-decadal resolution. We present regional examples from south-eastern Australia over a large latitudinal gradient from subtropical Queensland (S 25°) to mid-latitude Bass Strait (S 40°) that illustrate the morphodynamic evolution and reorganization to wave climate change. We then use the conceptual modeling to inform a two-dimensional coupled spectral wave-hydrodynamic-morphodynamic model to investigate the shoreface response to paleo-directional wind and wave climates. Unlike one-line shoreline modelling, this fully dynamical approach allows for the investigation of cumulative and spatial bathymetric change due to wave-induced currents, as well as proxy-shoreline change. The fusion of the two modeling approaches allows for: (i) the identification of the natural range of coastal planform geometries in response to wave climate shifts; and, (ii) the decomposition of the multidecadal coastal change into the cross-shore and along-shore sand supply drivers, according to the best-matching planforms.

Engaging communities and climate change futures with Multi-Scale, Iterative Scenario Building (MISB) in the western United States

Treesearch

Daniel Murphy; Carina Wyborn; Laurie Yung; Daniel R. Williams; Cory Cleveland; Lisa Eby; Solomon Dobrowski; Erin Towler

2016-01-01

Current projections of future climate change foretell potentially transformative ecological changes that threaten communities globally. Using two case studies from the United States Intermountain West, this article highlights the ways in which a better articulation between theory and methods in research design can generate proactive applied tools that enable...

Climate Change Impacts at Department of Defense Installations

DTIC Science & Technology

2017-06-16

locations. The ease of use of this method and its flexibility have led to a wide variety of applications for assessing impacts of climate change 4...versions of these statistical methods to provide the basis for regional climate assessments for various states, regions, and government agencies...averaging (REA) method proposed by Giorgi and Mearns (2002). This method assigns reliability classifications for the multi-model ensemble simulation by

Unveiling exceptional Baltic bog ecohydrology, autogenic succession and climate change during the last 2000 years in CE Europe using replicate cores, multi-proxy data and functional traits of testate amoebae

NASA Astrophysics Data System (ADS)

Gałka, Mariusz; Tobolski, Kazimierz; Lamentowicz, Łukasz; Ersek, Vasile; Jassey, Vincent E. J.; van der Knaap, Willem O.; Lamentowicz, Mariusz

2017-01-01

We present the results of high-resolution, multi-proxy palaeoecological investigations of two parallel peat cores from the Baltic raised bog Mechacz Wielki in NE Poland. We aim to evaluate the role of regional climate and autogenic processes of the raised bog itself in driving the vegetation and hydrology dynamics. Based on partly synchronous changes in Sphagnum communities in the two study cores we suggest that extrinsic factors (climate) played an important role as a driver in mire development during the bog stage (500-2012 CE). Using a testate amoebae transfer function, we found exceptionally stable hydrological conditions during the last 2000 years with a relatively high water table and lack of local fire events that allowed for rapid peat accumulation (2.75 mm/year) in the bog. Further, the strong correlation between pH and community-weighted mean of testate amoeba traits suggests that other variables than water-table depth play a role in driving microbial properties under stable hydrological conditions. There is a difference in hydrological dynamics in bogs between NW and NE Poland until ca 1500 CE, after which the water table reconstructions show more similarities. Our results illustrate how various functional traits relate to different environmental variables in a range of trophic and hydrological scenarios on long time scales. Moreover, our data suggest a common regional climatic forcing in Mechacz Wielki, Gązwa and Kontolanrahka. Though it may still be too early to attempt a regional summary of wetness change in the southern Baltic region, this study is a next step to better understand the long-term peatland palaeohydrology in NE Europe.

Understanding how lake populations of arctic char are structured and function with special consideration of the potential effects of climate change: a multi-faceted approach.

PubMed

Budy, Phaedra; Luecke, Chris

2014-09-01

Size dimorphism in fish populations, both its causes and consequences, has been an area of considerable focus; however, uncertainty remains whether size dimorphism is dynamic or stabilizing and about the role of exogenous factors. Here, we explored patterns among empirical vital rates, population structure, abundance and trend, and predicted the effects of climate change on populations of arctic char (Salvelinus alpinus) in two lakes. Both populations cycle dramatically between dominance by small (≤300 mm) and large (>300 mm) char. Apparent survival (Φ) and specific growth rates (SGR) were relatively high (40-96%; SGR range 0.03-1.5%) and comparable to those of conspecifics at lower latitudes. Climate change scenarios mimicked observed patterns of warming and resulted in temperatures closer to optimal for char growth (15.15 °C) and a longer growing season. An increase in consumption rates (28-34%) under climate change scenarios led to much greater growth rates (23-34%). Higher growth rates predicted under climate change resulted in an even greater predicted amplitude of cycles in population structure as well as an increase in reproductive output (Ro) and decrease in generation time (Go). Collectively, these results indicate arctic char populations (not just individuals) are extremely sensitive to small changes in the number of ice-free days. We hypothesize years with a longer growing season, predicted to occur more often under climate change, produce elevated growth rates of small char and act in a manner similar to a "resource pulse," allowing a sub-set of small char to "break through," thus setting the cycle in population structure.

Understanding how lake populations of arctic char are structured and function with special consideration of the potential effects of climate change: A multi-faceted approach.

USGS Publications Warehouse

Budy, Phaedra; Luecke, Chris

2014-01-01

Size dimorphism in fish populations, both its causes and consequences, has been an area of considerable focus; however, uncertainty remains whether size dimorphism is dynamic or stabilizing and about the role of exogenous factors. Here, we explored patterns among empirical vital rates, population structure, abundance and trend, and predicted the effects of climate change on populations of arctic char (Salvelinus alpinus) in two lakes. Both populations cycle dramatically between dominance by small (≤300 mm) and large (>300 mm) char. Apparent survival (Φ) and specific growth rates (SGR) were relatively high (40–96 %; SGR range 0.03–1.5 %) and comparable to those of conspecifics at lower latitudes. Climate change scenarios mimicked observed patterns of warming and resulted in temperatures closer to optimal for char growth (15.15 °C) and a longer growing season. An increase in consumption rates (28–34 %) under climate change scenarios led to much greater growth rates (23–34 %). Higher growth rates predicted under climate change resulted in an even greater predicted amplitude of cycles in population structure as well as an increase in reproductive output (Ro) and decrease in generation time (Go). Collectively, these results indicate arctic char populations (not just individuals) are extremely sensitive to small changes in the number of ice-free days. We hypothesize years with a longer growing season, predicted to occur more often under climate change, produce elevated growth rates of small char and act in a manner similar to a “resource pulse,” allowing a sub-set of small char to “break through,” thus setting the cycle in population structure.

Effects of land cover and regional climate variations on long-term spatiotemporal changes in sagebrush ecosystems

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.; Aldridge, Cameron L.

2012-01-01

This research investigated the effects of climate and land cover change on variation in sagebrush ecosystems. We combined information of multi-year sagebrush distribution derived from multitemporal remote sensing imagery and climate data to study the variation patterns of sagebrush ecosystems under different potential disturbances. We found that less than 40% of sagebrush ecosystem changes involved abrupt changes directly caused by landscape transformations and over 60% of the variations involved gradual changes directly related to climatic perturbations. The primary increases in bare ground and declines in sagebrush vegetation abundance were significantly correlated with the 1996-2006 decreasing trend in annual precipitation.

How multiple factors control evapotranspiration in North America evergreen needleleaf forests.

PubMed

Chen, Yueming; Xue, Yueju; Hu, Yueming

2018-05-01

Identifying the factors dominating ecosystem water flux is a critical step for predicting evapotranspiration (ET). Here, the fuzzy rough set with binary shuffled frog leaping (BSFL-FRSA) was used to identify both individual factors and multi-factor combinations that dominate the half-hourly ET variation at evergreen needleleaf forests (ENFs) sites across three different climatic zones in the North America. Among 21factors, air temperature (TA), atmospheric CO 2 concentration (CCO 2 ), soil temperature (TS), soil water content (SWC) and net radiation (NETRAD) were evaluated as dominant single factors, contributed to the ET variation averaged for all ENF sites by 48%, 36%, 32%, 18% and 13%, respectively. While the importance order would vary with climatic zones, and TA was assessed as the most influential factor at a single climatic zone level, counting a contribution rate of 54.7%, 49.9%, and 38.6% in the subarctic, warm summer continental, and Mediterranean climatic zones, respectively. In view of impacts of each multi-factors combination on ET, both TA and CCO 2 made a contribution of 71% across three climate zones; the combination of TA, CCO 2 and NETRAD was evaluated the most dominant at Mediterranean and subarctic ENF sites, and the combination of TA, CCO 2 and TS at warm summer continental sites. Our results suggest that temperature was most critical for ET variation at the warm summer continental ENF. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate impact on malaria in northern Burkina Faso.

PubMed

Tourre, Yves M; Vignolles, Cécile; Viel, Christian; Mounier, Flore

2017-11-27

The Paluclim project managed by the French Centre National d'Etudes Spatiales (CNES) found that total rainfall for a 3-month period is a confounding factor for the density of malaria vectors in the region of Nouna in the Sahel administrative territory of northern Burkina Faso. Following the models introduced in 1999 by Craig et al. and in 2003 by Tanser et al., a climate impact model for malaria risk (using different climate indices) was created. Several predictions of this risk at different temporal scales (i.e. seasonal, inter-annual and low-frequency) were assessed using this climate model. The main result of this investigation was the discovery of a significant link between malaria risk and low-frequency rainfall variability related to the Atlantic Multi-decadal Oscillation (AMO). This result is critical for the health information systems in this region. Knowledge of the AMO phases would help local authorities to organise preparedness and prevention of malaria, which is of particular importance in the climate change context.

The burgeoning field of transdisciplinary adaptation research in Quebec (1998-): a climate change-related public health narrative.

PubMed

Gosselin, Pierre; Bélanger, Diane; Lapaige, Véronique; Labbé, Yolaine

2011-01-01

This paper presents a public health narrative on Quebec's new climatic conditions and human health, and describes the transdisciplinary nature of the climate change adaptation research currently being adopted in Quebec, characterized by the three phases of problem identification, problem investigation, and problem transformation. A transdisciplinary approach is essential for dealing with complex ill-defined problems concerning human-environment interactions (for example, climate change), for allowing joint research, collective leadership, complex collaborations, and significant exchanges among scientists, decision makers, and knowledge users. Such an approach is widely supported in theory but has proved to be extremely difficult to implement in practice, and those who attempt it have met with heavy resistance, succeeding when they find the occasional opportunity within institutional or social contexts. In this paper we narrate the ongoing struggle involved in tackling the negative effects of climate change in multi-actor contexts at local and regional levels, a struggle that began in a quiet way in 1998. The paper will describe how public health adaptation research is supporting transdisciplinary action and implementation while also preparing for the future, and how this interaction to tackle a life-world problem (adaptation of the Quebec public health sector to climate change) in multi-actors contexts has progressively been established during the last 13 years. The first of the two sections introduces the social context of a Quebec undergoing climate changes. Current climatic conditions and expected changes will be described, and attendant health risks for the Quebec population. The second section addresses the scientific, institutional and normative dimensions of the problem. It corresponds to a "public health narrative" presented in three phases: (1) problem identification (1998-2002) beginning in northern Quebec; (2) problem investigation (2002-2006) in which the issues are successively explored, understood, and conceptualized for all of Quebec, and (3) problem transformation (2006-2009), which discusses major interactions among the stakeholders and the presentation of an Action Plan by a central actor, the Quebec government, in alliance with other stakeholders. In conclusion, we underline the importance, in the current context, of providing for a sustained transdisciplinary adaptation to climatic change. This paper should be helpful for (1) public health professionals confronted with establishing a transdisciplinary approach to a real-world problem other than climate change, (2) professionals in other sectors (such as public safety, built environment) confronted with climate change, who wish to implement transdisciplinary adaptive interventions and/or research, and (3) knowledge users (public and private actors; nongovernment organizations; citizens) from elsewhere in multi-contexts/environments/sectors who wish to promote complex collaborations (with us or not), collective leadership, and "transfrontier knowledge-to-action" for implementing climate change-related adaptation measures.

The burgeoning field of transdisciplinary adaptation research in Quebec (1998–): a climate change-related public health narrative

PubMed Central

Gosselin, Pierre; Bélanger, Diane; Lapaige, Véronique; Labbé, Yolaine

2011-01-01

This paper presents a public health narrative on Quebec’s new climatic conditions and human health, and describes the transdisciplinary nature of the climate change adaptation research currently being adopted in Quebec, characterized by the three phases of problem identification, problem investigation, and problem transformation. A transdisciplinary approach is essential for dealing with complex ill-defined problems concerning human–environment interactions (for example, climate change), for allowing joint research, collective leadership, complex collaborations, and significant exchanges among scientists, decision makers, and knowledge users. Such an approach is widely supported in theory but has proved to be extremely difficult to implement in practice, and those who attempt it have met with heavy resistance, succeeding when they find the occasional opportunity within institutional or social contexts. In this paper we narrate the ongoing struggle involved in tackling the negative effects of climate change in multi-actor contexts at local and regional levels, a struggle that began in a quiet way in 1998. The paper will describe how public health adaptation research is supporting transdisciplinary action and implementation while also preparing for the future, and how this interaction to tackle a life-world problem (adaptation of the Quebec public health sector to climate change) in multi-actors contexts has progressively been established during the last 13 years. The first of the two sections introduces the social context of a Quebec undergoing climate changes. Current climatic conditions and expected changes will be described, and attendant health risks for the Quebec population. The second section addresses the scientific, institutional and normative dimensions of the problem. It corresponds to a “public health narrative” presented in three phases: (1) problem identification (1998–2002) beginning in northern Quebec; (2) problem investigation (2002–2006) in which the issues are successively explored, understood, and conceptualized for all of Quebec, and (3) problem transformation (2006–2009), which discusses major interactions among the stakeholders and the presentation of an Action Plan by a central actor, the Quebec government, in alliance with other stakeholders. In conclusion, we underline the importance, in the current context, of providing for a sustained transdisciplinary adaptation to climatic change. This paper should be helpful for (1) public health professionals confronted with establishing a transdisciplinary approach to a real-world problem other than climate change, (2) professionals in other sectors (such as public safety, built environment) confronted with climate change, who wish to implement transdisciplinary adaptive interventions and/or research, and (3) knowledge users (public and private actors; nongovernment organizations; citizens) from elsewhere in multi-contexts/environments/sectors who wish to promote complex collaborations (with us or not), collective leadership, and “transfrontier knowledge-to-action” for implementing climate change-related adaptation measures. PMID:21966228

A potato model intercomparison across varying climates and productivity levels

USDA-ARS?s Scientific Manuscript database

A potato crop multi-model assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low- (Chinoli, Bolivia and Gisozi, Burundi) and high- (Jyndevad, Denmark and Washington, United States) ...

