Climate, Water and Renewable Energy in the Nordic Countries
NASA Astrophysics Data System (ADS)
Snorrason, A.; Jonsdottir, J. F.
2004-05-01
Climate and Energy (CE) is a new Nordic research project with funding from Nordic Energy Research (NEFP) and the Nordic energy sector. The project has the objective of a comprehensive assessment of the impact of climate variability and change on Nordic renewable energy resources including hydropower, wind power, bio-fuels and solar energy. This will include assessment of the power production of the hydropower dominated Nordic energy system and its sensitivity and vulnerability to climate change on both temporal and spatial scales; assessment of the impacts of extremes including floods, droughts, storms, seasonal patterns and variability. Within the CE project several thematic groups work on specific issues of climatic change and their impacts on renewable energy. A primary aim of the CE climate group is to supply a standard set of common scenarios of climate change in northern Europe and Greenland, based on recent global and regional climate change experiments. The snow and ice group has chosen glaciers from Greenland, Iceland, Norway and Sweden for an analysis of the response of glaciers to climate changes. Mass balance and dynamical changes, corresponding to the common scenario for climate changes, will be modelled and effects on glacier hydrology will be estimated. Preliminary work with dynamic modelling and climate scenarios shows a dramatic response of glacial runoff to increased temperature and precipitation. The statistical analysis group has reported on the status of time series analysis in the Nordic countries. The group has selected and quality controlled time series of stream flow to be included in the Nordic component of the database FRIEND. Also the group will collect information on time series for other variables and these series will be systematically analysed with respect to trend and other long-term changes. Preliminary work using multivariate analysis on stream flow and climate variables shows strong linkages with the long term atmospheric circulation in the North Atlantic. The hydrological modelling group has already reported on "Climate change impacts on water resources in the Nordic countries - State of the art and discussion of principles". The group will compare different approaches of transferring the climate change signal into hydrological models and discuss uncertainties in models and climate scenarios. Furthermore, comprehensive assessment and mapping of impact of climate change will be produced for the whole Nordic region based on the scenarios from the CE-climate group.
Güizado-Rodríguez, Martha Anahí; Ballesteros-Barrera, Claudia; Casas-Andreu, Gustavo; Barradas-Miranda, Victor Luis; Téllez-Valdés, Oswaldo; Salgado-Ugarte, Isaías Hazarmabeth
2012-12-01
The ectothermic nature of reptiles makes them especially sensitive to global warming. Although climate change and its implications are a frequent topic of detailed studies, most of these studies are carried out without making a distinction between populations. Here we present the first study of an Aspidoscelis species that evaluates the effects of global warming on its distribution using ecological niche modeling. The aims of our study were (1) to understand whether predicted warmer climatic conditions affect the geographic potential distribution of different climatic groups of Aspidoscelis costata costata and (2) to identify potential altitudinal changes of these groups under global warming. We used the maximum entropy species distribution model (MaxEnt) to project the potential distributions expected for the years 2020, 2050, and 2080 under a single simulated climatic scenario. Our analysis suggests that some climatic groups of Aspidoscelis costata costata will exhibit reductions and in others expansions in their distribution, with potential upward shifts toward higher elevation in response to climate warming. Different climatic groups were revealed in our analysis that subsequently showed heterogeneous responses to climatic change illustrating the complex nature of species geographic responses to environmental change and the importance of modeling climatic or geographic groups and/or populations instead of the entire species' range treated as a homogeneous entity.
PRISM Climate Group, Oregon State U
FAQ PRISM Climate Data The PRISM Climate Group gathers climate observations from a wide range of monitoring networks, applies sophisticated quality control measures, and develops spatial climate datasets to reveal short- and long-term climate patterns. The resulting datasets incorporate a variety of modeling
Wang, J C; Liu, W C; Chatzisarantis, N L; Lim, C B
2010-06-01
The purpose of the current study was to examine the influence of perceived motivational climate on achievement goals in physical education using a structural equation mixture modeling (SEMM) analysis. Within one analysis, we identified groups of students with homogenous profiles in perceptions of motivational climate and examined the relationships between motivational climate, 2 x 2 achievement goals, and affect, concurrently. The findings of the current study showed that there were at least two distinct groups of students with differing perceptions of motivational climate: one group of students had much higher perceptions in both climates compared with the other group. Regardless of their grouping, the relationships between motivational climate, achievement goals, and enjoyment seemed to be invariant. Mastery climate predicted the adoption of mastery-approach and mastery-avoidance goals; performance climate was related to performance-approach and performance-avoidance goals. Mastery-approach goal had a strong positive effect while performance-avoidance had a small negative effect on enjoyment. Overall, it was concluded that only perception of a mastery motivational climate in physical education may foster intrinsic interest in physical education through adoption of mastery-approach goals.
Climate, Water and Energy in the Nordic Countries
NASA Astrophysics Data System (ADS)
Snorrason, A.; Jonsdottir, J. F.
2003-04-01
In light of the recent IPCC Climate Change Assessment and recent progress made in meteorological and hydrological modelling, the directors of the Nordic hydrological institutes (CHIN) initiated a research project "Climate, Water and Energy" (CWE) with funding from the Nordic Energy Research and the Nordic Council of Ministers focusing on climatic impact assessment in the energy sector. Climatic variability and change affect the hydrological systems, which in turn affect the energy sector, this will increase the risk associated with the development and use of water resources in the Nordic countries. Within the CWE project four thematic groups work on this issue of climatic change and how changes in precipitation and temperature will have direct influences on runoff. A primary aim of the CWE climate group is to derive a common scenario or a "best-guess" estimate of climate change in northern Europe and Greenland, based on recent regional climate change experiments and representing the change from 1990 to 2050 under the IPCC SRES B2 emission scenario. A data set, along with the most important information for using the scenario is available at the project web site. The glacier group has chosen 8 glaciers from Greenland, Iceland, Norway and Sweden for an analysis of the response of glaciers to climate changes. Mass balance and dynamical changes, corresponding to the common scenario for climate changes, will be modelled and effects on glacier hydrology will be estimated. The long time series group has reported on the status of time series analysis in the Nordic countries. The group will select and quality control time series of stream flow to be included in the Nordic component of the database FRIEND. Also the group will collect information on time series for other variables and these series will be systematically analysed with respect to trend and other long-term changes. The hydrological modelling group has reported on "Climate change impacts on water resources in the Nordic countries - State of the art and discussion of principles". The group will compare different hydrological models and discuss uncertainties in models and climate scenarios, while production of new results based on the composite scenario from the CWE-climate group depends on other projects. The product of the project will be an in-depth analysis of the present status of research and know-how in the sphere of climatic and hydrological research in the Nordic countries. It will be a synthesis and integration of present research with focus on the needs of the energy sector. It will also identify and prioritise key future research areas that are of benefit to the energy sector.
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) ...
Transformational leadership and group interaction as climate antecedents: a social network analysis.
Zohar, Dov; Tenne-Gazit, Orly
2008-07-01
In order to test the social mechanisms through which organizational climate emerges, this article introduces a model that combines transformational leadership and social interaction as antecedents of climate strength (i.e., the degree of within-unit agreement about climate perceptions). Despite their longstanding status as primary variables, both antecedents have received limited empirical research. The sample consisted of 45 platoons of infantry soldiers from 5 different brigades, using safety climate as the exemplar. Results indicate a partially mediated model between transformational leadership and climate strength, with density of group communication network as the mediating variable. In addition, the results showed independent effects for group centralization of the communication and friendship networks, which exerted incremental effects on climate strength over transformational leadership. Whereas centralization of the communication network was found to be negatively related to climate strength, centralization of the friendship network was positively related to it. Theoretical and practical implications are discussed.
Visual Reconciliation of Alternative Similarity Spaces in Climate Modeling.
Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher R; Huntzinger, Deborah N; Cook, Robert; Bertini, Enrico; Silva, Claudio T
2014-12-01
Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses additional challenges. In this paper we define visual reconciliation as the problem of reconciling multiple alternative similarity spaces through visualization and interaction. We derive this problem from our work on model comparison in climate science where climate modelers are faced with the challenge of making sense of alternative ways to describe their models: one through the output they generate, another through the large set of properties that describe them. Ideally, they want to understand whether groups of models with similar spatio-temporal behaviors share similar sets of criteria or, conversely, whether similar criteria lead to similar behaviors. We propose a visual analytics solution based on linked views, that addresses this problem by allowing the user to dynamically create, modify and observe the interaction among groupings, thereby making the potential explanations apparent. We present case studies that demonstrate the usefulness of our technique in the area of climate science.
The Nested Regional Climate Model: An Approach Toward Prediction Across Scales
NASA Astrophysics Data System (ADS)
Hurrell, J. W.; Holland, G. J.; Large, W. G.
2008-12-01
The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.
Multilevel model of safety climate for furniture industries.
Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P
2015-01-01
Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.
Documenting Climate Models and Simulations: the ES-DOC Ecosystem in Support of CMIP
NASA Astrophysics Data System (ADS)
Pascoe, C. L.; Guilyardi, E.
2017-12-01
The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now non-specialists such as government officials, policy-makers, and the general public, all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. Here we describe the ES-DOC community-govern project to collect and make available documentation of climate models and their simulations for the internationally coordinated modeling activity CMIP6 (Coupled Model Intercomparison Project, Phase 6). An overview of the underlying standards, key properties and features, the evolution from CMIP5, the underlying tools and workflows as well as what modelling groups should expect and how they should engage with the documentation of their contribution to CMIP6 is also presented.
The Community Earth System Model-Polar Climate Working Group and the status of CESM2.
NASA Astrophysics Data System (ADS)
Bailey, D. A.; Holland, M. M.; DuVivier, A. K.
2017-12-01
The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.
The agricultural model intercomparison and improvement project (AgMIP): Protocols and pilot studies
USDA-ARS?s Scientific Manuscript database
The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a distributed climate-scenario simulation research activity for historical period model intercomparison and future climate change conditions with participation of multiple crop and agricultural economic model groups around the...
The role of organizational trust in safety climate's influence on organizational outcomes.
Kath, Lisa M; Magley, Vicki J; Marmet, Matthew
2010-09-01
Based on elements of social exchange theory and other conceptualizations of trust, a model was developed situating organizational trust as a central component to the relationship that safety climate has with organizational outcomes. Specifically, the model specified that two facets of safety climate--upward safety communication and management attitudes toward safety--would be positively related to organizational trust. Increased levels of trust would then predict increased motivation to engage in safe job-related behaviors, increased job satisfaction, and decreased turnover intentions. Another hypothesis investigated whether job safety relevance would moderate the relationship between safety climate and trust. Online survey research was conducted with 599 employees from 97 work groups across a New England grocery store chain. Hierarchical linear modeling indicated support for trust mediating the relationship between safety climate and organizational outcomes; further, the relationship between safety climate and trust was stronger within work groups where safety was more relevant. 2009 Elsevier Ltd. All rights reserved.
Identifying organizational cultures that promote patient safety.
Singer, Sara J; Falwell, Alyson; Gaba, David M; Meterko, Mark; Rosen, Amy; Hartmann, Christine W; Baker, Laurence
2009-01-01
Safety climate refers to shared perceptions of what an organization is like with regard to safety, whereas safety culture refers to employees' fundamental ideology and orientation and explains why safety is pursued in the manner exhibited within a particular organization. Although research has sought to identify opportunities for improving safety outcomes by studying patterns of variation in safety climate, few empirical studies have examined the impact of organizational characteristics such as culture on hospital safety climate. This study explored how aspects of general organizational culture relate to hospital patient safety climate. In a stratified sample of 92 U.S. hospitals, we sampled 100% of senior managers and physicians and 10% of other hospital workers. The Patient Safety Climate in Healthcare Organizations and the Zammuto and Krakower organizational culture surveys measured safety climate and group, entrepreneurial, hierarchical, and production orientation of hospitals' culture, respectively. We administered safety climate surveys to 18,361 personnel and organizational culture surveys to a 5,894 random subsample between March 2004 and May 2005. Secondary data came from the 2004 American Hospital Association Annual Hospital Survey and Dun & Bradstreet. Hierarchical linear regressions assessed relationships between organizational culture and safety climate measures. Aspects of general organizational culture were strongly related to safety climate. A higher level of group culture correlated with a higher level of safety climate, but more hierarchical culture was associated with lower safety climate. Aspects of organizational culture accounted for more than threefold improvement in measures of model fit compared with models with controls alone. A mix of culture types, emphasizing group culture, seemed optimal for safety climate. Safety climate and organizational culture are positively related. Results support strategies that promote group orientation and reduced hierarchy, including use of multidisciplinary team training, continuous quality improvement tools, and human resource practices and policies.
Clustering of Global Climate Models outputs as a tool for scenario-based risk assessment
NASA Astrophysics Data System (ADS)
R Pereira, V.; Zullo, J., Jr.; Avila, A. M. H. D.
2016-12-01
The choice of the Global Climate Models (GCMs) future projections outputs for the scenario based risk assessment studies is a challenge for the non-climate models scientists. This study presents a method to select a range of the GCMs scenarios for regional/continental agriculture studies. The technique proposed here is based on grouping the surface air temperature (tas) anomalies in a continental /regional scale - in Brazil-South America - projected by the AR5-CMIP5-GCMs. We run the k-means cluster algorithm and the silhouette method to identify the optimal number and to group the GCMs tas outputs under the rcp 8.5. We applied the delta method to calculate the near future climate change. This method is based on the difference between the future and the baseline in a 30 year running mean periods basis. The future considered here is the 2021-2050 [2030s] and the baseline is the period of 1976-2005 (1980s). As expected, all the models projections showed increases in tas in the near future, ranging from ≅ 3.6 to 0.2 oC. The k-means clustering clearly indicates 5 groups of GCMs tas deltas. The majority of GCMs indicated an intermediate future temperature changes. There is a group of 12 GCMs that is indicating an average change of ≅ 2 oC and another group of 16 indicating ≅ 1 oC. The other two groups with 3 GCMs each indicated a most extreme tas scenario - 0.2 and 3.6 oC respectively. The results were in agreement with previous studies with the AR4 GCMs in which the Miroc5 and HADGEM ES predecessors were classified in different groups of models. The results also allowed us to gradually access the optimist - pessimist groups of 34 GCMs that is a good reference to guide the public policy demands for agriculture under climate change conditions.