A framework for considering climate change in transportation and land use scenario planning : lessons learned from an interagency pilot project on Cape Cod.

DOT National Transportation Integrated Search

2011-07-01

The Interagency Transportation, Land Use, and Climate Change Pilot Project utilized a scenario planning process to develop a multi-agency transportation- and land use-focused development strategy for Cape Cod, Massachusetts, with the intention of ach...

Climate Change Impacts on Electricity Demand and Supply in the United States: A Multi-Model Comparison

EPA Science Inventory

This paper compares the climate change impacts on U.S. electricity demand and supply from three models: the Integrated Planning Model (IPM), the Regional Energy Deployment System (ReEDS) model, and GCAM. Rising temperatures cause an appreciable net increase in electricity demand....

Long-term dynamics of a floodplain shallow lake in the Pantanal wetland: Is it all about climate?

PubMed

Silio-Calzada, Ana; Barquín, José; Huszar, Vera L M; Mazzeo, Nestor; Méndez, Fernando; Álvarez-Martínez, Jose Manuel

2017-12-15

Hydrological variability over seasonal and multi-annual timescales strongly shapes the ecological structure and functioning of floodplain ecosystems. The current IPCC climate scenario foresees an increase in the frequency of extreme events. This, in conjunction with other anthropogenic disturbances (e.g., river regulation or land-use changes) poses a serious threat to the natural functioning of these ecosystems. In this study we aimed to i) evaluate the long-term variability of the flooded area of the third largest floodplain lake in the Brazilian Pantanal using remote sensing techniques, and ii) analyze the possible factors influencing this variability. Changes in open-water and riparian floodplain-wetland vegetation areas were mapped by applying an ad hoc-developed remote-sensing method (including a newly developed normalized water index, NWI) to 221 Landsat-Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images, acquired between 1984 and 2011. Added to the lake's natural swing between riparian floodplain-wetland vegetation expansion and retraction, our analyses revealed large interannual changes, grouped into three main periods within the studied time interval. Moreover, our results indicate that this floodplain-lake system is losing open-water area, paired with an increase in riparian floodplain-wetland vegetation. The system's long-term dynamics are not all climate related, but are the result of a combination of drivers. The start of the Manso dam's operation upstream of the studied system, and the subsequent river regulation because of the dam operation, coupled with climatic oscillation appear to be responsible for the observed changes. However, other factors which were not considered in this study might also be important in this process and contributing to the reduction of the system's resilience to droughts (e.g., land-use changes). This study illustrates the serious conservation risks that the Pantanal faces in the near future, given the current climate-change scenario and the accumulation of dam building projects in this region. Copyright © 2017 Elsevier B.V. All rights reserved.

Mapping the Drivers of Climate Change Vulnerability for Australia’s Threatened Species

PubMed Central

Lee, Jasmine R.; Maggini, Ramona; Taylor, Martin F. J.; Fuller, Richard A.

2015-01-01

Effective conservation management for climate adaptation rests on understanding the factors driving species’ vulnerability in a spatially explicit manner so as to direct on-ground action. However, there have been only few attempts to map the spatial distribution of the factors driving vulnerability to climate change. Here we conduct a species-level assessment of climate change vulnerability for a sample of Australia’s threatened species and map the distribution of species affected by each factor driving climate change vulnerability across the continent. Almost half of the threatened species assessed were considered vulnerable to the impacts of climate change: amphibians being the most vulnerable group, followed by plants, reptiles, mammals and birds. Species with more restricted distributions were more likely to show high climate change vulnerability than widespread species. The main factors driving climate change vulnerability were low genetic variation, dependence on a particular disturbance regime and reliance on a particular moisture regime or habitat. The geographic distribution of the species impacted by each driver varies markedly across the continent, for example species impacted by low genetic variation are prevalent across the human-dominated south-east of the country, while reliance on particular moisture regimes is prevalent across northern Australia. Our results show that actions to address climate adaptation will need to be spatially appropriate, and that in some regions a complex suite of factors driving climate change vulnerability will need to be addressed. Taxonomic and geographic variation in the factors driving climate change vulnerability highlights an urgent need for a spatial prioritisation of climate adaptation actions for threatened species. PMID:26017785

Geodetic mass balance of key glaciers across High Mountain Asia: a multi-decadal survey

NASA Astrophysics Data System (ADS)

Maurer, J. M.; Schaefer, J. M.; Rupper, S.; Corley, A. D.

2016-12-01

Glaciers in High Mountain Asia (HMA) supply seasonal meltwater for large populations, yet field observations are scarce and glacier sensitivities are poorly understood. In order to link complex atmospheric driving factors with heterogeneous glacier responses, detailed remote sensing observations of past changes in ice volume are needed. Here we compile a spatially and temporally extensive satellite-based remote sensing record to quantify multi-decadal geodetic mass balance of large mountain glaciers across key regions in HMA, including the Pamir, Himachal Pradesh, Uttarakhand, Nepal, Sikkim, and Bhutan regions. By utilizing declassified spy satellite imagery from the 1970's, ASTER scenes spanning 2000-present, and the ALOS global digital surface model, a methodologically homogenous assessment of regional and individual glacier responses to climate change over several decades is obtained. Although gaps due to low radiometric contrast result in significant uncertainties, the consistent approach across the HMA provides a useful comparison of relative geodetic changes between climatically diverse regions. Various patterns of ice loss are observed, including dynamic retreat of clean-ice glaciers and downwasting of debris-covered glaciers. In particular, we highlight the pronounced thinning and retreat of glaciers undergoing calving into proglacial lakes, which has important implications regarding ongoing and future ice loss of HMA glaciers.

Modeling the Effects of Drought Events on Forest Ecosystem Functioning Historically and Under Scenarios of Climate Change

NASA Astrophysics Data System (ADS)

Ren, J.; Hanan, E. J.; Kolden, C.; Abatzoglou, J. T.; Tague, C.; Liu, M.; Adam, J. C.

2017-12-01

Drought events have been increasing across the western United States in recent years. Many studies have shown that, in the context of climate change, droughts will continue to be stronger, more frequent, and prolonged in the future. However, the response of forest ecosystems to droughts, particularly multi-year droughts, is not well understood. The objectives of this study are to examine how drought events of varying characteristics (e.g. intensity, duration, frequency, etc.) have affected the functioning of forest ecosystems historically, and how changing drought characteristics (including multi-year droughts) may affect forest functioning in a future climate. We utilize the Regional Hydro-Ecological Simulation System (RHESSys) to simulate impacts of both historical droughts and scenarios of future droughts on forest ecosystems. RHESSys is a spatially-distributed and process-based model that captures the interactions between coupled biogeochemical and hydrologic cycles at catchment scales. Here our case study is the Trail Creek catchment of the Big Wood River basin in Idaho, the Northwestern USA. For historical simulations, we use the gridded meteorological data of 1979 to 2016; for future climate scenarios, we utilize downscaled data from GCMs that have been demonstrated to capture drought events in the Northwest of the USA. From these climate projections, we identify various types of drought in intensity and duration, including multi-year drought events. We evaluate the following responses of ecosystems to these events: 1) evapotranspiration and streamflow; 2) gross primary productivity; 3) the post-drought recovery of plant biomass; and 4) the forest functioning and recovery after multi-year droughts. This research is part of an integration project to examine the roles of drought, insect outbreak, and forest management activities on wildfire activity and its impacts. This project will provide improved information for forest managers and communities in the wild urban interface to adapt to climate change.

The Citizen Science Program "H2O SOS: Help Heal the Ocean—Student Operated Solutions: Operation Climate Change" teaches middle and high school students about ocean threats related to climate change through hands-on activities and learning experiences in the field. This is a continuation of the Program presented last year at the Poster Session.

NASA Astrophysics Data System (ADS)

Weiss, N. K.; Wood, J. H.

2017-12-01

TThe Citizen Science Program H2O SOS: Help Heal the Ocean—Student Operated Solutions: Operation Climate Change, teaches middle and high school students about ocean threats related to climate change through hands-on activities and learning experiences in the field. During each session (in-class or after-school as a club), students build an understanding about how climate change impacts our oceans using resources provided by ExplorOcean (hands-on activities, presentations, multi-media). Through a student leadership model, students present lessons to each other, interweaving a deep learning of science, 21st century technology, communication skills, and leadership. After participating in learning experiences and activities related to 6 key climate change concepts: 1) Introduction to climate change, 2) Increased sea temperatures, 3) Ocean acidification, 4) Sea level rise, 5) Feedback mechanisms, and 6) Innovative solutions. H2O SOS- Operation Climate change participants select one focus issue and use it to design a multi-pronged campaign to increase awareness about this issue in their local community. The campaign includes social media, an interactive activity, and a visual component. All participating clubs that meet participation and action goals earn a field trip to Ocean Quest where they dive deeper into their selected issue through hands-on activities, real-world investigations, and interviews or presentations with experts. In addition to self-selected opportunities to showcase their focus issue, teams will participate in one of several key events identified by Ocean Quest.

The Distribution of Climate Change Public Opinion in Canada.

PubMed

Mildenberger, Matto; Howe, Peter; Lachapelle, Erick; Stokes, Leah; Marlon, Jennifer; Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change's causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels.

Advances in desertification and climate change research: Are they accessible for application to enhance adaptive capacity?

NASA Astrophysics Data System (ADS)

Seely, M.; Dirkx, E.; Hager, C.; Klintenberg, P.; Roberts, C.; von Oertzen, D.

2008-12-01

Sustainable living in arid lands is the goal of many, including local residents, policy-makers and scientists. Research into desertification and climate change has the potential to significantly enhance livelihoods of resident people. It also has the potential to contribute to their capacity for risk reduction, improved natural resources management and adaptation to climatic and other changes in multi-stressor systems. This potential is not frequently realised. To effectively ensure that scientific insights and contemporary technologies are applied, active involvement of and feedback from those who apply and use the benefits offered by science and technology are required. Scientists and technologists have to address the diverse, mainly non-technical, aspects required to understand and cope with endemic climate variability, desertification and climate change. They need to appropriately tailor their approaches to disseminate results, and communicate their findings in a way that can be understood and readily implemented by policy-makers, politicians and communities. At the same time, they must learn from experiences gained through implementation by users at all levels. The challenges of making the necessary connections between the combinatory effects of desertification and climate change and their effective application are explored and tested. It was found that several key factors contribute to making the necessary connections to facilitate application on all levels of research advances. These include translation, information dissemination, communication, communication platforms, boundary organisations and leadership contributing to knowledge, motivation and capacity. The purpose of this paper is to assess research experiences from integrated land and water resource management, the application of renewable energy and energy efficiency, and local-level monitoring of natural resources and their application to the challenges of desertification and climate change. The conclusion of this assessment is the identification and description of a common framework that can be applied to address the challenges of desertification and climate change.

Climate shapes the protein abundance of dominant soil bacteria.

PubMed

Bastida, Felipe; Crowther, Tom W; Prieto, Iván; Routh, Devin; García, Carlos; Jehmlich, Nico

2018-05-28

Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of Actinobacteria, Planctomycetes and Proteobacteria, supporting the hypothesis that metabolic activity of some dominant phyla may be closely linked to climate. These results may improve our capacity to construct microbial models that better predict the impact of climate change in ecosystem processes. Copyright © 2018 Elsevier B.V. All rights reserved.

Transformational Leadership Related to School Climate: A Multi-Level Analysis

ERIC Educational Resources Information Center

McCarley, Troy A.; Peters, Michelle L.; Decman, John M.

2016-01-01

Across the nation, quality leadership and positive school climate are critical to the success of every principal, student, and school. As a result, this study examined the relationship between teacher perceptions of the degree to which a principal displays the factors of transformational leadership and the perceived school climate. A purposeful…

Abrupt and severe 20th Century changes in the fire regimes of southeastern Australia: Evidence from a 3000 year multi-proxy analysis

NASA Astrophysics Data System (ADS)

Baker, Patrick; Mooney, Scott; Allen, Kathryn; Willersdorf, Timothy

2015-04-01

Fire is the dominant natural disturbance in southeastern Australia. For millennia it has been the driving force shaping terrestrial ecosystems in the region -- simultaneously killing vegetation and initiating regeneration across whole landscapes. Fire regimes across the region are driven by several factors including climate, vegetation, and ignition sources. Humans have been a significant contributing factor to past and present fire regimes. Prior to European settlement in the late 1700s, Aboriginal Australians used frequent, low-intensity fires to manage vegetation across much of the landscape. European settlement led to the displacement of Aboriginal communities and a shift to active fire suppression and control. This changing approach to fire management is widely believed to have initiated a fundamental shift towards extreme, high-intensity fire events as fuel loads increased. In addition, during the 20th Century prolonged periods of warm, dry conditions have occurred with greater frequency and intensity. The relative importance of climate and fire management practices on contemporary fire regimes is vigorously debated in Australia and is directly relevant to land management policies and their implementation. To put the current fire regime into historical context, we used a multi-proxy approach combining palaeo-charcoal and tree-ring analyses to assess how fire regimes have changed over the last 3000 years in the Snowy Mountains region of southeastern Australia. We found almost no evidence of high-intensity fires in the 3000 years that preceded the 20th Century. However, in the mid-20th Century there is a sudden and dramatic increase in the presence of charcoal and the pulsed establishment of trees across the landscape, suggesting a recent shift from low-intensity fires with minimal charcoal signatures to moderate- to high-intensity fires with substantial charcoal inputs. Importantly, the tree-ring data demonstrate that most of these fires were not stand-replacing and led to the establishment of multiple-age cohorts. While there is a clear shift in the fire regime in the 20th Century, the intensification of fire occurs nearly 150 years after European settlement in this area and has led to the establishment of complex, multi-aged forests across the landscape, suggesting an important interaction between fire management practices associated with European settlement and changing climatic conditions.

Water, land, fire, and forest: Multi-scale determinants of rainforests in the Australian monsoon tropics.

PubMed

Ondei, Stefania; Prior, Lynda D; Williamson, Grant J; Vigilante, Tom; Bowman, David M J S

2017-03-01

The small rainforest fragments found in savanna landscapes are powerful, yet often overlooked, model systems to understand the controls of these contrasting ecosystems. We analyzed the relative effect of climatic variables on rainforest density at a subcontinental level, and employed high-resolution, regional-level analyses to assess the importance of landscape settings and fire activity in determining rainforest density in a frequently burnt Australian savanna landscape. Estimates of rainforest density (ha/km 2 ) across the Northern Territory and Western Australia, derived from preexisting maps, were used to calculate the correlations between rainforest density and climatic variables. A detailed map of the northern Kimberley (Western Australia) rainforests was generated and analyzed to determine the importance of geology and topography in controlling rainforests, and to contrast rainforest density on frequently burnt mainland and nearby islands. In the northwestern Australian, tropics rainforest density was positively correlated with rainfall and moisture index, and negatively correlated with potential evapotranspiration. At a regional scale, rainforests showed preference for complex topographic positions and more fertile geology. Compared with mainland areas, islands had significantly lower fire activity, with no differences between terrain types. They also displayed substantially higher rainforest density, even on level terrain where geomorphological processes do not concentrate nutrients or water. Our multi-scale approach corroborates previous studies that suggest moist climate, infrequent fires, and geology are important stabilizing factors that allow rainforest fragments to persist in savanna landscapes. These factors need to be incorporated in models to predict the future extent of savannas and rainforests under climate change.

Can we use the past as a lens to the future? Using historic events to predict regional grassland and shrubland responses to multi-year drought or wet periods under climate change

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Water availability is the primary driver of ecosystem processes in temperate grasslands and shrublands, but uncertainty in the magnitude and direction of change in precipita...

ExplorOcean H2O SOS: Help Heal the Ocean-Student Operated Solutions: Operation Climate Change

NASA Astrophysics Data System (ADS)

Weiss, N.; Wood, J. H.

2016-12-01

The ExplorOcean H2O SOS: Help Heal the Ocean—Student Operated Solutions: Operation Climate Change, teaches middle and high school students about ocean threats related to climate change through hands-on activities and learning experiences in the field. During each session (in-class or after-school as a club), students build an understanding about how climate change impacts our oceans using resources provided by ExplorOcean (hands-on activities, presentations, multi-media). Through a student leadership model, students present lessons to each other, interweaving a deep learning of science, 21st century technology, communication skills, and leadership. After participating in learning experiences and activities related to 6 key climate change concepts: 1) Introduction to climate change, 2) Increased sea temperatures, 3) Ocean acidification, 4) Sea level rise, 5) Feedback mechanisms, and 6) Innovative solutions. H2O SOS- Operation Climate change participants select one focus issue and use it to design a multi-pronged campaign to increase awareness about this issue in their local community. The campaign includes social media, an interactive activity, and a visual component. All participating clubs that meet participation and action goals earn a field trip to ExplorOcean where they dive deeper into their selected issue through hands-on activities, real-world investigations, and interviews or presentations with experts. In addition to self-selected opportunities to showcase their focus issue, teams will participate in one of several key events identified by ExplorOcean, including ExplorOcean's annual World Oceans Day Expo.

Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies

NASA Astrophysics Data System (ADS)

Casey, M.; Luo, L.; Lang, Y.

2014-12-01

Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.

Multi-model projections of Indian summer monsoon climate changes under A1B scenario

NASA Astrophysics Data System (ADS)

Niu, X.; Wang, S.; Tang, J.

2016-12-01

As part of the Regional Climate Model Intercomparison Project for Asia, the projections of Indian summer monsoon climate changes are constructed using three global climate models (GCMs) and seven regional climate models (RCMs) during 2041-2060 based on the Intergovernmental Panel on Climate Change A1B emission scenario. For the control climate of 1981-2000, most nested RCMs show advantage over the driving GCM of European Centre/Hamburg Fifth Generation (ECHAM5) in the temporal-spatial distributions of temperature and precipitation over Indian Peninsula. Following the driving GCM of ECHAM5, most nested RCMs produce advanced monsoon onset in the control climate. For future climate widespread summer warming is projected over Indian Peninsula by all climate models, with the Multi-RCMs ensemble mean (MME) temperature increasing of 1°C to 2.5°C and the maximum warming center located in northern Indian Peninsula. While for the precipitation, a large inter-model spread is projected by RCMs, with wetter condition in MME projections and significant increase over southern India. Driven by the same GCM, most RCMs project advanced monsoon onset while delayed onset is found in two Regional Climate Model (RegCM3) projections, indicating uncertainty can be expected in the Indian Summer Monsoon onset. All climate models except Conformal-Cubic Atmospheric Model with equal resolution (referred as CCAMP) and two RegCM3 models project stronger summer monsoon during 2041-2060. The disagreement in precipitation projections by RCMs indicates that the surface climate change on regional scale is not only dominated by the large-scale forcing which is provided by driving GCM but also sensitive to RCM' internal physics.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

Progress in modelling agricultural impacts of and adaptations to climate change.

PubMed

Rötter, R P; Hoffmann, M P; Koch, M; Müller, C

2018-06-01

Modelling is a key tool to explore agricultural impacts of and adaptations to climate change. Here we report recent progress made especially referring to the large project initiatives MACSUR and AgMIP; in particular, in modelling potential crop impacts from field to global using multi-model ensembles. We identify two main fields where further progress is necessary: a more mechanistic understanding of climate impacts and management options for adaptation and mitigation; and focusing on cropping systems and integrative multi-scale assessments instead of single season and crops, especially in complex tropical and neglected but important cropping systems. Stronger linking of experimentation with statistical and eco-physiological crop modelling could facilitate the necessary methodological advances. Copyright © 2018 Elsevier Ltd. All rights reserved.

CLIMLINK: Climate forcing factors for marine environmental change during the mid- and late Holocene - a link between the NE Atlantic and the Baltic Sea.

NASA Astrophysics Data System (ADS)

Polovodova Asteman, Irina; Risebrobakken, Bjørg; Bąk, Małgorzata; Binczewska, Anna; Borówka, Ryszard; Dobosz, Sławomir; Jansen, Eystein; Kaniak, Aleksandra; Moros, Matthias; Perner, Kerstin; Sławinska, Joanna

2015-04-01

Climate change has a strong amplifying effect on the environment of marginal seas such as the Baltic Sea. Owing to the connection of the Baltic Sea with the Atlantic (and the resultant pathway of water exchange via the narrow Danish Straits), changes in the Baltic region are suggested to be driven by external oceanic and atmospheric forcing originating in the Atlantic, particularly in the eastern Nordic seas, the Skagerrak, and the Kattegat. CLIMLINK aims to reconstruct mid- to late Holocene ecosystem changes in these regions and identify linkages, common forcing factors and effects for the Baltic Sea on a millennial to decadal time scale. High-resolution sediment records from selected key sites in the Norwegian Trench, and central Baltic Sea are studied by using a multi-proxy approach. Micropalaeontological studies of diatoms and foraminifera are combined with geochemical proxies, such as stable isotopes, Mg/Ca, TOC, TIC, C/N, XRF and magnetic susceptibility in order to achieve a more comprehensive view on environmental changes during the last 6000 to 8000 years. The chronology of the sediment cores is secured by using multiple dating tools: Hg-pollution records, 137Cs, 210Pb, 14C and tephra layers. Herein we present the initial results of the project.

Hot spots of crop production changes at 1.5°C and 2°C

NASA Astrophysics Data System (ADS)

Schleussner, C. F.; Deryng, D.; Mueller, C.; Elliott, J. W.; Saeed, F.; Folberth, C.; Liu, W.; Wang, X.; Pugh, T.

2017-12-01

Studying changes in global and regional crop production is central for assessing the benefits of limiting global average temperature below 1.5ºC versus 2ºC. Projections of future climatic impacts on crop production are commonly focussed on focussing on mean changes. However, substantial risks are posed by extreme weather events such as heat waves and droughts that are of great relevance for imminent policy relevant questions such as price shocks or food security. Preliminary research on the benefits of keeping global average temperature increase below 1.5ºC versus 2ºC above pre-industrial levels has indicated that changes in extreme weather event occurrences will be more pronounced than changes in the mean climate. Here we will present results of crop yield projections for a set of global gridded crop models (GGCMs) for four major staple crops at 1.5°C and 2°C warming above pre-industrial levels using climate forcing data from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. We will assess changes in crop production on the global and regional level, and identify hot spots of change. The unique multi-ensemble setup allows to identify changes in extreme yield losses with multi-year to multi-decadal return periods, and thus elucidate the consequences for global and regional food security.

Climate-Change Impacts on Major Societal and Environmental Sectors: a National View

NASA Astrophysics Data System (ADS)

Melillo, J. M.

2009-05-01

The U.S. Climate Change Science Program's Unified Synthesis Product reports on extant and possible future impacts of climate change for seven sectors at the national level - water resources, energy supply and use, transportation, agriculture, ecosystems, human health and society. The sectoral analyses provide an integrated national picture of the climate-change consequences, now and in the future, for society and the environment, albeit a picture with regional texture. Major report findings for each sector will be presented. In addition to the specific sectoral findings, several overarching messages emerge from this component of the synthesis activity. First, it is important to think about interactions between and among sectors with regard to climate impacts. For example, the projected changes in the timing and amount of precipitation, and hence water supply, will very likely have significant implications for other sectors considered in the report. Changes in water supply have the potential to affect hydropower generation, river transportation, crop timing and management, in-stream ecosystem services including fish habitat, and human health issues related to links between heavy rains ad water-borne diseases. Second, the report concludes that climate-change impacts on the sectors must be considered in the context of a range of environmental and social factors including pollution, population growth, over use of resources, and urbanization. The multi-factor analysis provides insight into our understanding of where, when and how climate change combines with other environmental and social changes to affect the sectors. It also provides some understanding of how these interactions can either amplify or dampen climate-change impacts. This message has profound implications for the design of research programs and information systems at the national, regional and local levels. Furthermore, it demands that a true partnership be forged between the natural and social sciences to more adequately conduct assessments and seek solutions that address the complex challenges that multiple stresses pose. Third, the report notes that the United States is connected to a world that is unevenly vulnerable to climate change and thus will be affected by impacts globally. One example is agriculture. The degree to which climate change affects food production across the globe will affect the demand for our agricultural products and so the profitability of this sector. Fourth, the report highlights the importance of considering the unintended consequences of adaptation measures designed to avert or minimize negative impacts of climate change on various sectors. For example, the "hardening" of coastlines with sea walls and other structures to protect transportation infrastructure against storm surge and sea-level rise eliminates the ability of coastal ecosystems to adapt to these aspects of climate change by inward migration. While this "tradeoff" may be essential, it must be understood that with the loss of coastal ecosystems such as marshlands, comes the loss of the services they provide to society such as their function as nurseries for juvenile fish stocks that are essential for the sustainability of coastal fisheries. The general message about unintended consequences is that system-level analyses must be part of developing intelligent adaptation strategies to meet the challenges of climate change.

Nile Basin Vegetation Response and Vulnerability to Climate Change: A Multi-Sensor Remote Sensing Approach

NASA Astrophysics Data System (ADS)

Yitayew, M.; Didan, K.; Barreto-munoz, A.

2013-12-01

The Nile Basin is one of the world's water resources hotspot that is home to over 437 million people in ten riparian countries with 54% or 238 millions live directly within the basin. The basin like all other basins of the world is facing water resources challenges exacerbated by climate change and increased demand. Nowadays any water resource management action in the basin has to assess the impacts of climate change to be able to predict future water supply and also to help in the negotiation process. Presently, there is a lack of basin wide weather networks to understand sensitivity of the vegetation cover to the impacts of climate change. Vegetation plays major economic and ecological functions in the basin and provides key services ranging from pastoralism, agricultural production, firewood, habitat and food sources for the rich wildlife, as well as a major role in the carbon cycle and climate regulation of the region. Under the threat of climate change and the incessant anthropogenic pressure the distribution and services of the region's ecosystems are projected to change The goal of this work is to assess and characterize how the basin vegetation productivity, distribution, and phenology have changed over the last 30+ years and what are the key climatic drivers of this change. This work makes use of a newly generated multi-sensor long-term land surface data set about vegetation and phenology. Vegetation indices derived from remotely sensed surface reflectance data are commonly used to characterize phenology or vegetation dynamics accurately and with enough spatial and temporal resolution to support change detection. We used more than 30 years of vegetation index and growing season data from AVHRR and MODIS sensors compiled by the Vegetation Index and Phenology laboratory (VIP LAB) at the University of Arizona. Available climate data about precipitation and temperature for the corresponding 30 years period is also used for this analysis. We looked at the changes in the vegetation index signal and to a lesser degree the change in land cover and land use over the last 30 years. Using the climate data record we looked at the drivers of this change. The sensitivity of the basin to climate change was assessed using the multi-linear regression analysis on the covariance of the change in key phenology parameters and the two climate drivers considered here. The overall response was very complex owing to the complicated climate regime and topography of the region. Vegetation response was mostly stable in high lands with a slightly decreasing trend over low and mid-elevations. Over the same period we also observed an intensification of agriculture production corresponding to an increase in percent cover and productivity. We also observed a decrease in forest cover associated with land use conversion. These changes were mostly driven by the precipitation regimes with little impact of the temperature. Climate models project an eventual decrease in precipitation and increase in temperature over the basin. Coupled with these results and observations these projected changes point to major challenges to the vegetation cover, productivity, and associated ecosystem services of the Nile basin.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

PubMed

Mendlik, Thomas; Gobiet, Andreas

In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

An Ensemble Approach to Understanding the ENSO Response to Climate Change

NASA Astrophysics Data System (ADS)

Stevenson, S.; Capotondi, A.; Fasullo, J.; Otto-Bliesner, B. L.