Cluster analysis of Southeastern U.S. climate stations
NASA Astrophysics Data System (ADS)
Stooksbury, D. E.; Michaels, P. J.
1991-09-01
A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.
Lin, Shang-Ping; Tang, Ta-Wei; Li, Chao-Hua; Wu, Chien-Ming; Lin, Hsiu-Hsia
2007-08-01
Although the relationships between procedural justice climate and organizational citizenship behaviors have been examined in recent years, little research has explored the mechanism by which procedural justice climate shapes individual employee prosocial behaviors in the workplace. The purpose of this study was to examine the mediating role of a group-level cooperative norm on the relationships between the group-level procedural justice climate and individual-level organizational citizenship behaviors. The survey involved 45 work groups in four different industry fields in Taiwan, including manufacturing, technology, banking, and insurance, and each of the groups was composed of one supervisor and three subordinates. Cross-level analyses using hierarchical linear modeling (HLM) indicated that the cooperative norm fully mediated the relationship between procedural justice climate and individual helping behaviors. Procedural justice climate indirectly affects individual helping behaviors through their effects on the cooperative norm.
NASA Astrophysics Data System (ADS)
Keener, V. W.; Brewington, L.; Jaspers, K.
2016-12-01
To build an effective bridge from the climate modeling community to natural resource managers, we assessed the existing landscape to see where different groups diverge in their perceptions of climate data and needs. An understanding of a given community's shared knowledge and differences can help design more actionable science. Resource managers in Hawaii are eager to have future climate projections at spatial scales relevant to the islands. National initiatives to downscale climate data often exclude US insular regions, so researchers in Hawaii have generated regional dynamically and statistically downscaled projections. Projections of precipitation diverge, however, leading to difficulties in communication and use. Recently, a two day workshop was held with scientists and managers to evaluate available models and determine a set of best practices for moving forward with decision-relevant downscaling in Hawaii. To seed the discussion, the Pacific Regional Integrated Sciences and Assessments (RISA) program conducted a pre-workshop survey (N=65) of climate modelers and freshwater, ecosystem, and wildfire managers working in Hawaii. Scientists reported spending less than half of their time on operational research, although the majority was eager to partner with managers on specific projects. Resource managers had varying levels of familiarity with downscaled climate projections, but reported needing more information about uncertainty for decision making, and were less interested in the technical model details. There were large differences between groups of managers, with 41.7% of freshwater managers reporting that they used climate projections regularly, while a majority of ecosystem and wildfire managers reported having "no familiarity". Scientists and managers rated which spatial and temporal scales were most relevant to decision making. Finally, when asked to compare how confident they were in projections of specific climate variables between the dynamical and statistical data, 80-90% of managers responded that they had no opinion. Workshop attendees were very interested in the survey results, adding to evidence of a need for sustained engagement between modeler and user groups, as well as different strategies for working with different types of resource managers.
NASA Technical Reports Server (NTRS)
Ding, Feng; Fang, Fan; Hearty, Thomas J.; Theobald, Michael; Vollmer, Bruce; Lynnes, Christopher
2014-01-01
The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.
The predictive validity of safety climate.
Johnson, Stephen E
2007-01-01
Safety professionals have increasingly turned their attention to social science for insight into the causation of industrial accidents. One social construct, safety climate, has been examined by several researchers [Cooper, M. D., & Phillips, R. A. (2004). Exploratory analysis of the safety climate and safety behavior relationship. Journal of Safety Research, 35(5), 497-512; Gillen, M., Baltz, D., Gassel, M., Kirsch, L., & Vacarro, D. (2002). Perceived safety climate, job Demands, and coworker support among union and nonunion injured construction workers. Journal of Safety Research, 33(1), 33-51; Neal, A., & Griffin, M. A. (2002). Safety climate and safety behaviour. Australian Journal of Management, 27, 66-76; Zohar, D. (2000). A group-level model of safety climate: Testing the effect of group climate on microaccidents in manufacturing jobs. Journal of Applied Psychology, 85(4), 587-596; Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628] who have documented its importance as a factor explaining the variation of safety-related outcomes (e.g., behavior, accidents). Researchers have developed instruments for measuring safety climate and have established some degree of psychometric reliability and validity. The problem, however, is that predictive validity has not been firmly established, which reduces the credibility of safety climate as a meaningful social construct. The research described in this article addresses this problem and provides additional support for safety climate as a viable construct and as a predictive indicator of safety-related outcomes. This study used 292 employees at three locations of a heavy manufacturing organization to complete the 16 item Zohar Safety Climate Questionnaire (ZSCQ) [Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628]. In addition, safety behavior and accident experience data were collected for 5 months following the survey and were statistically analyzed (structural equation modeling, confirmatory factor analysis, exploratory factor analysis, etc.) to identify correlations, associations, internal consistency, and factorial structures. Results revealed that the ZSCQ: (a) was psychometrically reliable and valid, (b) served as an effective predictor of safety-related outcomes (behavior and accident experience), and (c) could be trimmed to an 11 item survey with little loss of explanatory power. Practitioners and researchers can use the ZSCQ with reasonable certainty of the questionnaire's reliability and validity. This provides a solid foundation for the development of meaningful organizational interventions and/or continued research into social factors affecting industrial accident experience.
Bortoli, Laura; Bertollo, Maurizio; Vitali, Francesca; Filho, Edson; Robazza, Claudio
2015-06-01
The purpose of this study was to examine the effects of task- and ego-involving climate manipulations on students' climate perception and psychobiosocial (PBS) states in a physical education setting. Two subsamples of female students (N = 108, 14-15 years of age) participated in 12 lessons on either a task- or an ego-involving climate intervention as grounded in the TARGET (tasks, authority, recognition, grouping, evaluation, and time) model. At the end of the treatment, the participants of the ego-involved group reported lower scores in the perceived task-involving climate and higher scores in the perceived ego-involving climate compared with their peers in the task-involved group. Lower scores in pleasant/functional PBS states and higher scores in unpleasant/dysfunctional PBS states were also observed in the ego-involved group as a consequence of the intervention. Findings suggested that teachers' induced achievement motivational climates can influence students' perceptions and prompt PBS states consistent with the motivational atmosphere.
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.
Intercomparison of four regional climate models for the German State of Saxonia
NASA Astrophysics Data System (ADS)
Kreienkamp, F.; Spekat, A.; Enke, W.
2009-09-01
Results from four regional climate models which focus on Central Europe are presented: CCLM, the climate version of the German Weather Service's Local Model - REMO, the regional dynamic model from the Max Planck Institute for Meteorology in Hamburg - STAR, the statistical model developed at the PIK Potsdam Institute and WETTREG, the statistic-dynamic model developed by the company CEC Potsdam. For the area of the German State of Saxonia a host of properties and indicators were analyzed aiming to show the models' abilities to reconstruct the current climate and compare climate model scenarios. These include a group of thermal indicators, such as the number of ice, frost, summer and hot days, the number of tropical nights; then there are hydrometeorological indicators such as the exceedance of low and high precipitation thresholds; humidity, cloudiness and wind indicators complement the array. A selection of them showing similarities and differences of the models investigated will be presented.
NASA Astrophysics Data System (ADS)
White, D.; Trainor, S.; Walsh, J.; Gerlach, C.
2008-12-01
The Alaska Center for Climate Assessment and Policy (ACCAP; www.uaf.edu/accap) is one of several, NOAA funded, Regional Integrated Science and Policy (RISA) programs nation-wide (http://www.climate.noaa.gov/cpo_pa/risa/). Our mission is to assess the socio-economic and biophysical impacts of climate variability in Alaska, make this information available to local and regional decision-makers, and improve the ability of Alaskans to adapt to a changing climate. We partner with the University of Alaska?s Scenario Network for Alaska Planning (SNAP; http://www.snap.uaf.edu/), state and local government, state and federal agencies, industry, and non-profit organizations to communicate accurate and up-to-date climate science and assist in formulating adaptation and mitigation plans. ACCAP and SNAP scientists are members of the Governor?s Climate Change Sub-Cabinet Adaptation and Mitigation Advisory and Technical Working Groups (http://www.climatechange.alaska.gov/), and apply their scientific expertise to provide down-scaled, state-wide maps of temperature and precipitation projections for these groups. An ACCAP scientist also serves as co-chair for the Fairbanks North Star Borough Climate Change Task Force, assisting this group as they work through the five-step model for climate change planning put forward by the International Council for Local Environmental Initiatives (http://www.investfairbanks.com/Taskforces/climate.php). ACCAP scientists work closely with federal resource managers in on a range of projects including: partnering with the U.S. Fish and Wildlife Service to analyze hydrologic changes associated with climate change and related ecological impacts and wildlife management and development issues on Alaska?s North Slope; partnering with members of the Alaska Interagency Wildland Fire Coordinating Group in statistical modeling to predict seasonal wildfire activity and coordinate fire suppression resources state-wide; and working with Alaska Native Elders and resource managers to document traditional ecological knowledge (TEK) and integrate this knowledge with Western science for crafting adaptation response to climate impacts in rural Native Alaska.
Brown, Theresa C; Fry, Mary D
2014-06-01
The purpose of this study was to examine the association between members' perceptions of staffs behaviors, motivational climate, their own behaviors, commitment to future exercise, and life satisfaction in a group-fitness setting. The theory-driven hypothesized mediating role of perceptions of the climate was also tested. Members (N = 5,541) of a national group-fitness studio franchise completed a survey regarding their class experiences. The survey included questions that measured participants' perceptions of the motivational climate (caring, task-involving, ego-involving), perceptions of staff's behaviors, their own behaviors, commitment to exercise, and life satisfaction. Structural equation modeling was used to assess both the association between variables and the theoretically driven predictive relationships. The participants perceived the environment as highly caring and task-involving and low ego-involving. They reported high exercise commitment and moderately high life satisfaction and perceived that the staffs and their own behaviors reflected caring, task-involving characteristics. Structural equation modeling demonstrated that those who perceived a higher caring, task-involving climate and lower ego-involving climate were more likely to report more task-involving, caring behaviors among the staff and themselves as well as greater commitment to exercise. In addition, a theory-driven mediational model suggested that staff behaviors may be an antecedent to members' exercise experiences by impacting their perceptions of the climate. The results of this study give direction to specific behaviors in which staff of group-fitness programs might engage to positively influence members' exercise experiences.
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Redesigning mental healthcare delivery: is there an effect on organizational climate?
Joosten, T C M; Bongers, I M B; Janssen, R T J M
2014-02-01
Many studies have investigated the effect of redesign on operational performance; fewer studies have evaluated the effects on employees' perceptions of their working environment (organizational climate). Some authors state that redesign will lead to poorer organizational climate, while others state the opposite. The goal of this study was to empirically investigate this relation. Organizational climate was measured in a field experiment, before and after a redesign intervention. At one of the sites, a redesign project was conducted. At the other site, no redesign efforts took place. Two Dutch child- and adolescent-mental healthcare providers. Professionals that worked at one of the units at the start and/or the end of the intervention period. The main intervention was a redesign project aimed at improving timely delivery of services (modeled after the breakthrough series). Scores on the four models of the organizational climate measure, a validated questionnaire that measures organizational climate. Our analysis showed that climate at the intervention site changed on factors related to productivity and goal achievement (rational goal model). The intervention group scored worse than the comparison group on the part of the questionnaire that focuses on sociotechnical elements of organizational climate. However, observed differences were so small, that their practical relevance seems rather limited. Redesign efforts in healthcare, so it seems, do not influence organizational climate as much as expected.
ERIC Educational Resources Information Center
Bush, Drew; Sieber, Renee; Seiler, Gale; Chandler, Mark
2018-01-01
This study with 79 students in Montreal, Quebec, compared the educational use of a National Aeronautics and Space Administration (NASA) global climate model (GCM) to climate education technologies developed for classroom use that included simpler interfaces and processes. The goal was to show how differing climate education technologies succeed…
Climate change vulnerability assessment of forests in the Southwest USA
James H. Thorne; Hyeyeong Choe; Peter A. Stine; Jeanne C. Chambers; Andrew Holguin; Amber C. Kerr; Mark W. Schwartz
2017-01-01
Climate change effects are already apparent in some Southwestern US forests and are expected to intensify in the coming decades, via direct (temperature, precipitation) and indirect (fire, pests, pathogens) stressors. We grouped Southwestern forests into ten major types to assess their climate exposure by 2070 using two global climate models (GCMs) and two emission...
Climate change effects on international stability : a white paper.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Murphy, Kathryn; Taylor, Mark A.; Fujii, Joy
2004-12-01
This white paper represents a summary of work intended to lay the foundation for development of a climatological/agent model of climate-induced conflict. The paper combines several loosely-coupled efforts and is the final report for a four-month late-start Laboratory Directed Research and Development (LDRD) project funded by the Advanced Concepts Group (ACG). The project involved contributions by many participants having diverse areas of expertise, with the common goal of learning how to tie together the physical and human causes and consequences of climate change. We performed a review of relevant literature on conflict arising from environmental scarcity. Rather than simply reviewingmore » the previous work, we actively collected data from the referenced sources, reproduced some of the work, and explored alternative models. We used the unfolding crisis in Darfur (western Sudan) as a case study of conflict related to or triggered by climate change, and as an exercise for developing a preliminary concept map. We also outlined a plan for implementing agents in a climate model and defined a logical progression toward the ultimate goal of running both types of models simultaneously in a two-way feedback mode, where the behavior of agents influences the climate and climate change affects the agents. Finally, we offer some ''lessons learned'' in attempting to keep a diverse and geographically dispersed group working together by using Web-based collaborative tools.« less
Functional Group, Biomass, and Climate Change Effects on Ecological Drought in Semiarid Grasslands
NASA Astrophysics Data System (ADS)
Wilson, S. D.; Schlaepfer, D. R.; Bradford, J. B.; Lauenroth, W. K.; Duniway, M. C.; Hall, S. A.; Jamiyansharav, K.; Jia, G.; Lkhagva, A.; Munson, S. M.; Pyke, D. A.; Tietjen, B.