2017-12-01

The dynamics of the El Nino/Southern Oscillation (ENSO) are known to be sensitive to changes in background climate conditions, as well as atmosphere/ocean feedbacks. However, the degree to which shifts in ENSO characteristics can be robustly attributed to external climate forcings remains unknown. Efforts to assess these changes in a multi-model framework are subject to uncertainties due to both differing model physics and internal ENSO variability. New community ensembles created at the National Center for Atmospheric Research and the NOAA Geophysical Fluid Dynamics Laboratory are ideally suited to addressing this problem, providing many realizations of the climate of the 850-2100 period with a combination of both natural and anthropogenic climate forcing factors. Here we analyze the impacts of external forcing on El Nino and La Nina evolution using four sets of simulations: the CESM Last Millennium Ensemble (CESM-LME), which covers the 850-2005 period and provides long-term context for forced responses; the Large Ensemble (CESM-LE), which includes 20th century and 21st century (RCP8.5) projections; the Medium Ensemble (CESM-ME), which is composed of 21st century RCP4.5 projections; and a large ensemble with the GFDL ESM2M, which includes 20th century and RCP8.5 projections. In the CESM, ENSO variance increases slightly over the 20th century in all ensembles, with the effects becoming much larger during the 21st. The slower increase in variance over the 20th century is shown to arise from compensating influences from greenhouse gas (GHG) and anthropogenic aerosol emissions, which give way to GHG-dominated effects by 2100. However, the 21st century variance increase is not robust: CESM and the ESM2M differ drastically in their ENSO projections. The mechanisms for these inter-model differences are discussed, as are the implications for the design of future multi-model ENSO projection experiments.

Crop improvement in the era of climate change: an integrated, multi-disciplinary approach for common bean (Phaseolus vulgaris L.)

USDA-ARS?s Scientific Manuscript database

Two forces are converging that will jointly challenge researchers to design programs that ensure our crop production systems meet the world’s food demand. Climate change will potentially reduce productivity while a global population increase will require more food. If productivity is not increased...

Estimating the future agriculture freight transportation network needs due to climate change using remote sensing and regional climate models.

DOT National Transportation Integrated Search

2016-12-01

A reoccurring challenge with increasing fuel prices is optimization of multi- and inter-modal freight transport to move products most efficiently. Projections for the future of agriculture in the United States (U.S.) combined with regional climate mo...

Report on the projected future climate of the Walnut Gulch Watershed, AZ

USDA-ARS?s Scientific Manuscript database

This report is one of several that provides technical information on projected climate change at selected ARS experimental watersheds across the continental United States. The report is an attachment to the main report of the multi-location project titled “Estimating impacts of projected climate cha...

Hampton Roads climate impact quantification initiative : baseline assessment of the transportation assets & overview of economic analyses useful in quantifying impacts

DOT National Transportation Integrated Search

2016-09-13

The Hampton Roads Climate Impact Quantification Initiative (HRCIQI) is a multi-part study sponsored by the U.S. Department of Transportation (DOT) Climate Change Center with the goals that include developing a cost tool that provides methods for volu...

The emerging threats of climate change on tropical coastal ecosystem services, public health, local economies and livelihood sustainability of small islands: Cumulative impacts and synergies.

PubMed

Hernández-Delgado, E A

2015-12-15

Climate change has significantly impacted tropical ecosystems critical for sustaining local economies and community livelihoods at global scales. Coastal ecosystems have largely declined, threatening the principal source of protein, building materials, tourism-based revenue, and the first line of defense against storm swells and sea level rise (SLR) for small tropical islands. Climate change has also impacted public health (i.e., altered distribution and increased prevalence of allergies, water-borne, and vector-borne diseases). Rapid human population growth has exacerbated pressure over coupled social-ecological systems, with concomitant non-sustainable impacts on natural resources, water availability, food security and sovereignty, public health, and quality of life, which should increase vulnerability and erode adaptation and mitigation capacity. This paper examines cumulative and synergistic impacts of climate change in the challenging context of highly vulnerable small tropical islands. Multiple adaptive strategies of coupled social-ecological ecosystems are discussed. Multi-level, multi-sectorial responses are necessary for adaptation to be successful. Copyright © 2015 Elsevier Ltd. All rights reserved.

Undocumented migration in response to climate change

PubMed Central

Riosmena, Fernando; Hunter, Lori M.; Runfola, Daniel M.

2016-01-01

In the face of climate change induced economic uncertainty, households may employ migration as an adaptation strategy to diversify their livelihood portfolio through remittances. However, it is unclear whether such climate migration will be documented or undocumented. In this study we combine detailed migration histories with daily temperature and precipitation information for 214 weather stations to investigate whether climate change more strongly impacts undocumented or documented migration from 68 rural Mexican municipalities to the U.S. during the years 1986–1999. We employ two measures of climate change, the warm spell duration index (WSDI) and the precipitation during extremely wet days (R99PTOT). Results from multi-level event-history models demonstrate that climate-related international migration from rural Mexico was predominantly undocumented. We conclude that programs to facilitate climate change adaptation in rural Mexico may be more effective in reducing undocumented border crossings than increased border fortification. PMID:27570840

Undocumented migration in response to climate change.

PubMed

Nawrotzki, Raphael J; Riosmena, Fernando; Hunter, Lori M; Runfola, Daniel M

In the face of climate change induced economic uncertainty, households may employ migration as an adaptation strategy to diversify their livelihood portfolio through remittances. However, it is unclear whether such climate migration will be documented or undocumented. In this study we combine detailed migration histories with daily temperature and precipitation information for 214 weather stations to investigate whether climate change more strongly impacts undocumented or documented migration from 68 rural Mexican municipalities to the U.S. during the years 1986-1999. We employ two measures of climate change, the warm spell duration index ( WSDI ) and the precipitation during extremely wet days ( R99PTOT ). Results from multi-level event-history models demonstrate that climate-related international migration from rural Mexico was predominantly undocumented. We conclude that programs to facilitate climate change adaptation in rural Mexico may be more effective in reducing undocumented border crossings than increased border fortification.

Patterns and biases in climate change research on amphibians and reptiles: a systematic review.

PubMed

Winter, Maiken; Fiedler, Wolfgang; Hochachka, Wesley M; Koehncke, Arnulf; Meiri, Shai; De la Riva, Ignacio

2016-09-01

Climate change probably has severe impacts on animal populations, but demonstrating a causal link can be difficult because of potential influences by additional factors. Assessing global impacts of climate change effects may also be hampered by narrow taxonomic and geographical research foci. We review studies on the effects of climate change on populations of amphibians and reptiles to assess climate change effects and potential biases associated with the body of work that has been conducted within the last decade. We use data from 104 studies regarding the effect of climate on 313 species, from 464 species-study combinations. Climate change effects were reported in 65% of studies. Climate change was identified as causing population declines or range restrictions in half of the cases. The probability of identifying an effect of climate change varied among regions, taxa and research methods. Climatic effects were equally prevalent in studies exclusively investigating climate factors (more than 50% of studies) and in studies including additional factors, thus bolstering confidence in the results of studies exclusively examining effects of climate change. Our analyses reveal biases with respect to geography, taxonomy and research question, making global conclusions impossible. Additional research should focus on under-represented regions, taxa and questions. Conservation and climate policy should consider the documented harm climate change causes reptiles and amphibians.

Overview of the Special Issue: A Multi-Model Framework to Achieve Consistent Evaluation of Climate Change Impacts in the United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waldhoff, Stephanie T.; Martinich, Jeremy; Sarofim, Marcus

2015-07-01

The Climate Change Impacts and Risk Analysis (CIRA) modeling exercise is a unique contribution to the scientific literature on climate change impacts, economic damages, and risk analysis that brings together multiple, national-scale models of impacts and damages in an integrated and consistent fashion to estimate climate change impacts, damages, and the benefits of greenhouse gas (GHG) mitigation actions in the United States. The CIRA project uses three consistent socioeconomic, emissions, and climate scenarios across all models to estimate the benefits of GHG mitigation policies: a Business As Usual (BAU) and two policy scenarios with radiative forcing (RF) stabilization targets ofmore » 4.5 W/m2 and 3.7 W/m2 in 2100. CIRA was also designed to specifically examine the sensitivity of results to uncertainties around climate sensitivity and differences in model structure. The goals of CIRA project are to 1) build a multi-model framework to produce estimates of multiple risks and impacts in the U.S., 2) determine to what degree risks and damages across sectors may be lowered from a BAU to policy scenarios, 3) evaluate key sources of uncertainty along the causal chain, and 4) provide information for multiple audiences and clearly communicate the risks and damages of climate change and the potential benefits of mitigation. This paper describes the motivations, goals, and design of the CIRA modeling exercise and introduces the subsequent papers in this special issue.« less

Towards understanding the epidemiology of Neisseria meningitidis in the African meningitis belt: a multi-disciplinary overview.

PubMed

Agier, Lydiane; Martiny, Nadège; Thiongane, Oumy; Mueller, Judith E; Paireau, Juliette; Watkins, Eleanor R; Irving, Tom J; Koutangni, Thibaut; Broutin, Hélène

2017-01-01

Neisseria meningitidis is the major cause of seasonal meningitis epidemics in the African meningitis belt. In the changing context of a reduction in incidence of serogroup A and an increase in incidence of serogroups W and C and of Streptococcus pneumoniae, a better understanding of the determinants driving the disease transmission dynamics remains crucial to improving bacterial meningitis control. The literature was searched to provide a multi-disciplinary overview of the determinants of meningitis transmission dynamics in the African meningitis belt. Seasonal hyperendemicity is likely predominantly caused by increased invasion rates, sporadic localized epidemics by increased transmission rates, and larger pluri-annual epidemic waves by changing population immunity. Carriage likely involves competition for colonization and cross-immunity. The duration of immunity likely depends on the acquisition type. Major risk factors include dust and low humidity, and presumably human contact rates and co-infections; social studies highlighted environmental and dietary factors, with supernatural explanations. Efforts should focus on implementing multi-country, longitudinal seroprevalence and epidemiological studies, validating immune markers of protection, and improving surveillance, including more systematic molecular characterizations of the bacteria. Integrating climate and social factors into disease control strategies represents a high priority for optimizing the public health response and anticipating the geographic evolution of the African meningitis belt. Copyright © 2016. Published by Elsevier Ltd.

Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

2016-08-01

The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.

Forest management under climatic and social uncertainty: trade-offs between reducing climate change impacts and fostering adaptive capacity.

PubMed

Seidl, Rupert; Lexer, Manfred J

2013-01-15

The unabated continuation of anthropogenic greenhouse gas emissions and the lack of an international consensus on a stringent climate change mitigation policy underscore the importance of adaptation for coping with the all but inevitable changes in the climate system. Adaptation measures in forestry have particularly long lead times. A timely implementation is thus crucial for reducing the considerable climate vulnerability of forest ecosystems. However, since future environmental conditions as well as future societal demands on forests are inherently uncertain, a core requirement for adaptation is robustness to a wide variety of possible futures. Here we explicitly address the roles of climatic and social uncertainty in forest management, and tackle the question of robustness of adaptation measures in the context of multi-objective sustainable forest management (SFM). We used the Austrian Federal Forests (AFF) as a case study, and employed a comprehensive vulnerability assessment framework based on ecosystem modeling, multi-criteria decision analysis, and practitioner participation. We explicitly considered climate uncertainty by means of three climate change scenarios, and accounted for uncertainty in future social demands by means of three societal preference scenarios regarding SFM indicators. We found that the effects of climatic and social uncertainty on the projected performance of management were in the same order of magnitude, underlining the notion that climate change adaptation requires an integrated social-ecological perspective. Furthermore, our analysis of adaptation measures revealed considerable trade-offs between reducing adverse impacts of climate change and facilitating adaptive capacity. This finding implies that prioritization between these two general aims of adaptation is necessary in management planning, which we suggest can draw on uncertainty analysis: Where the variation induced by social-ecological uncertainty renders measures aiming to reduce climate change impacts statistically insignificant (i.e., for approximately one third of the investigated management units of the AFF case study), fostering adaptive capacity is suggested as the preferred pathway for adaptation. We conclude that climate change adaptation needs to balance between anticipating expected future conditions and building the capacity to address unknowns and surprises. Copyright © 2012 Elsevier Ltd. All rights reserved.

The impact of SciDAC on US climate change research and the IPCCAR4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wehner, Michael

2005-07-08

SciDAC has invested heavily in climate change research. We offer a candid opinion as to the impact of the DOE laboratories' SciDAC projects on the upcoming Fourth Assessment Report of the Intergovernmental Panel on Climate Change. As a result of the direct importance of climate change to society, climate change research is highly coordinated at the international level. The Intergovernmental Panel on Climate Change (IPCC) is charged with providing regular reports on the state of climate change research to government policymakers. These reports are the product of thousands of scientists efforts. A series of reviews involving both scientists and policymakersmore » make them among the most reviewed documents produced in any scientific field. The high profile of these reports acts a driver to many researchers in the climate sciences. The Fourth Assessment Report (AR4) is scheduled to be released in 2007. SciDAC sponsored research has enabled the United States climate modeling community to make significant contributions to this report. Two large multi-Laboratory SciDAC projects are directly relevant to the activities of the IPCC. The first, entitled ''Collaborative Design and Development of the Community Climate System Model for Terascale Computers'', has made important software contributions to the recently released third version of the Community Climate System Model (CCSM3.0) developed at the National Center for Atmospheric Research. This is a multi-institutional project involving Los Alamos National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The original principal investigators were Robert Malone and John B. Drake. The current principal investigators are Phil Jones and John B. Drake. The second project, entitled ''Earth System Grid II: Turning Climate Datasets into Community Resources'' aims to facilitate the distribution of the copious amounts of data produced by coupled climate model integrations to the general scientific community. This is also a multi-institutional project involving Argonne National Laboratory, Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory and the National Center for Atmospheric Research. The principal investigators are Ian Foster, Don Middleton and Dean Williams. Perhaps most significant among the activities of the ''Collaborative Design'', project was the development of an efficient multi-processor coupling package. CCSM3.0 is an extraordinarily complicated physics code. The fully coupled model consists of separate submodels of the atmosphere, ocean, sea ice and land. In addition, comprehensive biogeochemistry and atmospheric chemistry submodels are under intensive current development. Each of these submodels is a large and sophisticated program in its own right. Furthermore, in the coupled model, each of the submodels, including the coupler, is a separate multiprocessor executable program. The coupler package must efficiently coordinate the communication as well as interpolate or aggregate information between these programs. This regridding function is necessary because each major subsystem (air, water or surface) is allowed to have its own independent grid.« less

Medical aspects of atmosphere pollution in Tbilisi, Georgia.

PubMed

Lagidze, Lamzira; Matchavariani, Lia; Tsivtsivadze, Nodar; Khidasheli, Nargiz; Paichadze, Nino; Motsonelidze, Nargiz; Vakhtangishvili, Maia

2015-01-01

Climate change and its impact on ecosystems is one of the main problem of 21st century. Increase in green house gas in the atmosphere was regarded as an important cause. Atmospheric composition had significantly changed due to intensive technogenic pollution. Increase in aerosol (solid, liquid and gas) concentration had serious impact on human health and raised the level of risk factors for longevity of life. Despite, global character of climatic change and its intensity in numerous ways was influenced by local specificity of regions, their geographical location and meteorological factors. A study on the atmospheric quality (quantitative and percentage estimation of aerosols) of Georgia was carried out. Also the assessment of impact of meteorological and ecological conditions on human health was made for Tbilisi city. A relation between contaminants and meteorological factors was evaluated, particularly gas pollutants were strongly correlated with each other due to their photochemical activity; positive correlation (0.65; 0.69) between air temperature and pollutants. All the contaminants showed negative correlation with relative humidity, due to hydrolyzing ability. On the basis of multi-factorial statistical analysis, correlation between ambulance call, weather type, atmosphere pollution index, change in ground ozone quantity and earth magnetic field were determined. Atmospheric pollution due to dust, carbon, sulfur and nitrogen oxides, ground ozone quantity in Tbilisi significantly exceeded maximum permissible level, that effected human health.

SPAGETTA, a Gridded Weather Generator: Calibration, Validation and its Use for Future Climate

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Rotach, Mathias W.; Huth, Radan

2017-04-01

Spagetta is a new (started in 2016) stochastic multi-site multi-variate weather generator (WG). It can produce realistic synthetic daily (or monthly, or annual) weather series representing both present and future climate conditions at multiple sites (grids or stations irregularly distributed in space). The generator, whose model is based on the Wilks' (1999) multi-site extension of the parametric (Richardson's type) single site M&Rfi generator, may be run in two modes: In the first mode, it is run as a classical generator, which is calibrated in the first step using weather data from multiple sites, and only then it may produce arbitrarily long synthetic time series mimicking the spatial and temporal structure of the calibration weather data. To generate the weather series representing the future climate, the WG parameters are modified according to the climate change scenario, typically derived from GCM or RCM simulations. In the second mode, the user provides only basic information (not necessarily to be realistic) on the temporal and spatial auto-correlation structure of the surface weather variables and their mean annual cycle; the generator itself derives the parameters of the underlying autoregressive model, which produces the multi-site weather series. In the latter mode of operation, the user is allowed to prescribe the spatially varying trend, which is superimposed to the values produced by the generator; this feature has been implemented for use in developing the methodology for assessing significance of trends in multi-site weather series (for more details see another EGU-2017 contribution: Huth and Dubrovsky, 2017, Evaluating collective significance of climatic trends: A comparison of methods on synthetic data; EGU2017-4993). This contribution will focus on the first (classical) mode. The poster will present (a) model of the generator, (b) results of the validation tests made in terms of the spatial hot/cold/dry/wet spells, and (c) results of the pilot climate change impact experiment, in which (i) the WG parameters representing the spatial and temporal variability are modified using the climate change scenarios and then (ii) the effect on the above spatial validation indices derived from the synthetic series produced by the modified WG is analysed. In this experiment, the generator is calibrated using the E-OBS gridded daily weather data for several European regions, and the climate change scenarios are derived from the selected RCM simulation (taken from the CORDEX database).

76 FR 44301 - Information Collection; Homeowner Risk Reduction Behaviors Concerning Wildfire Risks and Climate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-25

... Behaviors Concerning Wildfire Risks and Climate Change Impacts AGENCY: Forest Service, USDA. ACTION: Notice... collection, Homeowner Risk Reduction Behaviors Concerning Wildfire Risks and Climate Change Impacts. The... undertake, and factors that influence these choices, particularly factors related to climate change impacts...

Climatic change controls productivity variation in global grasslands

PubMed Central

Gao, Qingzhu; Zhu, Wenquan; Schwartz, Mark W.; Ganjurjav, Hasbagan; Wan, Yunfan; Qin, Xiaobo; Ma, Xin; Williamson, Matthew A.; Li, Yue

2016-01-01

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2–71.2% during 1982–2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms. PMID:27243565

Rising tides, cumulative impacts and cascading changes to estuarine ecosystem functions.

PubMed

O'Meara, Theresa A; Hillman, Jenny R; Thrush, Simon F

2017-08-31

In coastal ecosystems, climate change affects multiple environmental factors, yet most predictive models are based on simple cause-and-effect relationships. Multiple stressor scenarios are difficult to predict because they can create a ripple effect through networked ecosystem functions. Estuarine ecosystem function relies on an interconnected network of physical and biological processes. Estuarine habitats play critical roles in service provision and represent global hotspots for organic matter processing, nutrient cycling and primary production. Within these systems, we predicted functional changes in the impacts of land-based stressors, mediated by changing light climate and sediment permeability. Our in-situ field experiment manipulated sea level, nutrient supply, and mud content. We used these stressors to determine how interacting environmental stressors influence ecosystem function and compared results with data collected along elevation gradients to substitute space for time. We show non-linear, multi-stressor effects deconstruct networks governing ecosystem function. Sea level rise altered nutrient processing and impacted broader estuarine services ameliorating nutrient and sediment pollution. Our experiment demonstrates how the relationships between nutrient processing and biological/physical controls degrade with environmental stress. Our results emphasise the importance of moving beyond simple physically-forced relationships to assess consequences of climate change in the context of ecosystem interactions and multiple stressors.

Climate Change Risk Perception in Taiwan: Correlation with Individual and Societal Factors

PubMed Central

2018-01-01

This study differentiates the risk perception and influencing factors of climate change along the dimensions of global severity and personal threat. Using the 2013 Taiwan Social Change Survey (TSGS) data (N = 2001) as a representative sample of adults from Taiwan, we investigated the influencing factors of the risk perceptions of climate change in these two dimensions (global severity and personal threat). Logistic regression models were used to examine the correlations of individual factors (gender, age, education, climate-related disaster experience and risk awareness, marital status, employment status, household income, and perceived social status) and societal factors (religion, organizational embeddedness, and political affiliations) with the above two dimensions. The results demonstrate that climate-related disaster experience has no significant impact on either the perception of global severity or the perception of personal impact. However, climate-related risk awareness (regarding typhoons, in particular) is positively associated with both dimensions of the perceived risks of climate change. With higher education, individuals are more concerned about global severity than personal threat. Regarding societal factors, the supporters of political parties have higher risk perceptions of climate change than people who have no party affiliation. Religious believers have higher risk perceptions of personal threat than non-religious people. This paper ends with a discussion about the effectiveness of efforts to enhance risk perception of climate change with regard to global severity and personal threat. PMID:29316685

Climate Change Risk Perception in Taiwan: Correlation with Individual and Societal Factors.

PubMed

Sun, Yingying; Han, Ziqiang

2018-01-08

This study differentiates the risk perception and influencing factors of climate change along the dimensions of global severity and personal threat. Using the 2013 Taiwan Social Change Survey (TSGS) data (N = 2001) as a representative sample of adults from Taiwan, we investigated the influencing factors of the risk perceptions of climate change in these two dimensions (global severity and personal threat). Logistic regression models were used to examine the correlations of individual factors (gender, age, education, climate-related disaster experience and risk awareness, marital status, employment status, household income, and perceived social status) and societal factors (religion, organizational embeddedness, and political affiliations) with the above two dimensions. The results demonstrate that climate-related disaster experience has no significant impact on either the perception of global severity or the perception of personal impact. However, climate-related risk awareness (regarding typhoons, in particular) is positively associated with both dimensions of the perceived risks of climate change. With higher education, individuals are more concerned about global severity than personal threat. Regarding societal factors, the supporters of political parties have higher risk perceptions of climate change than people who have no party affiliation. Religious believers have higher risk perceptions of personal threat than non-religious people. This paper ends with a discussion about the effectiveness of efforts to enhance risk perception of climate change with regard to global severity and personal threat.

The Distribution of Climate Change Public Opinion in Canada

PubMed Central

Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change’s causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels. PMID:27486659

Assessing Inter-Sectoral Climate Change Risks: The Role of ISIMIP

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Arnell, Nigel W.; Ebi, Kristie L.; Lotze-Campen, Hermann; Raes, Frank; Rapley, Chris; Smith, Mark Stafford; Cramer, Wolfgang; Frieler, Katja; Reyer, Christopher P. O.;

Dominant climatic factors driving annual runoff changes at the catchment scale across China

NASA Astrophysics Data System (ADS)

Huang, Zhongwei; Yang, Hanbo; Yang, Dawen

2016-07-01

With global climate changes intensifying, the hydrological response to climate changes has attracted more attention. It is beneficial not only for hydrology and ecology but also for water resource planning and management to understand the impact of climate change on runoff. In addition, there are large spatial variations in climate type and geographic characteristics across China. To gain a better understanding of the spatial variation of the response of runoff to changes in climatic factors and to detect the dominant climatic factors driving changes in annual runoff, we chose the climate elasticity method proposed by Yang and Yang (2011). It is shown that, in most catchments of China, increasing air temperature and relative humidity have negative impacts on runoff, while declining net radiation and wind speed have positive impacts on runoff, which slow the overall decline in runoff. The dominant climatic factors driving annual runoff are precipitation in most parts of China, net radiation mainly in some catchments of southern China, air temperature and wind speed mainly in some catchments in northern China.

The strength of strategically placed in situ networks: The Critical Zone Observatory Program (Invited)

NASA Astrophysics Data System (ADS)

Bauer, S.; Benisch, K.; Li, D.; Beyer, C.; Mitiku, A. B.; Graupner, B.

2011-12-01

The Critical Zone Observatory (CZO) program, initiated by the U.S. National Science Foundation in 2007 with 3 sites, was expanded to 6 sites in 2009 and is expected to grow to at least 8 sites in FY 2014. The CZO program is now maturing into a coordinated network that enables scientific research around terrestrial fluxes of water, carbon and nutrients and informs societal questions around resource management and adaptation to climate change. Individual CZOs have contributed to understanding of the influences of disturbances and of changes in climate on fluxes and stores in critical ecosystems, and to a better predictive ability. CZOs have enabled the disciplinary integration needed to consider controlling processes together, from bedrock to boundary layer, and over sub-daily to millennial or longer times. Together, the CZO network has shown the role of climate versus disturbance on rain, snowfall and snowmelt reaching the ground surface, and the influences of climate, disturbance and regolith properties on partitioning of infiltrated water into evapotranspiration versus streamflow. The influence of disturbance is manifest both through abiotic factors, e.g. boundary-layer meteorology and turbulence, and through biotic influences, e.g. changes in vegetation density due to fire or disease, and thus interception and evapotranspiration. Climatic influences are overlain on this, including i) changes in rain versus snowfall and thus snowpack and soil-water storage, and ii) growing season and thus evapotranspiration. Carbon and nutrient fluxes are closely linked to those of water. Thus rich data sets and improved models from the CZO sites together provide a better understanding of the bi-directional feedbacks between vegetation structure, regolith properties and climate. Going forward, the CZO network as a whole offers well-instrumented sites with many common measurements and multi-disciplinary data across gradient of climate, parent material, vegetation structure and regolith properties. Measurements are at scales that are sufficiently large for research involving water, carbon or nutrient balances. Results are relevant to help guide decisions around vegetation management, and to understand the water, carbon and nutrient implications of vegetation-management options. The CZO network is a community platform for research, with the common, long-term observations across the multiple sites a resource available to all for multi-disciplinary critical-zone science.

The strength of strategically placed in situ networks: The Critical Zone Observatory Program (Invited)

NASA Astrophysics Data System (ADS)

Bales, R. C.; Brooks, P. D.; Molotch, N. P.