2018-03-01
Water relations in plant communities are influenced both by contrasting functional groups (grasses and shrubs) and by climate change via complex effects on interception, uptake, and transpiration. We modeled the effects of functional group replacement and biomass increase, both of which can be outcomes of invasion and vegetation management, and climate change on ecological drought (soil water potential below which photosynthesis stops) in 340 semiarid grassland sites over 30 year periods. Relative to control vegetation (climate and site-determined mixes of functional groups), the frequency and duration of drought were increased by shrubs and decreased by annual grasses. The rankings of shrubs, control vegetation, and annual grasses in terms of drought effects were generally consistent in current and future climates, suggesting that current differences among functional groups on drought effects predict future differences. Climate change accompanied by experimentally increased biomass (i.e., the effects of invasions that increase community biomass or management that increases productivity through fertilization or respite from grazing) increased drought frequency and duration and advanced drought onset. Our results suggest that the replacement of perennial temperate semiarid grasslands by shrubs, or increased biomass, can increase ecological drought in both current and future climates.
Functional group, biomass, and climate change effects on ecological drought in semiarid grasslands
Wilson, Scott D.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, William K.; Duniway, Michael C.; Hall, Sonia A.; Jamiyansharav, Khishigbayar; Jia, Gensuo; Lkhagva, Ariuntsetseg; Munson, Seth M.; Pyke, David A.; Tietjen, Britta
2018-01-01
Water relations in plant communities are influenced both by contrasting functional groups (grasses, shrubs) and by climate change via complex effects on interception, uptake and transpiration. We modelled the effects of functional group replacement and biomass increase, both of which can be outcomes of invasion and vegetation management, and climate change on ecological drought (soil water potential below which photosynthesis stops) in 340 semiarid grassland sites over 30‐year periods. Relative to control vegetation (climate and site‐determined mixes of functional groups), the frequency and duration of drought were increased by shrubs and decreased by annual grasses. The rankings of shrubs, control vegetation, and annual grasses in terms of drought effects were generally consistent in current and future climates, suggesting that current differences among functional groups on drought effects predict future differences. Climate change accompanied by experimentally‐increased biomass (i.e. the effects of invasions that increase community biomass, or management that increases productivity through fertilization or respite from grazing) increased drought frequency and duration, and advanced drought onset. Our results suggest that the replacement of perennial temperate semiarid grasslands by shrubs, or increased biomass, can increase ecological drought both in current and future climates.
Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola
2015-11-15
Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on river ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Huxster, Joanna K.; Uribe-Zarain, Ximena; Kempton, Willett
2015-01-01
A survey covering the scientific and social aspects of climate change was administered to examine U.S. undergraduate student mental models, and compare knowledge between groups based on major and environmental group membership. A Knowledge Score (scale 0-35, mean score = 17.84) was generated for respondents at two, central East Coast, U.S.…
Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.
McMahon, Sean M; Harrison, Sandy P; Armbruster, W Scott; Bartlein, Patrick J; Beale, Colin M; Edwards, Mary E; Kattge, Jens; Midgley, Guy; Morin, Xavier; Prentice, I Colin
2011-05-01
Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models. Published by Elsevier Ltd.
Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.
While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less
Hurricanes and Climate: The U.S. CLIVAR Working Group on Hurricanes
Walsh, Kevin J. E.; Camargo, Suzana J.; Vecchi, Gabriel A.; ...
2015-06-01
While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and to understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. Climate and Ocean: Variability, Predictability and Change (CLIVAR). This work, combined with results frommore » other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as midtropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased compared with experiments where only atmospheric carbon dioxide is increased. Experiments where only carbon dioxide is increased are more likely to demonstrate a decrease in tropical cyclone numbers, similar to the decreases simulated by many climate models for a future, warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Lastly, further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.« less
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.
Assessing Climate Change Risks Using a Multi-Model Approach
NASA Astrophysics Data System (ADS)
Knorr, W.; Scholze, M.; Prentice, C.
2007-12-01
We quantify the risks of climate-induced changes in key ecosystem processes during the 21st century by forcing a dynamic global vegetation model with multiple scenarios from the IPCC AR4 data archive using 16 climate models and mapping the proportions of model runs showing exceedance of natural variability in wildfire frequency and freshwater supply or shifts in vegetation cover. Our analysis does not assign probabilities to scenarios. Instead, we consider the distribution of outcomes within three sets of model runs grouped according to the amount of global warming they simulate: < 2 degree C (including committed climate change simulations), 2-3 degree C, and >3 degree C. Here, we are contrasting two different methods for calculating the risks: first we use an equal weighting approach giving every model within one of the three sets the same weight, and second, we weight the models according to their ability to model ENSO. The differences are underpinning the need for the development of more robust performance metrics for global climate models.
Identifying bird and reptile vulnerabilities to climate change in the southwestern United States
Hatten, James R.; Giermakowski, J. Tomasz; Holmes, Jennifer A.; Nowak, Erika M.; Johnson, Matthew J.; Ironside, Kirsten E.; van Riper, Charles; Peters, Michael; Truettner, Charles; Cole, Kenneth L.
2016-07-06
Current and future breeding ranges of 15 bird and 16 reptile species were modeled in the Southwestern United States. Rather than taking a broad-scale, vulnerability-assessment approach, we created a species distribution model (SDM) for each focal species incorporating climatic, landscape, and plant variables. Baseline climate (1940–2009) was characterized with Parameter-elevation Regressions on Independent Slopes Model (PRISM) data and future climate with global-circulation-model data under an A1B emission scenario. Climatic variables included monthly and seasonal temperature and precipitation; landscape variables included terrain ruggedness, soil type, and insolation; and plant variables included trees and shrubs commonly associated with a focal species. Not all species-distribution models contained a plant, but if they did, we included a built-in annual migration rate for more accurate plant-range projections in 2039 or 2099. We conducted a group meta-analysis to (1) determine how influential each variable class was when averaged across all species distribution models (birds or reptiles), and (2) identify the correlation among contemporary (2009) habitat fragmentation and biological attributes and future range projections (2039 or 2099). Projected changes in bird and reptile ranges varied widely among species, with one-third of the ranges predicted to expand and two-thirds predicted to contract. A group meta-analysis indicated that climatic variables were the most influential variable class when averaged across all models for both groups, followed by landscape and plant variables (birds), or plant and landscape variables (reptiles), respectively. The second part of the meta-analysis indicated that numerous contemporary habitat-fragmentation (for example, patch isolation) and biological-attribute (for example, clutch size, longevity) variables were significantly correlated with the magnitude of projected range changes for birds and reptiles. Patch isolation was a significant trans-specific driver of projected bird and reptile ranges, suggesting that strategic actions should focus on restoration and enhancement of habitat at local and regional scales to promote landscape connectivity and conservation of core areas.
Practice and philosophy of climate model tuning across six US modeling centers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schmidt, Gavin A.; Bader, David; Donner, Leo J.
Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less
Practice and philosophy of climate model tuning across six US modeling centers
NASA Astrophysics Data System (ADS)
Schmidt, Gavin A.; Bader, David; Donner, Leo J.; Elsaesser, Gregory S.; Golaz, Jean-Christophe; Hannay, Cecile; Molod, Andrea; Neale, Richard B.; Saha, Suranjana
2017-09-01
Model calibration (or tuning
) is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.
Practice and philosophy of climate model tuning across six US modeling centers
Schmidt, Gavin A.; Bader, David; Donner, Leo J.; ...
2017-09-01
Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less
Drivers of Variability in Public-Supply Water Use Across the Contiguous United States
NASA Astrophysics Data System (ADS)
Worland, Scott C.; Steinschneider, Scott; Hornberger, George M.
2018-03-01
This study explores the relationship between municipal water use and an array of climate, economic, behavioral, and policy variables across the contiguous U.S. The relationship is explored using Bayesian-hierarchical regression models for over 2,500 counties, 18 covariates, and three higher-level grouping variables. Additionally, a second analysis is included for 83 cities where water price and water conservation policy information is available. A hierarchical model using the nine climate regions (product of National Oceanic and Atmospheric Administration) as the higher-level groups results in the best out-of-sample performance, as estimated by the Widely Available Information Criterion, compared to counties grouped by urban continuum classification or primary economic activity. The regression coefficients indicate that the controls on water use are not uniform across the nation: e.g., counties in the Northeast and Northwest climate regions are more sensitive to social variables, whereas counties in the Southwest and East North Central climate regions are more sensitive to environmental variables. For the national city-level model, it appears that arid cities with a high cost of living and relatively low water bills sell more water per customer, but as with the county-level model, the effect of each variable depends heavily on where a city is located.
Safety climate and the theory of planned behavior: towards the prediction of unsafe behavior.
Fogarty, Gerard J; Shaw, Andrew
2010-09-01
The present study is concerned with the human factors that contribute to violations in aviation maintenance. Much of our previous research in this area has been based on safety climate surveys and the analysis of relations among core dimensions of climate. In this study, we tap into mainstream psychological theory to help clarify the mechanisms underlying the links between climate and behavior. Specifically, we demonstrate the usefulness of Ajzen's (1991, 2001) Theory of Planned Behavior (TPB) to understanding violation behaviors in aircraft maintenance. A questionnaire was administered to 307 aircraft maintenance workers. Constructs measured by the survey included perceptions of management attitudes to safety, own attitudes to violations, intention to violate, group norms, workplace pressures, and violations. A model based on the TPB illustrated hypothetical connections among these variables. Path analyses using AMOS suggested some theoretically justifiable modifications to the model. Fit statistics of the revised model were excellent with intentions, group norms, and personal attitudes combining to explain 50% of the variance in self-reported violations. The model highlighted the importance of management attitudes and group norms as direct and indirect predictors of violation behavior. We conclude that the TPB is a useful tool for understanding the psychological background to the procedural violations so often associated with incidents and accidents. 2009 Elsevier Ltd. All rights reserved.
The global gridded crop model intercomparison: Data and modeling protocols for Phase 1 (v1.0)
Elliott, J.; Müller, C.; Deryng, D.; ...
2015-02-11
We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project consist of global simulations of yields, phenologies, and many land-surface fluxes using 12–15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification ofmore » key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.« less
NASA Astrophysics Data System (ADS)
Chaumont, Diane; Huard, David; Logan, Travis; Sottile, Marie-France; Brown, Ross; Gauvin St-Denis, Blaise; Grenier, Patrick; Braun, Marco
2013-04-01
Planning and adapting to a changing climate requires credible information about the magnitude and rate of projected changes. Ouranos, a consortium on regional climatology and adaptation to climate change was launched in the Province of Québec, Canada, ten years ago, with the objective of developing and providing climate information and expertise in support to adaption. Ouranos differs from most other climate service centers by integrating climate modeling activities, impacts and adaptation expertise and climate analysis services under one roof. The Climate Scenarios Group operates at the interface between climate modellers and users and is responsible for developing, producing and communicating climate scenarios to end-users in a consistent manner. This process requires close collaboration with users to define, understand and eventually anticipate their needs. The varied scientific expertise of climate scenarios specialists --who also act as communicators-- has proven to be a key element for successful communication. A large amount of effort is spent on the characterization and communication of the uncertainties involved in scenario construction. Two main activities have been put in place by the experts in climate modeling to address this: (1) a training course on climate models and (2) a fact-sheet summarizing the uncertainty and robustness of the climate change scenario provided for each I&A application. The latter tool ensures the transparency, traceability, and accountability of our products, and at the same time, encourages a sense of shared responsibility for the final choice of climate scenarios. In addition to uncertainty, two other main issues have been identified as essential in communication with users: 1) observed natural variability at relevant scales and 2) reconciliation of the projected trend with the recent observed trend. Our group has devoted substantial resources for the advancement of communication with end-users in these particular areas. This presentation will provide an overview of progress in communicating climate information at the Ouranos Consortium. We will discuss success and failures and future plans, in particular the extent to which Ouranos needs to work with users in decision-making activities.
Hrinkevich, Kathryn H; Progar, Robert A; Shaw, David C
2016-01-01
The balsam woolly adelgid (Adelges piceae (Ratzeburg) (Homoptera: Adelgidae)) (BWA) is a nonnative, invasive insect that threatens Abies species throughout North America. It is well established in the Pacific Northwest, but continues to move eastward through Idaho and into Montana and potentially threatens subalpine fir to the south in the central and southern Rocky Mountains. We developed a climatic risk model and map that predicts BWA impacts to subalpine fir using a two-step process. Using 30-year monthly climate normals from sites with quantitatively derived BWA damage severity index values, we built a regression model that significantly explained insect damage. The sites were grouped into two distinct damage categories (high damage and mortality versus little or no mortality and low damage) and the model estimates for each group were used to designate distinct value ranges for four climatic risk categories: minimal, low, moderate, and high. We then calculated model estimates for each cell of a 4-kilometer resolution climate raster and mapped the risk categories over the entire range of subalpine fir in the western United States. The spatial variation of risk classes indicates a gradient of climatic susceptibility generally decreasing from the Olympic Peninsula in Washington and the Cascade Range in Oregon and Washington moving eastward, with the exception of some high risk areas in northern Idaho and western Montana. There is also a pattern of decreasing climatic susceptibility from north to south in the Rocky Mountains. Our study provides an initial step for modeling the relationship between climate and BWA damage severity across the range of subalpine fir. We showed that September minimum temperature and a metric calculated as the maximum May temperature divided by total May precipitation were the best climatic predictors of BWA severity. Although winter cold temperatures and summer heat have been shown to influence BWA impacts in other locations, these variables were not as predictive as spring and fall conditions in the Pacific Northwest.
NASA Astrophysics Data System (ADS)
Ivanovic, Ruza F.; Gregoire, Lauren J.; Kageyama, Masa; Roche, Didier M.; Valdes, Paul J.; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev
2016-07-01
The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.
Hurricanes and Climate: the U.S. CLIVAR Working Group on Hurricanes
NASA Technical Reports Server (NTRS)
Walsh, Kevin; Camargo, Suzana J.; Vecchi, Gabriel A.; Daloz, Anne Sophie; Elsner, James; Emanuel, Kerry; Horn, Michael; Lim, Young-Kwon; Roberts, Malcolm; Patricola, Christina;
2015-01-01
While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. The idealized experiments of the Hurricane Working Group of U.S. CLIVAR, combined with results from other model simulations, have suggested relationships between tropical cyclone formation rates and climate variables such as mid-tropospheric vertical velocity. Systematic differences are shown between experiments in which only sea surface temperature is increases versus experiments where only atmospheric carbon dioxide is increased, with the carbon dioxide experiments more likely to demonstrate a decrease in numbers. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.
Assessing Impacts of Climate Change on Forests: The State of Biological Modeling
DOE R&D Accomplishments Database
Dale, V. H.; Rauscher, H. M.
1993-04-06
Models that address the impacts to forests of climate change are reviewed by four levels of biological organization: global, regional or landscape, community, and tree. The models are compared as to their ability to assess changes in greenhouse gas flux, land use, maps of forest type or species composition, forest resource productivity, forest health, biodiversity, and wildlife habitat. No one model can address all of these impacts, but landscape transition models and regional vegetation and land-use models consider the largest number of impacts. Developing landscape vegetation dynamics models of functional groups is suggested as a means to integrate the theory of both landscape ecology and individual tree responses to climate change. Risk assessment methodologies can be adapted to deal with the impacts of climate change at various spatial and temporal scales. Four areas of research development are identified: (1) linking socioeconomic and ecologic models, (2) interfacing forest models at different scales, (3) obtaining data on susceptibility of trees and forest to changes in climate and disturbance regimes, and (4) relating information from different scales.
Understanding National Models for Climate Assessments
NASA Astrophysics Data System (ADS)
Dave, A.; Weingartner, K.
2017-12-01
National-level climate assessments have been produced or are underway in a number of countries. These efforts showcase a variety of approaches to mapping climate impacts onto human and natural systems, and involve a variety of development processes, organizational structures, and intended purposes. This presentation will provide a comparative overview of national `models' for climate assessments worldwide, drawing from a geographically diverse group of nations with varying capacities to conduct such assessments. Using an illustrative sampling of assessment models, the presentation will highlight the range of assessment mandates and requirements that drive this work, methodologies employed, focal areas, and the degree to which international dimensions are included for each nation's assessment. This not only allows the U.S. National Climate Assessment to be better understood within an international context, but provides the user with an entry point into other national climate assessments around the world, enabling a better understanding of the risks and vulnerabilities societies face.
Ryberg, Karen R.; Blomquist, Joel; Sprague, Lori A.; Sekellick, Andrew J.; Keisman, Jennifer
2018-01-01
Causal attribution of changes in water quality often consists of correlation, qualitative reasoning, listing references to the work of others, or speculation. To better support statements of attribution for water-quality trends, structural equation modeling was used to model the causal factors of total phosphorus loads in the Chesapeake Bay watershed. By transforming, scaling, and standardizing variables, grouping similar sites, grouping some causal factors into latent variable models, and using methods that correct for assumption violations, we developed a structural equation model to show how causal factors interact to produce total phosphorus loads. Climate (in the form of annual total precipitation and the Palmer Hydrologic Drought Index) and anthropogenic inputs are the major drivers of total phosphorus load in the Chesapeake Bay watershed. Increasing runoff due to natural climate variability is offsetting purposeful management actions that are otherwise decreasing phosphorus loading; consequently, management actions may need to be reexamined to achieve target reductions in the face of climate variability.
NASA Astrophysics Data System (ADS)
Quinn, P.
2015-12-01
The Arctic Monitoring and Assessment Programme (AMAP) established an Expert Group on Short-Lived Climate Forcers (SLCFs) in 2009 with the goal of reviewing the state of science surrounding SLCFs in the Arctic and recommending science tasks to improve the state of knowledge and its application to policy-making. In 2011, the result of the Expert Group's work was published in a technical report entitled The Impact of Black Carbon on Arctic Climate (AMAP, 2011). That report focused entirely on black carbon (BC) and co-emitted organic carbon (OC). The SLCFs Expert Group then expanded its scope to include all species co-emitted with BC as well as tropospheric ozone. An assessment report, entitled Black Carbon and Tropospheric Ozone as Arctic Climate Forcers, was published in 2015. The assessment includes summaries of measurement methods and emissions inventories of SLCFs, atmospheric transport of SLCFs to and within the Arctic, modeling methods for estimating the impact of SLCFs on Arctic climate, model-measurement inter-comparisons, trends in concentrations of SLCFs in the Arctic, and a literature review of Arctic radiative forcing and climate response. In addition, three Chemistry Climate Models and five Chemistry Transport Models were used to calculate Arctic burdens of SLCFs and precursors species, radiative forcing, and Arctic temperature response to the forcing. Radiative forcing was calculated for the direct atmospheric effect of BC, BC-snow/ice effect, and cloud indirect effects. Forcing and temperature response associated with different source sectors (Domestic, Energy+Industry+Waste, Transport, Agricultural waste burning, Forest fires, and Flaring) and source regions (United States, Canada, Russia, Nordic Countries, Rest of Europe, East and South Asia, Arctic, mid-latitudes, tropics, southern hemisphere) were calculated. To enable an evaluation of the cost-effectiveness of regional emission mitigation options, the normalized impacts (i.e., impacts per unit emission from each sector and region) were also calculated. Key findings from the 2015 assessment will be presented.
Assessing and Upgrading Ocean Mixing for the Study of Climate Change
NASA Astrophysics Data System (ADS)
Howard, A. M.; Fells, J.; Lindo, F.; Tulsee, V.; Canuto, V.; Cheng, Y.; Dubovikov, M. S.; Leboissetier, A.
2016-12-01
Climate is critical. Climate variability affects us all; Climate Change is a burning issue. Droughts, floods, other extreme events, and Global Warming's effects on these and problems such as sea-level rise and ecosystem disruption threaten lives. Citizens must be informed to make decisions concerning climate such as "business as usual" vs. mitigating emissions to keep warming within bounds. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. To make useful predictions we must realistically model each component of the climate system, including the ocean, whose critical role includes transporting&storing heat and dissolved CO2. We need physically based parameterizations of key ocean processes that can't be put explicitly in a global climate model, e.g. vertical&lateral mixing. The NASA-GISS turbulence group uses theory to model mixing including: 1) a comprehensive scheme for small scale vertical mixing, including convection&shear, internal waves & double-diffusion, and bottom tides 2) a new parameterization for the lateral&vertical mixing by mesoscale eddies. For better understanding we write our own programs. To assess the modelling MATLAB programs visualize and calculate statistics, including means, standard deviations and correlations, on NASA-GISS OGCM output with different mixing schemes and help us study drift from observations. We also try to upgrade the schemes, e.g. the bottom tidal mixing parameterizations' roughness, calculated from high resolution topographic data using Gaussian weighting functions with cut-offs. We study the effects of their parameters to improve them. A FORTRAN program extracts topography data subsets of manageable size for a MATLAB program, tested on idealized cases, to visualize&calculate roughness on. Students are introduced to modeling a complex system, gain a deeper appreciation of climate science, programming skills and familiarity with MATLAB, while furthering climate science by improving our mixing schemes. We are incorporating climate research into our college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293.
NASA Astrophysics Data System (ADS)
Alexander, K.; Easterbrook, S. M.
2015-04-01
We analyze the source code of eight coupled climate models, selected from those that participated in the CMIP5 (Taylor et al., 2012) or EMICAR5 (Eby et al., 2013; Zickfeld et al., 2013) intercomparison projects. For each model, we sort the preprocessed code into components and subcomponents based on dependency structure. We then create software architecture diagrams that show the relative sizes of these components/subcomponents and the flow of data between them. The diagrams also illustrate several major classes of climate model design; the distribution of complexity between components, which depends on historical development paths as well as the conscious goals of each institution; and the sharing of components between different modeling groups. These diagrams offer insights into the similarities and differences in structure between climate models, and have the potential to be useful tools for communication between scientists, scientific institutions, and the public.
The meaning and measurement of implementation climate
2011-01-01
Background Climate has a long history in organizational studies, but few theoretical models integrate the complex effects of climate during innovation implementation. In 1996, a theoretical model was proposed that organizations could develop a positive climate for implementation by making use of various policies and practices that promote organizational members' means, motives, and opportunities for innovation use. The model proposes that implementation climate--or the extent to which organizational members perceive that innovation use is expected, supported, and rewarded--is positively associated with implementation effectiveness. The implementation climate construct holds significant promise for advancing scientific knowledge about the organizational determinants of innovation implementation. However, the construct has not received sufficient scholarly attention, despite numerous citations in the scientific literature. In this article, we clarify the meaning of implementation climate, discuss several measurement issues, and propose guidelines for empirical study. Discussion Implementation climate differs from constructs such as organizational climate, culture, or context in two important respects: first, it has a strategic focus (implementation), and second, it is innovation-specific. Measuring implementation climate is challenging because the construct operates at the organizational level, but requires the collection of multi-dimensional perceptual data from many expected innovation users within an organization. In order to avoid problems with construct validity, assessments of within-group agreement of implementation climate measures must be carefully considered. Implementation climate implies a high degree of within-group agreement in climate perceptions. However, researchers might find it useful to distinguish implementation climate level (the average of implementation climate perceptions) from implementation climate strength (the variability of implementation climate perceptions). It is important to recognize that the implementation climate construct applies most readily to innovations that require collective, coordinated behavior change by many organizational members both for successful implementation and for realization of anticipated benefits. For innovations that do not possess these attributes, individual-level theories of behavior change could be more useful in explaining implementation effectiveness. Summary This construct has considerable value in implementation science, however, further debate and development is necessary to refine and distinguish the construct for empirical use. PMID:21781328
Characteristics of Tropical Cyclones in High-Resolution Models of the Present Climate
NASA Technical Reports Server (NTRS)
Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, Jeffery A.; Kim, Daeyhun; Kumar, Arun; LaRow, Timothy E.; Lim, Young-Kwon; Murakami, Hiroyuki; Roberts, Malcolm J.;
2014-01-01
The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) in two types of experiments, using a climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.
Characteristics of Tropical Cyclones in High-resolution Models in the Present Climate
NASA Technical Reports Server (NTRS)
Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; Jonas, Jeffrey A.; Kim, Daehyun; Kumar, Arun; LaRow, Timothy E.; Lim, Young-Kwon; Murakami, Hiroyuki; Reed, Kevin;
2014-01-01
The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.
Signs of the Land: Reaching Arctic Communities Facing Climate Change
NASA Astrophysics Data System (ADS)
Sparrow, E. B.; Chase, M. J.; Demientieff, S.; Pfirman, S. L.; Brunacini, J.
2014-12-01
In July 2014, a diverse and intergenerational group of Alaskan Natives came together on Howard Luke's Galee'ya Camp by the Tanana River in Fairbanks, Alaska to talk about climate change and it's impacts on local communities. Over a period of four days, the Signs of the Land Climate Change Camp wove together traditional knowledge, local observations, Native language, and climate science through a mix of storytelling, presentations, dialogue, and hands-on, community-building activities. This camp adapted the model developed several years ago under the Association for Interior Native Educators (AINE)'s Elder Academy. Part of the Polar Learning and Responding Climate Change Education Partnership, the Signs of the Land Climate Change Camp was developed and conducted collaboratively with multiple partners to test a model for engaging indigenous communities in the co-production of climate change knowledge, communication tools, and solutions-building. Native Alaskans have strong subsistence and cultural connections to the land and its resources, and, in addition to being keen observers of their environment, have a long history of adapting to changing conditions. Participants in the camp included Elders, classroom teachers, local resource managers and planners, community members, and climate scientists. Based on their experiences during the camp, participants designed individualized outreach plans for bringing culturally-responsive climate learning to their communities and classrooms throughout the upcoming year. Plans included small group discussions, student projects, teacher training, and conference presentations.
Konold, Timothy; Cornell, Dewey; Shukla, Kathan; Huang, Francis
2017-06-01
Research indicates that a positive school climate is associated with higher levels of student engagement and lower rates of peer aggression. However, less attention has been given to whether such findings are consistent across racial/ethnic groups. The current study examined whether Black, Hispanic, and White high school students differed in their perceptions of school climate, student engagement, and peer aggression as measured by the Authoritative School Climate survey. In addition, the study tested whether the associations between school climate and both student engagement and peer aggression varied as a function of racial/ethnic group. The sample consisted of 48,027 students in grades 9-12 (51.4 % female; 17.9 % Black, 10.5 % Hispanic, 56.7 % White, and 14.9 % other) attending 323 high schools. Regression models that contrasted racial/ethnic groups controlled for the nesting of students within schools and used student covariates of parent education, student gender, and percentage of schoolmates sharing the same race/ethnicity, as well as school covariates of school size and school percentage of students eligible for free- or reduced-price meals. Perceptions of school climate differed between Black and White groups, but not between Hispanic and White groups. However, race/ethnicity did not moderate the associations between school climate and either engagement or peer aggression. Although correlational and cross-sectional in nature, these results are consistent with the conclusion that a positive school climate holds similar benefits of promoting student engagement and reducing victimization experiences across Black, Hispanic, and White groups.
Effects of Implementing Subgrid-Scale Cloud-Radiation Interactions in a Regional Climate Model
NASA Astrophysics Data System (ADS)
Herwehe, J. A.; Alapaty, K.; Otte, T.; Nolte, C. G.