2013-12-01

The Critical Zone Observatory (CZO) program, initiated by the U.S. National Science Foundation in 2007 with 3 sites, was expanded to 6 sites in 2009 and is expected to grow to at least 8 sites in FY 2014. The CZO program is now maturing into a coordinated network that enables scientific research around terrestrial fluxes of water, carbon and nutrients and informs societal questions around resource management and adaptation to climate change. Individual CZOs have contributed to understanding of the influences of disturbances and of changes in climate on fluxes and stores in critical ecosystems, and to a better predictive ability. CZOs have enabled the disciplinary integration needed to consider controlling processes together, from bedrock to boundary layer, and over sub-daily to millennial or longer times. Together, the CZO network has shown the role of climate versus disturbance on rain, snowfall and snowmelt reaching the ground surface, and the influences of climate, disturbance and regolith properties on partitioning of infiltrated water into evapotranspiration versus streamflow. The influence of disturbance is manifest both through abiotic factors, e.g. boundary-layer meteorology and turbulence, and through biotic influences, e.g. changes in vegetation density due to fire or disease, and thus interception and evapotranspiration. Climatic influences are overlain on this, including i) changes in rain versus snowfall and thus snowpack and soil-water storage, and ii) growing season and thus evapotranspiration. Carbon and nutrient fluxes are closely linked to those of water. Thus rich data sets and improved models from the CZO sites together provide a better understanding of the bi-directional feedbacks between vegetation structure, regolith properties and climate. Going forward, the CZO network as a whole offers well-instrumented sites with many common measurements and multi-disciplinary data across gradient of climate, parent material, vegetation structure and regolith properties. Measurements are at scales that are sufficiently large for research involving water, carbon or nutrient balances. Results are relevant to help guide decisions around vegetation management, and to understand the water, carbon and nutrient implications of vegetation-management options. The CZO network is a community platform for research, with the common, long-term observations across the multiple sites a resource available to all for multi-disciplinary critical-zone science.

Can metric-based approaches really improve multi-model climate projections? A perfect model framework applied to summer temperature change in France.

NASA Astrophysics Data System (ADS)

Boé, Julien; Terray, Laurent

2014-05-01

Ensemble approaches for climate change projections have become ubiquitous. Because of large model-to-model variations and, generally, lack of rationale for the choice of a particular climate model against others, it is widely accepted that future climate change and its impacts should not be estimated based on a single climate model. Generally, as a default approach, the multi-model ensemble mean (MMEM) is considered to provide the best estimate of climate change signals. The MMEM approach is based on the implicit hypothesis that all the models provide equally credible projections of future climate change. This hypothesis is unlikely to be true and ideally one would want to give more weight to more realistic models. A major issue with this alternative approach lies in the assessment of the relative credibility of future climate projections from different climate models, as they can only be evaluated against present-day observations: which present-day metric(s) should be used to decide which models are "good" and which models are "bad" in the future climate? Once a supposedly informative metric has been found, other issues arise. What is the best statistical method to combine multiple models results taking into account their relative credibility measured by a given metric? How to be sure in the end that the metric-based estimate of future climate change is not in fact less realistic than the MMEM? It is impossible to provide strict answers to those questions in the climate change context. Yet, in this presentation, we propose a methodological approach based on a perfect model framework that could bring some useful elements of answer to the questions previously mentioned. The basic idea is to take a random climate model in the ensemble and treat it as if it were the truth (results of this model, in both past and future climate, are called "synthetic observations"). Then, all the other members from the multi-model ensemble are used to derive thanks to a metric-based approach a posterior estimate of climate change, based on the synthetic observation of the metric. Finally, it is possible to compare the posterior estimate to the synthetic observation of future climate change to evaluate the skill of the method. The main objective of this presentation is to describe and apply this perfect model framework to test different methodological issues associated with non-uniform model weighting and similar metric-based approaches. The methodology presented is general, but will be applied to the specific case of summer temperature change in France, for which previous works have suggested potentially useful metrics associated with soil-atmosphere and cloud-temperature interactions. The relative performances of different simple statistical approaches to combine multiple model results based on metrics will be tested. The impact of ensemble size, observational errors, internal variability, and model similarity will be characterized. The potential improvements associated with metric-based approaches compared to the MMEM is terms of errors and uncertainties will be quantified.

The nexus between climate change, ecosystem services and human health: Towards a conceptual framework.

PubMed

Chiabai, Aline; Quiroga, Sonia; Martinez-Juarez, Pablo; Higgins, Sahran; Taylor, Tim

2018-09-01

This paper addresses the impact that changes in natural ecosystems can have on health and wellbeing focusing on the potential co-benefits that green spaces could provide when introduced as climate change adaptation measures. Ignoring such benefits could lead to sub-optimal planning and decision-making. A conceptual framework, building on the ecosystem-enriched Driver, Pressure, State, Exposure, Effect, Action model (eDPSEEA), is presented to aid in clarifying the relational structure between green spaces and human health, taking climate change as the key driver. The study has the double intention of (i) summarising the literature with a special emphasis on the ecosystem and health perspectives, as well as the main theories behind these impacts, and (ii) modelling these findings into a framework that allows for multidisciplinary approaches to the underlying relations between human health and green spaces. The paper shows that while the literature based on the ecosystem perspective presents a well-documented association between climate, health and green spaces, the literature using a health-based perspective presents mixed evidence in some cases. The role of contextual factors and the exposure mechanism are rarely addressed. The proposed framework could serve as a multidisciplinary knowledge platform for multi-perspecitve analysis and discussion among experts and stakeholders, as well as to support the operationalization of quantitative assessment and modelling exercises. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Mitigating and adapting to climate change: multi-functional and multi-scale assessment of green urban infrastructure.

PubMed

Demuzere, M; Orru, K; Heidrich, O; Olazabal, E; Geneletti, D; Orru, H; Bhave, A G; Mittal, N; Feliu, E; Faehnle, M

2014-12-15

In order to develop climate resilient urban areas and reduce emissions, several opportunities exist starting from conscious planning and design of green (and blue) spaces in these landscapes. Green urban infrastructure has been regarded as beneficial, e.g. by balancing water flows, providing thermal comfort. This article explores the existing evidence on the contribution of green spaces to climate change mitigation and adaptation services. We suggest a framework of ecosystem services for systematizing the evidence on the provision of bio-physical benefits (e.g. CO2 sequestration) as well as social and psychological benefits (e.g. improved health) that enable coping with (adaptation) or reducing the adverse effects (mitigation) of climate change. The multi-functional and multi-scale nature of green urban infrastructure complicates the categorization of services and benefits, since in reality the interactions between various benefits are manifold and appear on different scales. We will show the relevance of the benefits from green urban infrastructures on three spatial scales (i.e. city, neighborhood and site specific scales). We will further report on co-benefits and trade-offs between the various services indicating that a benefit could in turn be detrimental in relation to other functions. The manuscript identifies avenues for further research on the role of green urban infrastructure, in different types of cities, climates and social contexts. Our systematic understanding of the bio-physical and social processes defining various services allows targeting stressors that may hamper the provision of green urban infrastructure services in individual behavior as well as in wider planning and environmental management in urban areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adding Semantics and OPM Ontology for the Provenance of Multi-sensor Merged Climate Data Records. Now What About Reproducibility?

NASA Astrophysics Data System (ADS)

Hua, H.; Wilson, B. D.; Manipon, G.; Pan, L.; Fetzer, E.

2011-12-01

Multi-decadal climate data records are critical to studying climate variability and change. These often also require merging data from multiple instruments such as those from NASA's A-Train that contain measurements covering a wide range of atmospheric conditions and phenomena. Multi-decadal climate data record of water vapor measurements from sensors on A-Train, operational weather, and other satellites are being assembled from existing data sources, or produced from well-established methods published in peer-reviewed literature. However, the immense volume and inhomogeneity of data often requires an "exploratory computing" approach to product generation where data is processed in a variety of different ways with varying algorithms, parameters, and code changes until an acceptable intermediate product is generated. This process is repeated until a desirable final merged product can be generated. Typically the production legacy is often lost due to the complexity of processing steps that were tried along the way. The data product information associated with source data, processing methods, parameters used, intermediate product outputs, and associated materials are often hidden in each of the trials and scattered throughout the processing system(s). We will discuss methods to help users better capture and explore the production legacy of the data, metadata, ancillary files, code, and computing environment changes used during the production of these merged and multi-sensor data products. By leveraging existing semantic and provenance tools, we can capture sufficient information to enable users to track, perform faceted searches, and visualize the provenance of the products and processing lineage. We will explore if sufficient provenance information can be captured to enable science reproducibility of these climate data records.

The climate change-infectious disease nexus: is it time for climate change syndemics?

PubMed

Heffernan, Claire

2013-12-01

Conceptualizing climate as a distinct variable limits our understanding of the synergies and interactions between climate change and the range of abiotic and biotic factors, which influence animal health. Frameworks such as eco-epidemiology and the epi-systems approach, while more holistic, view climate and climate change as one of many discreet drivers of disease. Here, I argue for a new paradigmatic framework: climate-change syndemics. Climate-change syndemics begins from the assumption that climate change is one of many potential influences on infectious disease processes, but crucially is unlikely to act independently or in isolation; and as such, it is the inter-relationship between factors that take primacy in explorations of infectious disease and climate change. Equally importantly, as climate change will impact a wide range of diseases, the frame of analysis is at the collective rather than individual level (for both human and animal infectious disease) across populations.

Diverse Responses of Global Vegetation to Climate Changes: Spatial Patterns and Time-lag Effects

NASA Astrophysics Data System (ADS)

Wu, D.; Zhao, X.; Zhou, T.; Huang, K.; Xu, W.

2014-12-01

Global climate changes have enormous influences on vegetation growth, meanwhile, response of vegetation to climate express space diversity and time-lag effects, which account for spatial-temporal disparities of climate change and spatial heterogeneity of ecosystem. Revelation of this phenomenon will help us further understanding the impact of climate change on vegetation. Assessment and forecast of global environmental change can be also improved under further climate change. Here we present space diversity and time-lag effects patterns of global vegetation respond to three climate factors (temperature, precipitation and solar radiation) based on quantitative analysis of satellite data (NDVI) and Climate data (Climate Research Unit). We assessed the time-lag effects of global vegetation to main climate factors based on the great correlation fitness between NDVI and the three climate factors respectively among 0-12 months' temporal lags. On this basis, integrated response model of NDVI and the three climate factors was built to analyze contribution of different climate factors to vegetation growth with multiple regression model and partial correlation model. In the result, different vegetation types have distinct temporal lags to the three climate factors. For the precipitation, temporal lags of grasslands are the shortest while the evergreen broad-leaf forests are the longest, which means that grasslands are more sensitive to precipitation than evergreen broad-leaf forests. Analysis of different climate factors' contribution to vegetation reveal that vegetation are dominated by temperature in the high northern latitudes; they are mainly restricted by precipitation in arid and semi-arid areas (Australia, Western America); in humid areas of low and intermediate latitudes (Amazon, Eastern America), vegetation are mainly influenced by solar radiation. Our results reveal the time-lag effects and major driving factors of global vegetation growth and explain the spatiotemporal variations of global vegetation in last 30 years. Significantly, it is as well as in forecasting and assessing the influences of future climate change on the vegetation dynamics. This work was supported by the High Technology Research and Development Program of China (Grant NO.2013AA122801).

Multi-Scale Infrastructure Assessment

EPA Science Inventory

The U.S. Environmental Protection Agency’s (EPA) multi-scale infrastructure assessment project supports both water resource adaptation to climate change and the rehabilitation of the nation’s aging water infrastructure by providing tools, scientific data and information to progra...

The Greatest Challenge Ever for Mankind, Requiring Policies of Accelerating Hardship and Implementation Difficulty

NASA Astrophysics Data System (ADS)

Wilson, John

2015-04-01

Providing energy for the contemporary world has resulted in a multi-variable problem in which a confluence of historical anomalies and economic, psychological, political, and demographic factors thwart efforts to prevent significant harm from increasing atmospheric CO2. This unlikely combination has created the perfect storm in which the warnings by scientists are ineffective. Global warming is occurring simultaneously with increased population, some dysfunctional political institutions, ascendency of oversimplified economic theory, campaigns to discredit scientists, misinterpretation of the meaning of noise in the Milankovitch climate cycles, and substantially improved hydrocarbon extraction methods. These factors are compounded by traits of human nature, such as greed and resistance to changing the familiar and discontinuing profitable endeavors. The idea that future people are equal with us may not be widely supported, yet this value is the foundation of climate change action. History shows that most people and nations will not take appropriate measures until forced, yet the cost increases as action is delayed. This makes appropriate policies even more extreme and difficult to accomplish as more wealth is consumed in treating global warming symptoms.

Microbial responses to multi-factor climate change: effects on soil enzymes.

PubMed

Steinweg, J Megan; Dukes, Jeffrey S; Paul, Eldor A; Wallenstein, Matthew D

2013-01-01

The activities of extracellular enzymes, the proximate agents of decomposition in soils, are known to depend strongly on temperature, but less is known about how they respond to changes in precipitation patterns, and the interaction of these two components of climate change. Both enzyme production and turnover can be affected by changes in temperature and soil moisture, thus it is difficult to predict how enzyme pool size may respond to altered climate. Soils from the Boston-Area Climate Experiment (BACE), which is located in an old field (on abandoned farmland), were used to examine how climate variables affect enzyme activities and microbial biomass carbon (MBC) in different seasons and in soils exposed to a combination of three levels of precipitation treatments (ambient, 150% of ambient during growing season, and 50% of ambient year-round) and four levels of warming treatments (unwarmed to ~4°C above ambient) over the course of a year. Warming, precipitation and season had very little effect on potential enzyme activity. Most models assume that enzyme dynamics follow microbial biomass, because enzyme production should be directly controlled by the size and activity of microbial biomass. We observed differences among seasons and treatments in mass-specific potential enzyme activity, suggesting that this assumption is invalid. In June 2009, mass-specific potential enzyme activity, using chloroform fumigation-extraction MBC, increased with temperature, peaking under medium warming and then declining under the highest warming. This finding suggests that either enzyme production increased with temperature or turnover rates decreased. Increased maintenance costs associated with warming may have resulted in increased mass-specific enzyme activities due to increased nutrient demand. Our research suggests that allocation of resources to enzyme production could be affected by climate-induced changes in microbial efficiency and maintenance costs.