2012-12-01
Interactions between atmospheric radiation, clouds, and aerosols are the most important processes that determine the climate and its variability. In regional scale models, when used at relatively coarse spatial resolutions (e.g., larger than 1 km), convective cumulus clouds need to be parameterized as subgrid-scale clouds. Like many groups, our regional climate modeling group at the EPA uses the Weather Research & Forecasting model (WRF) as a regional climate model (RCM). One of the findings from our RCM studies is that the summertime convective systems simulated by the WRF model are highly energetic, leading to excessive surface precipitation. We also found that the WRF model does not consider the interactions between convective clouds and radiation, thereby omitting an important process that drives the climate. Thus, the subgrid-scale cloudiness associated with convective clouds (from shallow cumuli to thunderstorms) does not exist and radiation passes through the atmosphere nearly unimpeded, potentially leading to overly energetic convection. This also has implications for air quality modeling systems that are dependent upon cloud properties from the WRF model, as the failure to account for subgrid-scale cloudiness can lead to problems such as the underrepresentation of aqueous chemistry processes within clouds and the overprediction of ozone from overactive photolysis. In an effort to advance the climate science of the cloud-aerosol-radiation (CAR) interactions in RCM systems, as a first step we have focused on linking the cumulus clouds with the radiation processes. To this end, our research group has implemented into WRF's Kain-Fritsch (KF) cumulus parameterization a cloudiness formulation that is widely used in global earth system models (e.g., CESM/CAM5). Estimated grid-scale cloudiness and associated condensate are adjusted to account for the subgrid clouds and then passed to WRF's Rapid Radiative Transfer Model - Global (RRTMG) radiation schemes to affect the shortwave and longwave radiative processes. To evaluate the effects of implementing the subgrid-scale cloud-radiation interactions on WRF regional climate simulations, a three-year study period (1988-1990) was simulated over the CONUS using two-way nested domains with 108 km and 36 km horizontal grid spacing, without and with the cumulus feedbacks to radiation, and without and with some form of four dimensional data assimilation (FDDA). Initial and lateral boundary conditions (as well as data for the FDDA, when enabled) were supplied from downscaled NCEP-NCAR Reanalysis II (R2) data sets. Evaluation of the simulation results will be presented comparing regional surface precipitation and temperature statistics with North American Regional Reanalysis (NARR) data and Climate Forecast System Reanalysis (CFSR) data, respectively, as well as comparison with available surface radiation (SURFRAD) and satellite (CERES) observations. This research supports improvements in the EPA's WRF-CMAQ modeling system, leading to better predictions of present and future air quality and climate interactions in order to protect human health and the environment.
Bringing a Realistic Global Climate Modeling Experience to a Broader Audience
NASA Astrophysics Data System (ADS)
Sohl, L. E.; Chandler, M. A.; Zhou, J.
2010-12-01
EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.
Steele, Madeline O.; Chang, Heejun; Reusser, Deborah A.; Brown, Cheryl A.; Jung, Il-Won
2012-01-01
As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.
The socialization of dominance: peer group contextual effects on homophobic and dominance attitudes.
Poteat, V Paul; Espelage, Dorothy L; Green, Harold D
2007-06-01
Using the framework of social dominance theory, the current investigation tested for the contextual effects of adolescent peer groups on individuals' homophobic and social dominance attitudes. Results from multilevel models indicated that significant differences existed across peer groups on homophobic attitudes. In addition, these differences were accounted for on the basis of the hierarchy-enhancing or -attenuating climate of the group. A group socialization effect on individuals' social dominance attitudes over time was also observed. Furthermore, the social climate of the peer group moderated the stability of individuals' social dominance attitudes. Findings support the need to examine more proximal and informal group affiliations and earlier developmental periods in efforts to build more comprehensive theoretical models explaining when and how prejudiced and dominance attitudes are formed and the way in which they are perpetuated. (c) 2007 APA, all rights reserved.
Educational and Scientific Applications of Climate Model Diagnostic Analyzer
NASA Astrophysics Data System (ADS)
Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.
2016-12-01
Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of Two Variables, and the datasets used are NCAR CAM total cloud fraction and MODIS total cloud fraction. The scientific highlight of the use case is that the CAM5 model overall does a fairly decent job at simulating total cloud cover, though simulates too few clouds especially near and offshore of the eastern ocean basins where low clouds are dominant.
NASA Technical Reports Server (NTRS)
Putnam, WilliamM.
2011-01-01
In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.
Assessing ocean vertical mixing schemes for the study of climate change
NASA Astrophysics Data System (ADS)
Howard, A. M.; Lindo, F.; Fells, J.; Tulsee, V.; Cheng, Y.; Canuto, V.
2014-12-01
Climate change is a burning issue of our time. It is critical to know the consequences of choosing "business as usual" vs. mitigating our emissions for impacts e.g. ecosystem disruption, sea-level rise, floods and droughts. To make predictions we must model realistically each component of the climate system. The ocean must be modeled carefully as it plays a critical role, including transporting heat and storing heat and dissolved carbon dioxide. Modeling the ocean realistically in turn requires physically based parameterizations of key processes in it that cannot be explicitly represented in a global climate model. One such process is vertical mixing. The turbulence group at NASA-GISS has developed a comprehensive new vertical mixing scheme (GISSVM) based on turbulence theory, including surface convection and wind shear, interior waves and double-diffusion, and bottom tides. The GISSVM is tested in stand-alone ocean simulations before being used in coupled climate models. It is also being upgraded to more faithfully represent the physical processes. To help assess mixing schemes, students use data from NASA-GISS to create visualizations and calculate statistics including mean bias and rms differences and correlations of fields. These are created and programmed with MATLAB. Results with the commonly used KPP mixing scheme and the present GISSVM and candidate improved variants of GISSVM will be compared between stand-alone ocean models and coupled models and observations. This project introduces students to modeling of a complex system, an important theme in contemporary science and helps them gain a better appreciation of climate science and a new perspective on it. They also gain familiarity with MATLAB, a widely used tool, and develop skills in writing and understanding programs. Moreover they contribute to the advancement of science by providing information that will help guide the improvement of the GISSVM and hence of ocean and climate models and ultimately our understanding and prediction of climate. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, a minority serving institution in an urban setting in central Brooklyn. This Project is supported by NSF award AGS-1359293 REU site: CUNY/GISS Center for Global Climate Research.
Climate@Home: Crowdsourcing Climate Change Research
NASA Astrophysics Data System (ADS)
Xu, C.; Yang, C.; Li, J.; Sun, M.; Bambacus, M.
2011-12-01
Climate change deeply impacts human wellbeing. Significant amounts of resources have been invested in building super-computers that are capable of running advanced climate models, which help scientists understand climate change mechanisms, and predict its trend. Although climate change influences all human beings, the general public is largely excluded from the research. On the other hand, scientists are eagerly seeking communication mediums for effectively enlightening the public on climate change and its consequences. The Climate@Home project is devoted to connect the two ends with an innovative solution: crowdsourcing climate computing to the general public by harvesting volunteered computing resources from the participants. A distributed web-based computing platform will be built to support climate computing, and the general public can 'plug-in' their personal computers to participate in the research. People contribute the spare computing power of their computers to run a computer model, which is used by scientists to predict climate change. Traditionally, only super-computers could handle such a large computing processing load. By orchestrating massive amounts of personal computers to perform atomized data processing tasks, investments on new super-computers, energy consumed by super-computers, and carbon release from super-computers are reduced. Meanwhile, the platform forms a social network of climate researchers and the general public, which may be leveraged to raise climate awareness among the participants. A portal is to be built as the gateway to the climate@home project. Three types of roles and the corresponding functionalities are designed and supported. The end users include the citizen participants, climate scientists, and project managers. Citizen participants connect their computing resources to the platform by downloading and installing a computing engine on their personal computers. Computer climate models are defined at the server side. Climate scientists configure computer model parameters through the portal user interface. After model configuration, scientists then launch the computing task. Next, data is atomized and distributed to computing engines that are running on citizen participants' computers. Scientists will receive notifications on the completion of computing tasks, and examine modeling results via visualization modules of the portal. Computing tasks, computing resources, and participants are managed by project managers via portal tools. A portal prototype has been built for proof of concept. Three forums have been setup for different groups of users to share information on science aspect, technology aspect, and educational outreach aspect. A facebook account has been setup to distribute messages via the most popular social networking platform. New treads are synchronized from the forums to facebook. A mapping tool displays geographic locations of the participants and the status of tasks on each client node. A group of users have been invited to test functions such as forums, blogs, and computing resource monitoring.
Livshultz, Tatyana; Mead, Jerry V; Goyder, David J; Brannin, Michelle
2011-12-01
Climate change that increases mortality of plants and pollinators can create mate-finding Allee effects and thus act as a strong selective force on floral morphology. Milkweeds (Secamonoideae and Asclepiadoideae; Apocynaceae) are typically small plants of seasonally dry habitats, with pollinia and high pollen-transfer efficiency. Their sister group (tribe Baisseeae and Dewevrella) is mostly comprised of giant lianas of African rainforests, with pollen in monads. Comparison of the two groups motivated a new hypothesis: milkweeds evolved in the context of African aridification and the shifting of rainforest to dry forest. Pollinia and high pollen-transfer efficiency may have been adaptations that alleviated mate-finding Allee effects generated by high mortality during droughts. We formally tested whether milkweeds have a drier climate niche by comparing milkweeds with plesiomorphic traits (Secamonoideae) and the milkweed sister group in continental Africa. We georeferenced specimens of the milkweed sister group and Secamonoideae in continental Africa, extracted 19 climatic variables from the Worldclim model, conducted factor analysis to identify correlated suites of variables, and compared the frequency distributions of the two lineages relative to each factor. The distributions of Secamonoideae and the milkweed sister group differed significantly relative to four factors, each correlated with a distinct suite of climate parameters: (1) air temperature (Secamonoideae: cooler), (2) total and (3) summer precipitation (Secamonoideae: drier), and (4) temperature seasonality and isothermality (Secamonoideae: more seasonal and less isothermal). Secamonoideae in continental Africa inhabit drier, cooler sites than do the milkweed sister group, consistent with a shift from rainforests to dry forests in a cooling climate.
Multi-scale modeling of relationships between forest health and climatic factors
Michael K. Crosby; Zhaofei Fan; Xingang Fan; Martin A. Spetich; Theodor D. Leininger
2015-01-01
Forest health and mortality trends are impacted by changes in climate. These trends can vary by species, plot location, forest type, and/or ecoregion. To assess the variation among these groups, Forest Inventory and Analysis (FIA) data were obtained for 10 states in the southeastern United States and combined with downscaled climate data from the Weather Research and...
McKenzie, Don; Allen, Craig D.
2007-01-01
Warming temperatures across western North America, coupled with increased drought, are expected to exacerbate disturbance regimes, particularly wildfires, insect outbreaks, and invasions of exotic species. Many ecologists and resource managers expect ecosystems to change more rapidly from disturbance effects than from the effects of a changing climate by itself. A particular challenge is to understand the interactions among disturbance regimes; for example, how will massive outbreaks of bark beetles, which kill drought-stressed trees by feeding on cambial tissues, increase the potential for large severe wildfires in a warming climate?Researchers in climatology, ecosystem science, fire and insect ecology, and landscape modeling from across western North America convened in Tucson, Ariz., for a 2 and a half day intensive workshop to identify new research directions in climate change and disturbance ecology. Four work groups focused on different aspects of the response of disturbance regimes to climate change: (1) extreme events and climatic variability (2) the effects of changing disturbance regimes on ecosystems, (3) disturbance interactions and cumulative effects, and (4) developing new landscape disturbance models. The workshop was structured with the analytic hierarchy process, a decision support method for achieving consensus from diverse groups of experts without sacrificing individual contributions.
A Model for Collaborative Learning in Undergraduate Climate Change Courses
NASA Astrophysics Data System (ADS)
Teranes, J. L.
2008-12-01
Like several colleges and universities across the nation, the University of California, San Diego, has introduced climate change topics into many existing and new undergraduate courses. I have administered a program in this area at UCSD and have also developed and taught a new lower-division UCSD course entitled "Climate Change and Society", a general education course for non-majors. This class covers the basics of climate change, such as the science that explains it, the causes of climate change, climate change impacts, and mitigation strategies. The teaching methods for this course stress interdisciplinary approaches. I find that inquiry-based and collaborative modes of learning are particularly effective when applied to science-based climate, environmental and sustainability topics. Undergraduate education is often dominated by a competitive and individualistic approach to learning. In this approach, individual success is frequently perceived as contingent on others being less successful. Such a model is at odds with commonly stated goals of teaching climate change and sustainability, which are to equip students to contribute to the debate on global environmental change and societal adaptation strategies; and to help students become better informed citizens and decision makers. I present classroom-tested strategies for developing collaborative forms of learning in climate change and environmental courses, including team projects, group presentations and group assessment exercises. I show how critical thinking skills and long-term retention of information can benefit in the collaborative mode of learning. I find that a collaborative learning model is especially appropriate to general education courses in which the enrolled student body represents a wide diversity of majors, class level and expertise. I also connect collaborative coursework in interdisciplinary environmental topics directly to applications in the field, where so much "real-world" achievement in research, education, government and business is effectively accomplished in collaborative teams.
Impact of climate change on global malaria distribution.
Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M; Morse, Andrew P; Colón-González, Felipe J; Stenlund, Hans; Martens, Pim; Lloyd, Simon J
2014-03-04
Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution.
Impact of climate change on global malaria distribution
Caminade, Cyril; Kovats, Sari; Rocklov, Joacim; Tompkins, Adrian M.; Morse, Andrew P.; Colón-González, Felipe J.; Stenlund, Hans; Martens, Pim; Lloyd, Simon J.
2014-01-01
Malaria is an important disease that has a global distribution and significant health burden. The spatial limits of its distribution and seasonal activity are sensitive to climate factors, as well as the local capacity to control the disease. Malaria is also one of the few health outcomes that has been modeled by more than one research group and can therefore facilitate the first model intercomparison for health impacts under a future with climate change. We used bias-corrected temperature and rainfall simulations from the Coupled Model Intercomparison Project Phase 5 climate models to compare the metrics of five statistical and dynamical malaria impact models for three future time periods (2030s, 2050s, and 2080s). We evaluated three malaria outcome metrics at global and regional levels: climate suitability, additional population at risk and additional person-months at risk across the model outputs. The malaria projections were based on five different global climate models, each run under four emission scenarios (Representative Concentration Pathways, RCPs) and a single population projection. We also investigated the modeling uncertainty associated with future projections of populations at risk for malaria owing to climate change. Our findings show an overall global net increase in climate suitability and a net increase in the population at risk, but with large uncertainties. The model outputs indicate a net increase in the annual person-months at risk when comparing from RCP2.6 to RCP8.5 from the 2050s to the 2080s. The malaria outcome metrics were highly sensitive to the choice of malaria impact model, especially over the epidemic fringes of the malaria distribution. PMID:24596427
NASA Astrophysics Data System (ADS)
Estrada, M.; Boudrias, M. A.; Silva-Send, N. J.; Gershunov, A.; Anders, S.
2013-12-01
Culture has been shown to be an important determinant of Latino/Hispanic American environmental attitudes (Schultz, Unipan, & Gamba, 2000), which might help to explain the underrepresentation of Latinos in the U.S. 'environmental' movement. With shifting U.S. demographics, however, there is increased urgency to understand how Latinos integrate into the community that is concerned and literate about climate change. As part of the Climate Education Partners (CEP) work in San Diego, we investigated how to address this ethnic group disparity. In this paper, we describe a study of how climate change science knowledge relates to Latino and Non-Latino citizen (a) engagement in conservation behaviors and (b) more informed decision-making. Drawing upon previous work on the Tripartite Integration Model of Social Influence (TIMSI) (Estrada et al., 2011), we hypothesized that climate change knowledge that promotes efficacy (i.e., a sense that one can do something) would relate to greater engagement in conservation behaviors and more informed decision-making (both common of community members concerned about climate change). To test this model, 1001 San Diego residence participated in a telephone survey in which the attitudes towards climate change were assessed using '6 Americas' segmentation (Leiserowitz et al., 2011), in addition to climate change science knowledge, efficacy, values, and engagement in weekly and yearly climate change friendly behaviors (e.g., conservation, transportation, community engagement behaviors). Results showed that there were significant differences in the 6 America segmentation distributions, knowledge, efficacy and behavioral engagement with Latinos significantly more concerned than Non-Latinos, and reporting greater knowledge, efficacy and engagement in behaviors. However, data from both groups showed support for the TIMSI theoretical framework, such that efficacy mediated the relationship between climate change knowledge and behavior. Thus, for both groups, climate change science knowledge was more likely to result in behavioral engagement when the science knowledge was accompanied with the belief that one has the ability to engage in behaviors that mitigate or adapt to climate change (i.e., efficacy). Implications for how to improve both Latino and Non-Latino climate change education that results in informed decision-making and greater integration into the community concerned about climate change will be discussed.
The foundation for climate services in Belgium: CORDEX.be
NASA Astrophysics Data System (ADS)
Van Schaeybroeck, Bert; Termonia, Piet; De Ridder, Koen; Fettweis, Xavier; Gobin, Anne; Luyten, Patrick; Marbaix, Philippe; Pottiaux, Eric; Stavrakou, Trissevgeni; Van Lipzig, Nicole; van Ypersele, Jean-Pascal; Willems, Patrick
2017-04-01
According to the Global Framework for Climate Services (GFCS) there are four pillars required to build climate services. As the first step towards the realization of a climate center in Belgium, the national project CORDEX.be focused on one pillar: research modelling and projection. By bringing together the Belgian climate and impact modeling research of nine groups a data-driven capacity development and community building in Belgium based on interactions with users. The project is based on the international CORDEX ("COordinated Regional Climate Downscaling Experiment") project where ".be" indicates it will go beyond for Belgium. Our national effort links to the regional climate initiatives through the contribution of multiple high-resolution climate simulations over Europe following the EURO-CORDEX guidelines. Additionally the same climate simulations were repeated at convection-permitting resolutions over Belgium (3 to 5 km). These were used to drive different local impact models to investigate the impact of climate change on urban effects, storm surges and waves, crop production and changes in emissions from vegetation. Akin to international frameworks such as CMIP and CORDEX a multi-model approach is adopted allowing for uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. However, due to the lack of a large set of high resolution model runs, a combination of all available climate information is supplemented with the statistical downscaling approach. The organization of the project, together with its main results will be outlined. The proposed coordination framework could serve as a demonstration case for regions or countries where the climate-research capacity is present but a structure is required to assemble it coherently. Based on interactions and feedback with stakeholders different applications are planned, demonstrating the use of the climate data.
NASA Technical Reports Server (NTRS)
Redemann, Jens
2018-01-01
Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.
Characteristics of tropical cyclones in high-resolution models in the present climate
Shaevitz, Daniel A.; Camargo, Suzana J.; Sobel, Adam H.; ...
2014-12-05
The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TCmore » frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.« less
NASA Astrophysics Data System (ADS)
Bush, Drew; Sieber, Renee; Seiler, Gale; Chandler, Mark
2018-04-01
This study with 79 students in Montreal, Quebec, compared the educational use of a National Aeronautics and Space Administration (NASA) global climate model (GCM) to climate education technologies developed for classroom use that included simpler interfaces and processes. The goal was to show how differing climate education technologies succeed and fail at getting students to evolve in their understanding of anthropogenic global climate change (AGCC). Many available climate education technologies aim to convey key AGCC concepts or Earth systems processes; the educational GCM used here aims to teach students the methods and processes of global climate modeling. We hypothesized that challenges to learning about AGCC make authentic technology-enabled inquiry important in developing accurate understandings of not just the issue but how scientists research it. The goal was to determine if student learning trajectories differed between the comparison and treatment groups based on whether each climate education technology allowed authentic scientific research. We trace learning trajectories using pre/post exams, practice quizzes, and written student reflections. To examine the reasons for differing learning trajectories, we discuss student pre/post questionnaires, student exit interviews, and 535 min of recorded classroom video. Students who worked with a GCM demonstrated learning trajectories with larger gains, higher levels of engagement, and a better idea of how climate scientists conduct research. Students who worked with simpler climate education technologies scored lower in the course because of lower levels of engagement with inquiry processes that were perceived to not actually resemble the work of climate scientists.
GCSS/WGNE Pacific Cross-section Intercomparison: Tropical and Subtropical Cloud Transitions
NASA Astrophysics Data System (ADS)
Teixeira, J.
2008-12-01
In this presentation I will discuss the role of the GEWEX Cloud Systems Study (GCSS) working groups in paving the way for substantial improvements in cloud parameterization in weather and climate models. The GCSS/WGNE Pacific Cross-section Intercomparison (GPCI) is an extension of GCSS and is a different type of model evaluation where climate models are analyzed along a Pacific Ocean transect from California to the equator. This approach aims at complementing the more traditional efforts in GCSS by providing a simple framework for the evaluation of models that encompasses several fundamental cloud regimes such as stratocumulus, shallow cumulus and deep cumulus, as well as the transitions between them. Currently twenty four climate and weather prediction models are participating in GPCI. We will present results of the comparison between models and recent satellite data. In particular, we will explore in detail the potential of the Atmospheric Infrared Sounder (AIRS) and CloudSat data for the evaluation of the representation of clouds and convection in climate models.
COP21 climate negotiators' responses to climate model forecasts
NASA Astrophysics Data System (ADS)
Bosetti, Valentina; Weber, Elke; Berger, Loïc; Budescu, David V.; Liu, Ning; Tavoni, Massimo
2017-02-01
Policymakers involved in climate change negotiations are key users of climate science. It is therefore vital to understand how to communicate scientific information most effectively to this group. We tested how a unique sample of policymakers and negotiators at the Paris COP21 conference update their beliefs on year 2100 global mean temperature increases in response to a statistical summary of climate models' forecasts. We randomized the way information was provided across participants using three different formats similar to those used in Intergovernmental Panel on Climate Change reports. In spite of having received all available relevant scientific information, policymakers adopted such information very conservatively, assigning it less weight than their own prior beliefs. However, providing individual model estimates in addition to the statistical range was more effective in mitigating such inertia. The experiment was repeated with a population of European MBA students who, despite starting from similar priors, reported conditional probabilities closer to the provided models' forecasts than policymakers. There was also no effect of presentation format in the MBA sample. These results highlight the importance of testing visualization tools directly on the population of interest.
NASA Astrophysics Data System (ADS)
Clifford, K. R.; Travis, W.; Rangwala, I.; Rondeau, R.; Young, L.
2016-12-01
Resource managers in the western U.S. are increasingly tasked to incorporate climate change into management decisions and long-term planning, but this task is complicated by multiple challenges, among them the need to bridge between the differing perspectives and prerogatives of scientists and resource managers. As part of a larger, iterative, interdisciplinary, multi-landscape research project that built on a prior climate vulnerability research, we conducted more than 50 semi-structured interviews and four focus groups with resource managers in the Gunnison Basin in western Colorado. The interviews addressed the managers' risk perceptions and knowledge about the resources and landscapes, while the focus groups asked resource managers to reflect on their own resource decision-making in light of three narrative future climate scenarios created by scientists on the research team. While time-intensive, the interviews and focus groups produced important insights into the managers' understanding of both the resources in question and the future climate scenarios. We found that the managers' mental models of their systems, and their conceptions of landscape changes and future threats, were diverse and sometimes in conflict with those held by the research team. The managers' responses to the climate scenarios reflected divergent and nuanced perceptions of risk, adaptation and uncertainty, heavily shaped by personal experience—which could be a constraint under rapidly changing future conditions. Our deployment of social science methodologies facilitated the co-production of climate adaptation strategies and a bridge between and among scientists and managers. The participants found the focus groups helpful since they (1) provided space to focus on decision-making under climate change, rather than fixate on details of the science, and (2) facilitated interaction with colleagues from other agencies. Climate scientists used participant feedback to inform future scenario development. The use of small focus groups to engage with climate scenarios could add value to other ongoing efforts to promote landscape-scale adaptation.
Stochastic Parameterization: Toward a New View of Weather and Climate Models
Berner, Judith; Achatz, Ulrich; Batté, Lauriane; ...
2017-03-31
The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less
Stochastic Parameterization: Toward a New View of Weather and Climate Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berner, Judith; Achatz, Ulrich; Batté, Lauriane
The last decade has seen the success of stochastic parameterizations in short-term, medium-range, and seasonal forecasts: operational weather centers now routinely use stochastic parameterization schemes to represent model inadequacy better and to improve the quantification of forecast uncertainty. Developed initially for numerical weather prediction, the inclusion of stochastic parameterizations not only provides better estimates of uncertainty, but it is also extremely promising for reducing long-standing climate biases and is relevant for determining the climate response to external forcing. This article highlights recent developments from different research groups that show that the stochastic representation of unresolved processes in the atmosphere, oceans,more » land surface, and cryosphere of comprehensive weather and climate models 1) gives rise to more reliable probabilistic forecasts of weather and climate and 2) reduces systematic model bias. We make a case that the use of mathematically stringent methods for the derivation of stochastic dynamic equations will lead to substantial improvements in our ability to accurately simulate weather and climate at all scales. Recent work in mathematics, statistical mechanics, and turbulence is reviewed; its relevance for the climate problem is demonstrated; and future research directions are outlined« less
Model robustness as a confirmatory virtue: The case of climate science.
Lloyd, Elisabeth A
2015-02-01
I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independently-supported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present climate models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists' discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ivanovic, Ruza; Gregoire, Lauren; Kageyama, Masa; Roche, Didier; Valdes, Paul; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev
2016-04-01
The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 thousand years. Here, we present the design of a coordinated Core simulation over the period 21-9 thousand years before present (ka) with time varying orbital forcing, greenhouse gases, ice sheets, and other geographical changes. A choice of two ice sheet reconstructions is given. Additional focussed simulations will also be coordinated on an ad-hoc basis by the working group, for example to investigate the effect of ice sheet and iceberg meltwater, and the uncertainty in other forcings. Some of these focussed simulations will concentrate on shorter durations around specific events to allow the more computationally expensive models to take part. Ivanovic, R. F., Gregoire, L. J., Kageyama, M., Roche, D. M., Valdes, P. J., Burke, A., Drummond, R., Peltier, W. R., and Tarasov, L.: Transient climate simulations of the deglaciation 21-9 thousand years before present; PMIP4 Core experiment design and boundary conditions, Geosci. Model Dev. Discuss., 8, 9045-9102, doi:10.5194/gmdd-8-9045-2015, 2015.
Archis, Jennifer N; Akcali, Christopher; Stuart, Bryan L; Kikuchi, David; Chunco, Amanda J
2018-01-01
Anthropogenic climate change is a significant global driver of species distribution change. Although many species have undergone range expansion at their poleward limits, data on several taxonomic groups are still lacking. A common method for studying range shifts is using species distribution models to evaluate current, and predict future, distributions. Notably, many sources of 'current' climate data used in species distribution modeling use the years 1950-2000 to calculate climatic averages. However, this does not account for recent (post 2000) climate change. This study examines the influence of climate change on the eastern coral snake ( Micrurus fulvius ). Specifically, we: (1) identified the current range and suitable environment of M. fulvius in the Southeastern United States, (2) investigated the potential impacts of climate change on the distribution of M. fulvius , and (3) evaluated the utility of future models in predicting recent (2001-2015) records. We used the species distribution modeling program Maxent and compared both current (1950-2000) and future (2050) climate conditions. Future climate models showed a shift in the distribution of suitable habitat across a significant portion of the range; however, results also suggest that much of the Southeastern United States will be outside the range of current conditions, suggesting that there may be no-analog environments in the future. Most strikingly, future models were more effective than the current models at predicting recent records, suggesting that range shifts may already be occurring. These results have implications for both M. fulvius and its Batesian mimics. More broadly, we recommend future Maxent studies consider using future climate data along with current data to better estimate the current distribution.
An Update on the VAMOS Extremes Working Group Activities
NASA Technical Reports Server (NTRS)
Schubert, Siegfried; Cavalcanti, Iracema
2011-01-01
We review here the progress of the Variability of the American MOnsoon Systems (VAMOS) extremes working group since it was formed in February of 2010. The goals of the working group are to 1) develop an atlas of warm-season extremes over the Americas, 2) evaluate existing and planned simulations, and 3) suggest new model runs to address mechanisms and predictability of extremes. Substantial progress has been made in the development of an extremes atlas based on gridded observations and several reanalysis products including Modern Era Retrospective-Analysis for Research and Applications (MERRA) and Climate Forecast System Reanalysis (CFSR). The status of the atlas, remaining issues and plans for its expansion to include model data will be discussed. This includes the possibility of adding a companion atlas based on station observations based on the software developed under the World Climate Research Programme (WCRP) Expert Team on Climate Change. Detection and Indices (ETCCDI) activity. We will also review progress on relevant research and plans for the use and validation of the atlas results.
Influence of climate drivers on colonization and extinction dynamics of wetland-dependent species
Ray, Andrew M.; Gould, William R.; Hossack, Blake R.; Sepulveda, Adam; Thoma, David P.; Patla, Debra A.; Daley, Rob; Al-Chokhachy, Robert K.