Characterizing environmental change in interior Alaska (1982-2012) using multi-temporal, multi-scale remote sensing data and field measurements

Treesearch

Hans-Erik Andersen; Robert. Pattison

2012-01-01

We investigate how vegetation in the Tanana Valley of interior Alaska (120,000 km2) has responded to a changing climate over the preceding three decades (1982-2012). Expected impacts include: 1) drying of wetlands and subsequent encroachment of woody vegetation into areas previously dominated by herbaceous and bryoid vegetation types, 2) changes...

Impacts of climate change on the hydrological cycle over France and associated uncertainties

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Éric; Gailhard, Joël

2018-05-01

This study deals with the evolution of the hydrological cycle over France during the 21st century. A large multi-member, multi-scenario, and multi-model ensemble of climate projections is downscaled with a new statistical method to drive a physically-based hydrological model with recent improvements. For a business-as-usual scenario, annual precipitation changes generally remain small, except over southern France, where decreases close to 20% are projected. Annual streamflows roughly decrease by 10% (±20%) on the Seine, by 20% (±20%) on the Loire, by 20% (±15%) on the Rhone and by 40% (±15%) on the Garonne. Attenuation measures, as implied by the other scenarios analyzed, lead to less severe changes. However, even with a scenario generally compatible with a limitation of global warming to two degrees, some notable impacts may still occur, with for example a decrease in summer river flows close to 25% for the Garonne.

Impacts of boundary condition changes on regional climate projections over West Africa

NASA Astrophysics Data System (ADS)

Kim, Jee Hee; Kim, Yeonjoo; Wang, Guiling

2017-06-01

Future projections using regional climate models (RCMs) are driven with boundary conditions (BCs) typically derived from global climate models. Understanding the impact of the various BCs on regional climate projections is critical for characterizing their robustness and uncertainties. In this study, the International Center for Theoretical Physics Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of different aspects of boundary conditions, including lateral BCs and sea surface temperature (SST), on projected future changes of regional climate in West Africa, and BCs from the coupled European Community-Hamburg Atmospheric Model 5/Max Planck Institute Ocean Model are used as an example. Historical, future, and several sensitivity experiments are conducted with various combinations of BCs and CO2 concentration, and differences among the experiments are compared to identify the most important drivers for RCMs. When driven by changes in all factors, the RegCM4-produced future climate changes include significantly drier conditions in Sahel and wetter conditions along the Guinean coast. Changes in CO2 concentration within the RCM domain alone or changes in wind vectors at the domain boundaries alone have minor impact on projected future climate changes. Changes in the atmospheric humidity alone at the domain boundaries lead to a wetter Sahel due to the northward migration of rain belts during summer. This impact, although significant, is offset and dominated by changes of other BC factors (primarily temperature) that cause a drying signal. Future changes of atmospheric temperature at the domain boundaries combined with SST changes over oceans are sufficient to cause a future climate that closely resembles the projection that accounts for all factors combined. Therefore, climate variability and changes simulated by RCMs depend primarily on the variability and change of temperature aspects of the RCM BCs. Moreover, it is found that the response of the RCM climate to different climate change factors is roughly linear in that the projected changes driven by combined factors are close to the sum of projected changes due to each individual factor alone at least for long-term averages. Findings from this study are important for understanding the source(s) of uncertainties in regional climate projections and for designing innovative approaches to climate downscaling and impact assessment.

Maximum warming occurs about one decade after carbon dioxide emission

NASA Astrophysics Data System (ADS)

Ricke, K.; Caldeira, K.

2014-12-01

There has been a long tradition of estimating the amount of climate change that would result from various carbon dioxide emission or concentration scenarios but there has been relatively little quantitative analysis of how long it takes to feel the consequences of an individual carbon dioxide emission. Using conjoined results of recent carbon-cycle and physical-climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6 to 30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. To characterize the carbon cycle uncertainty associated with the global temperature response to a carbon dioxide emission today, we use fits to the time series of carbon dioxide concentrations from a CO2-impulse response function model intercomparison project's 15 ensemble members (1). To characterize both the uncertainty in climate sensitivity and in the thermal inertia of the climate system, we use fits to the time series of global temperature change from the Coupled Model Intercomparison Project phase 5 (CMIP5; 2) abrupt4xco2 experiment's 20 ensemble's members separating the effects of each uncertainty factors using one of two simple physical models for each CMIP5 climate model. This yields 6,000 possible combinations of these three factors using a standard convolution integral approach. Our results indicate that benefits of avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While the relevant time lags imposed by the climate system are substantially shorter than a human lifetime, they are substantially longer than the typical political election cycle, making the delay and its associated uncertainties both economically and politically significant. References: 1. Joos F et al. (2013) Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmos Chem Phys 13:2793-2825. 2. Taylor KE, Stouffer RJ, Meehl GA (2011) An Overview of CMIP5 and the Experiment Design. Bull Am Meteorol Soc 93:485-498.

LGM permafrost distribution: how well can the latest PMIP multi-model ensembles perform reconstruction?

NASA Astrophysics Data System (ADS)

Saito, K.; Sueyoshi, T.; Marchenko, S.; Romanovsky, V.; Otto-Bliesner, B.; Walsh, J.; Bigelow, N.; Hendricks, A.; Yoshikawa, K.

2013-08-01

Here, global-scale frozen ground distribution from the Last Glacial Maximum (LGM) has been reconstructed using multi-model ensembles of global climate models, and then compared with evidence-based knowledge and earlier numerical results. Modeled soil temperatures, taken from Paleoclimate Modelling Intercomparison Project phase III (PMIP3) simulations, were used to diagnose the subsurface thermal regime and determine underlying frozen ground types for the present day (pre-industrial; 0 kya) and the LGM (21 kya). This direct method was then compared to an earlier indirect method, which categorizes underlying frozen ground type from surface air temperature, applying to both the PMIP2 (phase II) and PMIP3 products. Both direct and indirect diagnoses for 0 kya showed strong agreement with the present-day observation-based map. The soil temperature ensemble showed a higher diversity around the border between permafrost and seasonally frozen ground among the models, partly due to varying subsurface processes, implementation, and settings. The area of continuous permafrost estimated by the PMIP3 multi-model analysis through the direct (indirect) method was 26.0 (17.7) million km2 for LGM, in contrast to 15.1 (11.2) million km2 for the pre-industrial control, whereas seasonally frozen ground decreased from 34.5 (26.6) million km2 to 18.1 (16.0) million km2. These changes in area resulted mainly from a cooler climate at LGM, but from other factors as well, such as the presence of huge land ice sheets and the consequent expansion of total land area due to sea-level change. LGM permafrost boundaries modeled by the PMIP3 ensemble - improved over those of the PMIP2 due to higher spatial resolutions and improved climatology - also compared better to previous knowledge derived from geomorphological and geocryological evidence. Combinatorial applications of coupled climate models and detailed stand-alone physical-ecological models for the cold-region terrestrial, paleo-, and modern climates will advance our understanding of the functionality and variability of the frozen ground subsystem in the global eco-climate system.

Patterns and biases in climate change research on amphibians and reptiles: a systematic review

PubMed Central

2016-01-01

Climate change probably has severe impacts on animal populations, but demonstrating a causal link can be difficult because of potential influences by additional factors. Assessing global impacts of climate change effects may also be hampered by narrow taxonomic and geographical research foci. We review studies on the effects of climate change on populations of amphibians and reptiles to assess climate change effects and potential biases associated with the body of work that has been conducted within the last decade. We use data from 104 studies regarding the effect of climate on 313 species, from 464 species–study combinations. Climate change effects were reported in 65% of studies. Climate change was identified as causing population declines or range restrictions in half of the cases. The probability of identifying an effect of climate change varied among regions, taxa and research methods. Climatic effects were equally prevalent in studies exclusively investigating climate factors (more than 50% of studies) and in studies including additional factors, thus bolstering confidence in the results of studies exclusively examining effects of climate change. Our analyses reveal biases with respect to geography, taxonomy and research question, making global conclusions impossible. Additional research should focus on under-represented regions, taxa and questions. Conservation and climate policy should consider the documented harm climate change causes reptiles and amphibians. PMID:27703684

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Farmers' perceptions of climate change and agricultural adaptation strategies in rural Sahel.

PubMed

Mertz, Ole; Mbow, Cheikh; Reenberg, Anette; Diouf, Awa

2009-05-01

Farmers in the Sahel have always been facing climatic variability at intra- and inter-annual and decadal time scales. While coping and adaptation strategies have traditionally included crop diversification, mobility, livelihood diversification, and migration, singling out climate as a direct driver of changes is not so simple. Using focus group interviews and a household survey, this study analyzes the perceptions of climate change and the strategies for coping and adaptation by sedentary farmers in the savanna zone of central Senegal. Households are aware of climate variability and identify wind and occasional excess rainfall as the most destructive climate factors. Households attribute poor livestock health, reduced crop yields and a range of other problems to climate factors, especially wind. However, when questions on land use and livelihood change are not asked directly in a climate context, households and groups assign economic, political, and social rather than climate factors as the main reasons for change. It is concluded that the communities studied have a high awareness of climate issues, but climatic narratives are likely to influence responses when questions mention climate. Change in land use and livelihood strategies is driven by adaptation to a range of factors of which climate appears not to be the most important. Implications for policy-making on agricultural and economic development will be to focus on providing flexible options rather than specific solutions to uncertain climate.

The Political Economy of Health Co-Benefits: Embedding Health in the Climate Change Agenda.

PubMed

Workman, Annabelle; Blashki, Grant; Bowen, Kathryn J; Karoly, David J; Wiseman, John

2018-04-04

A complex, whole-of-economy issue such as climate change demands an interdisciplinary, multi-sectoral response. However, evidence suggests that human health has remained elusive in its influence on the development of ambitious climate change mitigation policies for many national governments, despite a recognition that the combustion of fossil fuels results in pervasive short- and long-term health consequences. We use insights from literature on the political economy of health and climate change, the science–policy interface and power in policy-making, to identify additional barriers to the meaningful incorporation of health co-benefits into climate change mitigation policy development. Specifically, we identify four key interrelated areas where barriers may exist in relation to health co-benefits: discourse, efficiency, vested interests and structural challenges. With these insights in mind, we argue that the current politico-economic paradigm in which climate change is situated and the processes used to develop climate change mitigation policies do not adequately support accounting for health co-benefits. We present approaches for enhancing the role of health co-benefits in the development of climate change mitigation policies to ensure that health is embedded in the broader climate change agenda.

The Political Economy of Health Co-Benefits: Embedding Health in the Climate Change Agenda

PubMed Central

Workman, Annabelle; Blashki, Grant; Bowen, Kathryn J.; Karoly, David J.; Wiseman, John

2018-01-01

A complex, whole-of-economy issue such as climate change demands an interdisciplinary, multi-sectoral response. However, evidence suggests that human health has remained elusive in its influence on the development of ambitious climate change mitigation policies for many national governments, despite a recognition that the combustion of fossil fuels results in pervasive short- and long-term health consequences. We use insights from literature on the political economy of health and climate change, the science–policy interface and power in policy-making, to identify additional barriers to the meaningful incorporation of health co-benefits into climate change mitigation policy development. Specifically, we identify four key interrelated areas where barriers may exist in relation to health co-benefits: discourse, efficiency, vested interests and structural challenges. With these insights in mind, we argue that the current politico-economic paradigm in which climate change is situated and the processes used to develop climate change mitigation policies do not adequately support accounting for health co-benefits. We present approaches for enhancing the role of health co-benefits in the development of climate change mitigation policies to ensure that health is embedded in the broader climate change agenda. PMID:29617317

Toward a consistent modeling framework to assess multi-sectoral climate impacts.

PubMed

Monier, Erwan; Paltsev, Sergey; Sokolov, Andrei; Chen, Y-H Henry; Gao, Xiang; Ejaz, Qudsia; Couzo, Evan; Schlosser, C Adam; Dutkiewicz, Stephanie; Fant, Charles; Scott, Jeffery; Kicklighter, David; Morris, Jennifer; Jacoby, Henry; Prinn, Ronald; Haigh, Martin

2018-02-13

Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis-which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios-we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations.

Factors influencing smallholder farmers' behavioural intention towards adaptation to climate change in transitional climatic zones: A case study of Hwedza District in Zimbabwe.

PubMed

Zamasiya, Byron; Nyikahadzoi, Kefasi; Mukamuri, Billy Billiard

2017-08-01

This paper examines factors influencing behavioural change among smallholder farmers towards adaptation to climate change in transitional climatic zones of Africa, specifically, Hwedza District in Zimbabwe. Data for this study were collected from 400 randomly-selected smallholder farmers, using a structured questionnaire, focus group discussions and key informant interviews. The study used an ordered logit model to examine the factors that influence smallholder farmers' behavioural intention towards adaptation to climate change. Results from the study show that the gender of the household head, access to extension services on crop and livestock production, access to climate information, membership to social groups and experiencing a drought have a positive influence on farmers' attitude towards adaptation to climate change and variability. The study concluded that although the majority of smallholder farmers perceive that the climate is changing, they continue to habour negative attitudes towards prescribed climate change adaptation techniques. This study recommends more education on climate change, as well as adaptation strategies for both agricultural extension workers and farmers. This can be complemented by disseminating timely climate information through extension officers and farmers' groups. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate change impacts on terrestrial ecosystems in metropolitan Chicago and its surrounding, multi-state region

Treesearch

Jessica J. Hellmann; Knute J. Nadelhoffer; Louis R. Iverson; Lewis H. Ziska; Stephen N. Matthews; Philip Myers; Anantha M. Prasad; Matthew P. Peters

2010-01-01

This paper describes the potential impacts of warming temperatures and changing precipitation on plants, wildlife, invasive species, pests, and agricultural ecosystems across the multi-state region centered on Chicago, Illinois. We examine a geographic area that captures much of Lake Michigan, including a complex mosaic of urbanization and agriculture surrounding...

Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles

USDA-ARS?s Scientific Manuscript database

To improve climate change impact estimates, multi-model ensembles (MMEs) have been suggested. MMEs enable quantifying model uncertainty, and their medians are more accurate than that of any single model when compared with observations. However, multi-model ensembles are costly to execute, so model i...

Description of Changes in Climatic Indices in USA over 25 Years (1989 – 2013)

EPA Science Inventory

The spatial distribution of long-term changes in climatic factors and its relation with vegetation cover, human health, hydrology and many other ecosystem processes help to identify the consequences of climatic factors changes. In recent studies, the significant changes of select...

A Multidisciplinary Approach to Assessing the Causal Components of Climate Change

NASA Astrophysics Data System (ADS)

Gosnold, W. D.; Todhunter, P. E.; Dong, X.; Rundquist, B.; Majorowicz, J.; Blackwell, D. D.

2004-05-01

Separation of climate forcing by anthropogenic greenhouse gases from natural radiative climate forcing is difficult because the composite temperature signal in the meteorological and multi-proxy temperature records cannot be resolved directly into radiative forcing components. To address this problem, we have initiated a large-scale, multidisciplinary project to test coherence between ground surface temperatures (GST) reconstructed from borehole T-z profiles, surface air temperatures (SAT), soil temperatures, and solar radiation. Our hypothesis is that radiative heating and heat exchange between the ground and the air directly control the ground surface temperature. Consequently, borehole T-z measurements at multi-year intervals spanning time periods when solar radiation, soil and air temperatures have been recorded should enable comparison of the thermal energy stored in the ground to these quantities. If coherence between energy storage, solar radiation, GST, SAT and multi-proxy temperature data can be discerned for a one or two decade scale, synthesis of GST and multi-proxy data over the past several centuries may enable us to separately determine the anthropogenic and natural forcings of climate change. The data we are acquiring include: (1) New T-z measurements in boreholes previously used in paleoclimate and heat flow research in Canada and the United States from the 1970's to the present. (2) Meteorological data from the US Historical Climatology Network and the Automated Weather Data Network of the High Plains Regional Climate Center, and Environment Canada. (3) Direct and remotely sensed data on land use, environment, and soil properties at selected borehole and meteorological sites for the periods between borehole observations. The project addresses three related questions: What is the coherence between the GST, SAT, soil temperatures and solar radiation? Have microclimate changes at borehole sites and climate stations affected temperature trends? If good coherence is obtained, can the coherence between thermal energy stored in the ground and radiative forcing during the time between T-z measurements be extended several centuries into the past?

Plant communities on infertile soils are less sensitive to climate change.

PubMed

Harrison, Susan; Damschen, Ellen; Fernandez-Going, Barbara; Eskelinen, Anu; Copeland, Stella

2015-11-01

Much evidence suggests that plant communities on infertile soils are relatively insensitive to increased water deficit caused by increasing temperature and/or decreasing precipitation. However, a multi-decadal study of community change in the western USA does not support this conclusion. This paper tests explanations related to macroclimatic differences, overstorey effects on microclimate, variation in soil texture and plant functional traits. A re-analysis was undertaken of the changes in the multi-decadal study, which concerned forest understorey communities on infertile (serpentine) and fertile soils in an aridifying climate (southern Oregan) from 1949-1951 to 2007-2008. Macroclimatic variables, overstorey cover and soil texture were used as new covariates. As an alternative measure of climate-related change, the community mean value of specific leaf area was used, a functional trait measuring drought tolerance. We investigated whether these revised analyses supported the prediction of lesser sensitivity to climate change in understorey communities on infertile serpentine soils. Overstorey cover, but not macroclimate or soil texture, was a significant covariate of community change over time. It strongly buffered understorey temperatures, was correlated with less change and averaged >50 % lower on serpentine soils, thereby counteracting the lower climate sensitivity of understorey herbs on these soils. Community mean specific leaf area showed the predicted pattern of less change over time in serpentine than non-serpentine communities. Based on the current balance of evidence, plant communities on infertile serpentine soils are less sensitive to changes in the climatic water balance than communities on more fertile soils. However, this advantage may in some cases be lessened by their sparser overstorey cover. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multi-scalar influence of weather and climate on very large-fires in the Eastern United States

Treesearch

John T. Abatzoglou; Renaud Barbero; Crystal A. Kolden; Katherine C. Hegewisch; Narasimhan K. Larkin; Harry Podschwit

2014-01-01

A majority of area burned in the Eastern United States (EUS) results from a limited number of exceptionally large wildfires. Relationships between climatic conditions and the occurrence of very large-fires (VLF) in the EUS were examined using composite and climate-niche analyses that consider atmospheric factors across inter-annual, sub-seasonal and synoptic temporal...

Understanding the Reach of Agricultural Impacts from Climate Extremes in the Agricultural Model Intercomparison and Improvement Project (AgMIP)

NASA Astrophysics Data System (ADS)

Ruane, A. C.

2016-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to build a modeling framework capable of representing the complexities of agriculture, its dependence on climate, and the many elements of society that depend on food systems. AgMIP's 30+ activities explore the interconnected nature of climate, crop, livestock, economics, food security, and nutrition, using common protocols to systematically evaluate the components of agricultural assessment and allow multi-model, multi-scale, and multi-method analysis of intertwining changes in socioeconomic development, environmental change, and technological adaptation. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) with a particular focus on unforeseen consequences of development strategies, interactions between global and local systems, and the resilience of agricultural systems to extreme climate events. Climate extremes shock the agricultural system through local, direct impacts (e.g., droughts, heat waves, floods, severe storms) and also through teleconnections propagated through international trade. As the climate changes, the nature of climate extremes affecting agriculture is also likely to change, leading to shifting intensity, duration, frequency, and geographic extents of extremes. AgMIP researchers are developing new scenario methodologies to represent near-term extreme droughts in a probabilistic manner, field experiments that impose heat wave conditions on crops, increased resolution to differentiate sub-national drought impacts, new behavioral functions that mimic the response of market actors faced with production shortfalls, analysis of impacts from simultaneous failures of multiple breadbasket regions, and more detailed mapping of food and socioeconomic indicators into food security and nutrition metrics that describe the human impact in diverse populations. Agricultural models illustrate the challenges facing agriculture, allowing resilience planning even as precise prediction of extremes remains difficult. Increased research is necessary to understand hazards, vulnerability, and exposure of populations to characterize the risk of shocks and mechanisms by which unexpected losses drive land-use transitions.

Pleistocene climate change inferred from multi-proxy analyses of a loess-paleosol sequence in China

NASA Astrophysics Data System (ADS)

Wu, Yi; Qiu, Shifan; Fu, Shuqing; Rao, Zhiguo; Zhu, Zhaoyu

2018-04-01

The aeolian loess blanketing the Chinese Loess Plateau (CLP) is sensitive to climate change in monsoonal East Asia. Here, we present a multi-proxy climatic record from a Pleistocene loess-paleosol sequence from the Lantian Basin on the southern margin of the CLP. The measurements include magnetic susceptibility and related magnetic properties, bulk median grain-size, color reflectance, and the color-inferred hematite versus goethite ratio (Hm/Gt). A long-term aridification and cooling trend during the interval from ca 2.22-0.43 Ma is indicated by two magnetic grain-size proxies, corresponding to the global climatic cooling of the late Cenozoic. In addition, at least four intervals of climatic extremes are evident in the record of Hm/Gt ratio: at 1.71-1.65 Ma, 1.26-1.24 Ma, 0.94-0.86 Ma, and 0.62-0.48 Ma. These intervals are characterized by distinct regional climates, which contrast with the global climatic conditions represented in marine sediments. For example, a relatively arid climate is documented from 1.71 to 1.65 Ma, which was rapidly succeeded by a relatively humid climate which is associated with the earliest hominin (with an age of ca 1.63 Ma) in the Lantian Basin.

Spatially explicit integrated modeling and economic valuation of climate driven land use change and its indirect effects.

PubMed

Bateman, Ian; Agarwala, Matthew; Binner, Amy; Coombes, Emma; Day, Brett; Ferrini, Silvia; Fezzi, Carlo; Hutchins, Michael; Lovett, Andrew; Posen, Paulette

2016-10-01

We present an integrated model of the direct consequences of climate change on land use, and the indirect effects of induced land use change upon the natural environment. The model predicts climate-driven shifts in the profitability of alternative uses of agricultural land. Both the direct impact of climate change and the induced shift in land use patterns will cause secondary effects on the water environment, for which agriculture is the major source of diffuse pollution. We model the impact of changes in such pollution on riverine ecosystems showing that these will be spatially heterogeneous. Moreover, we consider further knock-on effects upon the recreational benefits derived from water environments, which we assess using revealed preference methods. This analysis permits a multi-layered examination of the economic consequences of climate change, assessing the sequence of impacts from climate change through farm gross margins, land use, water quality and recreation, both at the individual and catchment scale. Copyright © 2016 Elsevier Ltd. All rights reserved.

Climate Change

MedlinePlus

... in a place over a period of time. Climate change is major change in temperature, rainfall, snow, or ... by natural factors or by human activities. Today climate changes are occurring at an increasingly rapid rate. Climate ...

Engaging Students in Climate Change Science and Communication through a Multi-disciplinary Study Abroad Program

NASA Astrophysics Data System (ADS)

North, L. A.; Polk, J.; Strenecky, B.

2014-12-01

The implications of the climate change phenomenon are far-reaching, and will impact every person on Earth. These problems will be complex, and will require leaders well-versed in interdisciplinary learning and international understanding. To employ a multi-disciplinary approach to studying the impact climate change is having in the world in which we live, a team of 57 Western Kentucky University (WKU) faculty, staff, and students participated in a study abroad program to seven ports in the North Sea and North Atlantic, including three ports in Iceland, onboard the Semester at Sea ship, MV Explorer. This program combined interdisciplinary learning, service learning, and international understanding toward the goal of preparing the leaders of tomorrow with the skills to address climate change challenges. Together, the group learned how climate change affects the world from varied academic perspectives, and how more often than not these perspectives are closely interrelated. Courses taught during the experience related to climate change science and communication, economics, future trends, and K-12 education. Each student also participated in a The $100 Solution™ service-learning course. While in port, each class engaged in a discipline-specific activities related to the climate change topic, while at sea students participated in class lectures, engaged in shipboard lectures by international experts in their respective fields, and participated in conversations with lifelong learners onboard the ship. A culminating point of the study abroad experience was a presentation by the WKU students to over 100 persons from the University of Akureyri in Akureyri, Iceland, representatives of neighboring Icelandic communities, environmental agencies, and tourism bureaus about what they had learned about climate change during their travels. By forging this relationship, students were able to share their knowledge, which in turn gave them a deeper understanding of the issues they were learning throughout the voyage.

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

NASA Astrophysics Data System (ADS)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).

Communicating uncertainty in circulation aspects of climate change

NASA Astrophysics Data System (ADS)

Shepherd, Ted

2017-04-01

The usual way of representing uncertainty in climate change is to define a likelihood range of possible futures, conditioned on a particular pathway of greenhouse gas concentrations (RCPs). Typically these likelihood ranges are derived from multi-model ensembles. However, there is no obvious basis for treating such ensembles as probability distributions. Moreover, for aspects of climate related to atmospheric circulation, such an approach generally leads to large uncertainty and low confidence in projections. Yet this does not mean that the associated climate risks are small. We therefore need to develop suitable ways of communicating climate risk whilst acknowledging the uncertainties. This talk will outline an approach based on conditioning the purely thermodynamic aspects of climate change, concerning which there is comparatively high confidence, on circulation-related aspects, and treating the latter through non-probabilistic storylines.

Projected changes to precipitation extremes over the Canadian Prairies using multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2016-12-01

Information on projected changes to precipitation extremes is needed for future planning of urban drainage infrastructure and storm water management systems and to sustain socio-economic activities and ecosystems at local, regional and other scales of interest. This study explores the projected changes to seasonal (April-October) precipitation extremes at daily, hourly and sub-hourly scales over the Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba, based on the North American Regional Climate Change Assessment Program multi-Regional Climate Model (RCM) ensemble and regional frequency analysis. The performance of each RCM is evaluated regarding boundary and performance errors to study various sources of uncertainties and the impact of large-scale driving fields. In the absence of RCM-simulated short-duration extremes, a framework is developed to derive changes to extremes of these durations. Results from this research reveal that the relative changes in sub-hourly extremes are higher than those in the hourly and daily extremes. Overall, projected changes in precipitation extremes are larger for southeastern parts of this region than southern and northern areas, and smaller for southwestern and western parts of the study area. Keywords: climate change, precipitation extremes, regional frequency analysis, NARCCAP, Canadian Prairie provinces

Precipitation drives interannual variation in summer soil respiration in a Mediterranean-climate, mixed-conifer forest

Treesearch

M. Concilio; J. Chen; S. Ma; M. North

2009-01-01

Predictions of future climate change rely on models of how both environmental conditions and disturbance impact carbon cycling at various temporal and spatial scales. Few multi-year studies, however, have examined how carbon efflux is affected by the interaction of disturbance and interannual climate variation. We measured daytime soil respiration (R...