2016-01-01
Freshwater wetlands are particularly vulnerable to climate change. Specifically, changes in temperature, precipitation, and evapotranspiration (i.e., climate drivers) are likely to alter flooding regimes of wetlands and affect the vital rates, abundance, and distributions of wetland-dependent species. Amphibians may be among the most climate-sensitive wetland-dependent groups, as many species rely on shallow or intermittently flooded wetland habitats for breeding. Here, we integrated multiple years of high-resolution gridded climate and amphibian monitoring data from Grand Teton and Yellowstone National Parks to explicitly model how variations in climate drivers and habitat conditions affect the occurrence and breeding dynamics (i.e., annual extinction and colonization rates) of amphibians. Our results showed that models incorporating climate drivers outperformed models of amphibian breeding dynamics that were exclusively habitat based. Moreover, climate-driven variation in extinction rates, but not colonization rates, disproportionately influenced amphibian occupancy in monitored wetlands. Long-term monitoring from national parks coupled with high-resolution climate data sets will be crucial to describing population dynamics and characterizing the sensitivity of amphibians and other wetland-dependent species to climate change. Further, long-term monitoring of wetlands in national parks will help reduce uncertainty surrounding wetland resources and strengthen opportunities to make informed, science-based decisions that have far-reaching benefits.
Importance of impacts scenarios for the adaptation of agriculture to climate change
NASA Astrophysics Data System (ADS)
Zullo, J.; Macedo, C.; Pinto, H. S.; Assad, E. D.; Koga Vicente, A.
2012-12-01
The great possibility that the climate is already changing, and the most drastic way possible, increases the challenge of agricultural engineering, especially in environmentally vulnerable areas and in regions where agriculture has a high economic and social importance. Knowledge of potential impacts that may be caused by changes in water and thermal regimes in coming decades is increasingly strategic, as they allow the development of techniques to adapt agriculture to climate change and therefore minimizes the risk of undesirable impacts, for example, in food and nutritional security. Thus, the main objective of this paper is to describe a way to generate impacts scenarios caused by anomalies of precipitation and temperature in the definition of climate risk zoning of an agricultural crop very important in the tropics, such as the sugar cane, especially in central-southern Brazil, which is one of its main world producers. A key point here is the choice of the climate model to be used, considering that 23 different models were used in the fourth IPCC report published in 2007. The number and range of available models requires the definition of criteria for choosing the most suitable for the preparation of the impacts scenarios. One way proposed and used in this work is based on the definition of two groups of models according to 27 technical attributes of them. The clustering of 23 models in two groups, with a model representing each group (UKMO_HadCM3 and MIROC3.2_medres), assists the generation and comparison of impacts scenarios, making them more representative and useful. Another important aspect in the generation of impacts scenarios is the estimate of the relative importance of the anomalies of precipitation and temperature, which are the most commonly used. To assess the relative importance of the anomalies are generated scenarios considering an anomaly at a time and both together. The impacts scenarios for a high emission of greenhouse gases (A2), from 2010 to 2039, were more drastic for the sugar cane in central-southern Brazil using the UKMO_HadCM3 model than the MIROC3.2_medres model. These impacts scenarios, however, were less drastic than those generated for the arabica coffee in the same simulation conditions, reinforcing the increased vulnerability of this agricultural crop to climate change than the sugar cane. The inclusion of other restrictions on the climate risk zoning improves the quality of the generated scenarios and expands its usefulness for agricultural engineering.
Capture mechanism in Palaeotropical pitcher plants (Nepenthaceae) is constrained by climate
Moran, Jonathan A.; Gray, Laura K.; Clarke, Charles; Chin, Lijin
2013-01-01
Background and Aims Nepenthes (Nepenthaceae, approx. 120 species) are carnivorous pitcher plants with a centre of diversity comprising the Philippines, Borneo, Sumatra and Sulawesi. Nepenthes pitchers use three main mechanisms for capturing prey: epicuticular waxes inside the pitcher; a wettable peristome (a collar-shaped structure around the opening); and viscoelastic fluid. Previous studies have provided evidence suggesting that the first mechanism may be more suited to seasonal climates, whereas the latter two might be more suited to perhumid environments. In this study, this idea was tested using climate envelope modelling. Methods A total of 94 species, comprising 1978 populations, were grouped by prey capture mechanism (large peristome, small peristome, waxy, waxless, viscoelastic, non-viscoelastic, ‘wet’ syndrome and ‘dry’ syndrome). Nineteen bioclimatic variables were used to model habitat suitability at approx. 1 km resolution for each group, using Maxent, a presence-only species distribution modelling program. Key Results Prey capture groups putatively associated with perhumid conditions (large peristome, waxless, viscoelastic and ‘wet’ syndrome) had more restricted areas of probable habitat suitability than those associated putatively with less humid conditions (small peristome, waxy, non-viscoelastic and‘dry’ syndrome). Overall, the viscoelastic group showed the most restricted area of modelled suitable habitat. Conclusions The current study is the first to demonstrate that the prey capture mechanism in a carnivorous plant is constrained by climate. Nepenthes species employing peristome-based and viscoelastic fluid-based capture are largely restricted to perhumid regions; in contrast, the wax-based mechanism allows successful capture in both perhumid and more seasonal areas. Possible reasons for the maintenance of peristome-based and viscoelastic fluid-based capture mechanisms in Nepenthes are discussed in relation to the costs and benefits associated with a given prey capture strategy. PMID:23975653
Capture mechanism in Palaeotropical pitcher plants (Nepenthaceae) is constrained by climate.
Moran, Jonathan A; Gray, Laura K; Clarke, Charles; Chin, Lijin
2013-11-01
Nepenthes (Nepenthaceae, approx. 120 species) are carnivorous pitcher plants with a centre of diversity comprising the Philippines, Borneo, Sumatra and Sulawesi. Nepenthes pitchers use three main mechanisms for capturing prey: epicuticular waxes inside the pitcher; a wettable peristome (a collar-shaped structure around the opening); and viscoelastic fluid. Previous studies have provided evidence suggesting that the first mechanism may be more suited to seasonal climates, whereas the latter two might be more suited to perhumid environments. In this study, this idea was tested using climate envelope modelling. A total of 94 species, comprising 1978 populations, were grouped by prey capture mechanism (large peristome, small peristome, waxy, waxless, viscoelastic, non-viscoelastic, 'wet' syndrome and 'dry' syndrome). Nineteen bioclimatic variables were used to model habitat suitability at approx. 1 km resolution for each group, using Maxent, a presence-only species distribution modelling program. Prey capture groups putatively associated with perhumid conditions (large peristome, waxless, viscoelastic and 'wet' syndrome) had more restricted areas of probable habitat suitability than those associated putatively with less humid conditions (small peristome, waxy, non-viscoelastic and'dry' syndrome). Overall, the viscoelastic group showed the most restricted area of modelled suitable habitat. The current study is the first to demonstrate that the prey capture mechanism in a carnivorous plant is constrained by climate. Nepenthes species employing peristome-based and viscoelastic fluid-based capture are largely restricted to perhumid regions; in contrast, the wax-based mechanism allows successful capture in both perhumid and more seasonal areas. Possible reasons for the maintenance of peristome-based and viscoelastic fluid-based capture mechanisms in Nepenthes are discussed in relation to the costs and benefits associated with a given prey capture strategy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pan, Y.
1993-01-01
Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less
Elevated temperature alters carbon cycling in a model microbial community
NASA Astrophysics Data System (ADS)
Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.
2013-12-01
Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.
Climate impacts on agricultural biomass production in the CORDEX.be project context
NASA Astrophysics Data System (ADS)
Gobin, Anne; Van Schaeybroeck, Bert; Termonia, Piet; Willems, Patrick; Van Lipzig, Nicole; Marbaix, Philippe; van Ypersele, Jean-Pascal; Fettweis, Xavier; De Ridder, Koen; Stavrakou, Trissevgeni; Luyten, Patrick; Pottiaux, Eric
2016-04-01
The most important coordinated international effort to translate the IPCC-AR5 outcomes to regional climate modelling is the so-called "COordinated Regional climate Downscaling EXperiment" (CORDEX, http://wcrp-cordex.ipsl.jussieu.fr/). CORDEX.be is a national initiative that aims at combining the Belgian climate and impact modelling research into a single network. The climate network structure is naturally imposed by the top-down data flow, from the four participating upper-air Regional Climate Modelling groups towards seven Local Impact Models (LIMs). In addition to the production of regional climate projections following the CORDEX guidelines, very high-resolution results are provided at convection-permitting resolutions of about 4 km across Belgium. These results are coupled to seven local-impact models with severity indices as output. A multi-model approach is taken that allows uncertainty estimation, a crucial aspect of climate projections for policy-making purposes. The down-scaled scenarios at 4 km resolution allow for impact assessment in different Belgian agro-ecological zones. Climate impacts on arable agriculture are quantified using REGCROP which is a regional dynamic agri-meteorological model geared towards modelling climate impact on biomass production of arable crops (Gobin, 2010, 2012). Results from previous work show that heat stress and water shortages lead to reduced crop growth, whereas increased CO2-concentrations and a prolonged growing season have a positive effect on crop yields. The interaction between these effects depend on the crop type and the field conditions. Root crops such as potato will experience increased drought stress particularly when the probability rises that sensitive crop stages coincide with dry spells. This may be aggravated when wet springs cause water logging in the field and delay planting dates. Despite lower summer precipitation projections for future climate in Belgium, winter cereal yield reductions due to drought stress will be smaller due to earlier maturity. Preliminary results will be presented using the new scenario runs for Belgium.
Thorne, James; Boynton, Ryan; Flint, Lorraine; Flint, Alan; N'goc Le, Thuy
2012-01-01
This paper outlines the production of 270-meter grid-scale maps for 14 climate and derivative hydrologic variables for a region that encompasses the State of California and all the streams that flow into it. The paper describes the Basin Characterization Model (BCM), a map-based, mechanistic model used to process the hydrological variables. Three historic and three future time periods of 30 years (1911–1940, 1941–1970, 1971–2000, 2010–2039, 2040–2069, and 2070–2099) were developed that summarize 180 years of monthly historic and future climate values. These comprise a standardized set of fine-scale climate data that were shared with 14 research groups, including the U.S. National Park Service and several University of California groups as part of this project. We present three analyses done with the outputs from the Basin Characterization Model: trends in hydrologic variables over baseline, the most recent 30-year period; a calibration and validation effort that uses measured discharge values from 139 streamgages and compares those to Basin Characterization Model-derived projections of discharge for the same basins; and an assessment of the trends of specific hydrological variables that links historical trend to projected future change under four future climate projections. Overall, increases in potential evapotranspiration dominate other influences in future hydrologic cycles. Increased potential evapotranspiration drives decreasing runoff even under forecasts with increased precipitation, and drives increased climatic water deficit, which may lead to conversion of dominant vegetation types across large parts of the study region as well as have implications for rain-fed agriculture. The potential evapotranspiration is driven by air temperatures, and the Basin Characterization Model permits it to be integrated with a water balance model that can be derived for landscapes and summarized by watershed. These results show the utility of using a process-based model with modules representing different hydrological pathways that can be inter-linked.
The climate4impact platform: Providing, tailoring and facilitating climate model data access
NASA Astrophysics Data System (ADS)
Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael
2017-04-01
One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European contribution to ESGF and contributes to the ESGF open source effort, notably through the development of search, monitoring, quality control, and metadata services. In its second phase, IS-ENES2 supports the implementation of regional climate model results from the international Coordinated Regional Downscaling Experiments (CORDEX). These services were extended within the European FP7 Climate Information Portal for Copernicus (CLIPC) project, and some could be later integrated into the European Copernicus platform.
Chen, Zhijun; Zhu, Jing; Zhou, Mingjian
2015-03-01
Building on a social identity framework, our cross-level process model explains how a manager's servant leadership affects frontline employees' service performance, measured as service quality, customer-focused citizenship behavior, and customer-oriented prosocial behavior. Among a sample of 238 hairstylists in 30 salons and 470 of their customers, we found that hair stylists' self-identity embedded in the group, namely, self-efficacy and group identification, partially mediated the positive effect of salon managers' servant leadership on stylists' service performance as rated by the customers, after taking into account the positive influence of transformational leadership. Moreover, group competition climate strengthened the positive relationship between self-efficacy and service performance. PsycINFO Database Record (c) 2015 APA, all rights reserved.
NASA Astrophysics Data System (ADS)
Rogers, M. J. B.; Petrone, C.; Merrick, B. A.; Drewes, A.
2017-12-01
The current shift in K-12 science education is towards a teaching and learning approach in which students actively do and experience science in a deep, meaningful way while being fully active in their learning. For students and teachers who have not experienced this approach, this shift is difficult without scaffolding. Professional learning for educators must allow teachers to experience this approach and reflect on their experience. We share an example from our 2017 K-12 Climate Change Academy in which educators created and modified murals of Earth's climate system while investigating ecosystem interactions, the carbon cycle, energy flow, and human impacts. The Academy constituted an online component followed by three consecutive in person days. The mural activity served as a framework. The first mural modeling occurred online. A1: Take a photo of an outdoor landscape. Annotate it with elements of Earth's atmosphere, biosphere, geosphere, hydrosphere and indicate energy flow, carbon cycling, and the processes driving these. Activities 2-6 were employed throughout the in person days. A2: Small groups create 2D, mural sized models of Earth's climate system. A3: Groups use carbon themed cards to document naturally occurring and human-influenced aspects of the carbon cycle on their models. A4-5: Teams add climate change impacts and possible mitigation/adaptation responses to murals. A6: Ongoing throughout, team members modify models as needed based on learning. Throughout the Academy, participants were able to experience the activities as students. As Academy facilitators, we modeled how educators could use these models in their classrooms. We used A1 submissions as a formative assessment tool and also as a guide for forming groups for the first in person mural. A2 was used as a small group icebreaker, serving as a bridge between the online and in person sessions both for community building and for providing peer support in knowledge building. A3-A5 allowed for reflection upon and meaning making from other activities. At set stopping points, participants changed roles to discuss the 3D NGSS elements they experienced and think about how each activity could be used in their classroom. We will share best practices from these activities, how they can be adapted for other uses, and Academy participants' reflections.
van der Zwaan, Bob; Calvin, Katherine V.; Clarke, Leon E.
2016-05-01
The CLIMACAP-LAMP project, completed in December 2015, was an inter-model comparison exercise that focused on energy and climate change economics issues in Latin America. The project partners – co-financed by the EC / EuropeAid (CLIMACAP part) and EPA / USAID (LAMP part) and co-coordinated by respectively the Energy research Centre of the Netherlands (ECN) and the Pacific Northwest National Laboratory (PNNL) – report their main and detailed findings in this Special Issue of Energy Economics, exclusively dedicated to climate mitigation, low-carbon development and implications for energy and land use in Latin America. Our research endeavor included several of the mostmore » prominent regional energy modeling groups from Latin America, as well as a representative set of global integrated assessment modeling groups from a number of institutions from Europe and the US. About two dozen universities, research groups and environmental or consulting organizations took part in the CLIMACAP-LAMP cross-model comparison project, from both sides of the Atlantic. Over a handful of workshops were organized over the past four years in several countries in Latin America, attended by between 30 and 50 participants from, amongst others, Argentina, Brazil, Colombia, Mexico, the EU, and the US.« less
Enting, I. G.; Wigley, M. L.; Heimann, M.
1995-01-01
This database contains the results of various projections of the relation between future CO2 concentrations and future industrial emissions. These projections were contributed by groups from a number of countries as part of the scientific assessment for the report, "Radiative Forcing of Climate Change" (1994), issued by Working Group 1 of the Intergovernmental Panel on Climate Change. There were three types of calculations: (1) forward projections, calculating the atmospheric CO2 concentrations resulting from specified emissions scenarios; (2) inverse calculations, determining the emission rates that would be required to achieve stabilization of CO2 concentrations via specified pathways; (3) impulse response function calculations, required for determining Global Warming Potentials. The projections were extrapolations of global carbon cycle models from pre-industrial times (starting at 1765) to 2100 or 2200 A.D. There were two aspects to the exercise: (1) an assessment of the uncertainty due to uncertainties regarding the current carbon budget, and (2) an assessment of the uncertainties arising from differences between models. To separate these effects, a set of standard conditions was used to explore inter-model differences and then a series of sensitivity studies was used to explore the consequences of current uncertainties in the carbon cycle.
The Prodiguer Messaging Platform
NASA Astrophysics Data System (ADS)
Denvil, S.; Greenslade, M. A.; Carenton, N.; Levavasseur, G.; Raciazek, J.
2015-12-01
CONVERGENCE is a French multi-partner national project designed to gather HPC and informatics expertise to innovate in the context of running French global climate models with differing grids and at differing resolutions. Efficient and reliable execution of these models and the management and dissemination of model output are some of the complexities that CONVERGENCE aims to resolve.At any one moment in time, researchers affiliated with the Institut Pierre Simon Laplace (IPSL) climate modeling group, are running hundreds of global climate simulations. These simulations execute upon a heterogeneous set of French High Performance Computing (HPC) environments. The IPSL's simulation execution runtime libIGCM (library for IPSL Global Climate Modeling group) has recently been enhanced so as to support hitherto impossible realtime use cases such as simulation monitoring, data publication, metrics collection, simulation control, visualizations … etc. At the core of this enhancement is Prodiguer: an AMQP (Advanced Message Queue Protocol) based event driven asynchronous distributed messaging platform. libIGCM now dispatches copious amounts of information, in the form of messages, to the platform for remote processing by Prodiguer software agents at IPSL servers in Paris. Such processing takes several forms: Persisting message content to database(s); Launching rollback jobs upon simulation failure; Notifying downstream applications; Automation of visualization pipelines; We will describe and/or demonstrate the platform's: Technical implementation; Inherent ease of scalability; Inherent adaptiveness in respect to supervising simulations; Web portal receiving simulation notifications in realtime.
Physical-Socio-Economic Modeling of Climate Change
NASA Astrophysics Data System (ADS)
Chamberlain, R. G.; Vatan, F.
2008-12-01
Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media/information operations model. Each of these models focuses on part of the overall picture while; each contributes information about its area of expertise to a common pool and draws from that pool and the feedbacks from the other models as needed. Existing high-quality physical models are based on analysis of the dynamic interactions of atmospheric, land, and ocean processes. The demographic model tracks the civilian demographics needed by the other models. The populations of neighborhood group age-gender cohorts are affected by births, deaths, aging, and migration. This model provides labor supply and product demand curves to the economic model. The political model focuses on political actors and describes how they use their clout to seek their goals. Clout is derived from civilian support, the formal and informal alliances that actors make with each other, military strength, wealth, and control of information. It considers how they are constrained by their cultural heritage. It deals with shifting alliances. The economic model determines local and international prices and production quantities for a small number of products, including imports and exports and black markets; wages, jobs, and unemployment for a small number of labor categories; capital, growth, and inflation; resource usage and pollution. The media/information operations model addresses the effects of the control and content of inter- group and intra-group communications-and the side effects of these on other groups. This model will consist of rules (probably a large number of them) detailing the effects of media/information operations of various kinds on civilian parameters used in the other models, such as political goals, concern saliencies, and shapes of supply and demand curves.
Liao, Hui; Rupp, Deborah E
2005-03-01
In this article, which takes a person-situation approach, the authors propose and test a cross-level multifoci model of workplace justice. They crossed 3 types of justice (procedural, informational, and interpersonal) with 2 foci (organization and supervisor) and aggregated to the group level to create 6 distinct justice climate variables. They then tested for the effects of these variables on either organization-directed or supervisor-directed commitment, satisfaction, and citizenship behavior. The authors also tested justice orientation as a moderator of these relationships. The results, based on 231 employees constituting 44 work groups representing multiple organizations and occupations, revealed that 4 forms of justice climate (organization-focused procedural and informational justice climate and supervisor-focused procedural and interpersonal justice climate) were significantly related to various work outcomes after controlling for corresponding individual-level justice perceptions. In addition, some moderation effects were found. Implications for organizations and future research are discussed.
Jaakkola, T; Ntoumanis, N; Liukkonen, J
2016-01-01
The aim of this study was to investigate the relations among situational motivational climate, dispositional approach and avoidance achievement goals, perceived sport ability, and enjoyment in Finnish male junior ice hockey players. The sample comprised 265 junior B-level male players with a mean age of 17.03 years (SD = 0.63). Players filled questionnaires tapping their perceptions of coach motivational climate, achievement goals, perceived sport ability, and enjoyment. For the statistical analysis, players were divided into high and low perceived sport ability groups. Multigroup structural equation modeling (SEM) revealed an indirect path from task-involving motivational climate via task-approach goal to enjoyment. Additionally, SEM demonstrated four other direct associations, which existed in both perceived ability groups: from ego-involving motivational climate to ego-approach and ego-avoidance goals; from ego-approach goal to ego-avoidance goal; and from task-avoidance goal to ego-avoidance goal. Additionally, in the high perceived sport ability group, there was an association from task-involving motivational climate to enjoyment. The results of this study reveal that motivational climate emphasizing effort, personal development and improvement, and achievement goal mastering tasks are significant elements of enjoyment in junior ice hockey. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Changes in U.S. Regional-Scale Air Quality at 2030 Simulated Using RCP 6.0
NASA Astrophysics Data System (ADS)
Nolte, C. G.; Otte, T.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.
2012-12-01
Recent improvements in air quality in the United States have been due to significant reductions in emissions of ozone and particulate matter (PM) precursors, and these downward emissions trends are expected to continue in the next few decades. To ensure that planned air quality regulations are robust under a range of possible future climates and to consider possible policy actions to mitigate climate change, it is important to characterize and understand the effects of climate change on air quality. Recent work by several research groups using global and regional models has demonstrated that there is a "climate penalty," in which climate change leads to increases in surface ozone levels in polluted continental regions. One approach to simulating future air quality at the regional scale is via dynamical downscaling, in which fields from a global climate model are used as input for a regional climate model, and these regional climate data are subsequently used for chemical transport modeling. However, recent studies using this approach have encountered problems with the downscaled regional climate fields, including unrealistic surface temperatures and misrepresentation of synoptic pressure patterns such as the Bermuda High. We developed a downscaling methodology and showed that it now reasonably simulates regional climate by evaluating it against historical data. In this work, regional climate simulations created by downscaling the NASA/GISS Model E2 global climate model are used as input for the Community Multiscale Air Quality (CMAQ) model. CMAQ simulations over the continental United States are conducted for two 11-year time slices, one representing current climate (1995-2005) and one following Representative Concentration Pathway 6.0 from 2025-2035. Anthropogenic emissions of ozone and PM precursors are held constant at year 2006 levels for both the current and future periods. In our presentation, we will examine the changes in ozone and PM concentrations, with particular focus on exceedances of the current U.S. air quality standards, and attempt to relate the changes in air quality to the projected changes in regional climate.
Konowalik, Kamil
2017-01-01
In the present study we investigate the concept of phylogenetic niche conservatism (PNC) within the American species of angraecoid orchids (Campylocentrum and Dendrophylax) and their closest relatives in the Old World (Angraecum) using ecological niche modelling (ENM). The predicted niche occupancy profiles were matched with the outcomes of previous phylogenetic studies to reconstruct the evolution of climatic suitability within the orchid group studied and evaluate the role of niche differentiation in the speciation of Angraecinae. No correlation between preferred niches and taxonomic relationships within the orchid group studied was revealed. The climatic suitability of the majority of the species overlapped each other, either fully or partially. This pattern is also present in the species of other orchid genera. Our research confirms a significant level of PNC in Orchidaceae, even within taxa exhibiting a transatlantic disjunction. The analysis of the evolution of climatic suitability indicated that the adaptation to various climatic conditions is not a factor that has driven speciation within orchids studied. PMID:28533976
Kolanowska, Marta; Grochocka, Elżbieta; Konowalik, Kamil
2017-01-01
In the present study we investigate the concept of phylogenetic niche conservatism (PNC) within the American species of angraecoid orchids ( Campylocentrum and Dendrophylax ) and their closest relatives in the Old World ( Angraecum ) using ecological niche modelling (ENM). The predicted niche occupancy profiles were matched with the outcomes of previous phylogenetic studies to reconstruct the evolution of climatic suitability within the orchid group studied and evaluate the role of niche differentiation in the speciation of Angraecinae. No correlation between preferred niches and taxonomic relationships within the orchid group studied was revealed. The climatic suitability of the majority of the species overlapped each other, either fully or partially. This pattern is also present in the species of other orchid genera. Our research confirms a significant level of PNC in Orchidaceae, even within taxa exhibiting a transatlantic disjunction. The analysis of the evolution of climatic suitability indicated that the adaptation to various climatic conditions is not a factor that has driven speciation within orchids studied.
NASA Astrophysics Data System (ADS)
McGuire, A. D.
2016-12-01
The Model Integration Group of the Permafrost Carbon Network (see http://www.permafrostcarbon.org/) has conducted studies to evaluate the sensitivity of offline terrestrial permafrost and carbon models to both historical and projected climate change. These studies indicate that there is a wide range of (1) initial states permafrost extend and carbon stocks simulated by these models and (2) responses of permafrost extent and carbon stocks to both historical and projected climate change. In this study, we synthesize what has been learned about the variability in initial states among models and the driving factors that contribute to variability in the sensitivity of responses. We conclude the talk with a discussion of efforts needed by (1) the modeling community to standardize structural representation of permafrost and carbon dynamics among models that are used to evaluate the permafrost carbon feedback and (2) the modeling and observational communities to jointly develop data sets and methodologies to more effectively benchmark models.
Bansal, Sheel; Sheley, Roger L.
2016-01-01
The invasion by winter-annual grasses (AGs) such as Bromus tectorum into sagebrush steppe throughout the western USA is a classic example of a biological invasion with multiple, interacting climate, soil and biotic factors driving the invasion, although few studies have examined all components together. Across a 6000-km2 area of the northern Great Basin, we conducted a field assessment of 100 climate, soil, and biotic (functional group abundances, diversity) factors at each of 90 sites that spanned an invasion gradient ranging from 0 to 100 % AG cover. We first determined which biotic and abiotic factors had the strongest correlative relationships with AGs and each resident functional group. We then used regression and structural equation modeling to explore how multiple ecological factors interact to influence AG abundance. Among biotic interactions, we observed negative relationships between AGs and biodiversity, perennial grass cover, resident species richness, biological soil crust cover and shrub density, whereas perennial and annual forb cover, tree cover and soil microbial biomass had no direct linkage to AG. Among abiotic factors, AG cover was strongly related to climate (increasing cover with increasing temperature and aridity), but had weak relationships with soil factors. Our structural equation model showed negative effects of perennial grasses and biodiversity on AG cover while integrating the negative effects of warmer climate and positive influence of belowground processes on resident functional groups. Our findings illustrate the relative importance of biotic interactions and climate on invasive abundance, while soil properties appear to have stronger relationships with resident biota than with invasives.
Using Paleo-climate Comparisons to Constrain Future Projections in CMIP5
NASA Technical Reports Server (NTRS)
Schmidt, G. A.; Annan, J D.; Bartlein, P. J.; Cook, B. I.; Guilyardi, E.; Hargreaves, J. C.; Harrison, S. P.; Kageyama, M.; LeGrande, A. N..; Konecky, B.;
2013-01-01
We present a description of the theoretical framework and best practice for using the paleo-climate model component of the Coupled Model Intercomparison Project (Phase 5) (CMIP5) to constrain future projections of climate using the same models. The constraints arise from measures of skill in hindcasting paleo-climate changes from the present over 3 periods: the Last Glacial Maximum (LGM) (21 thousand years before present, ka), the mid-Holocene (MH) (6 ka) and the Last Millennium (LM) (8501850 CE). The skill measures may be used to validate robust patterns of climate change across scenarios or to distinguish between models that have differing outcomes in future scenarios. We find that the multi-model ensemble of paleo-simulations is adequate for addressing at least some of these issues. For example, selected benchmarks for the LGM and MH are correlated to the rank of future projections of precipitationtemperature or sea ice extent to indicate that models that produce the best agreement with paleoclimate information give demonstrably different future results than the rest of the models. We also find that some comparisons, for instance associated with model variability, are strongly dependent on uncertain forcing timeseries, or show time dependent behaviour, making direct inferences for the future problematic. Overall, we demonstrate that there is a strong potential for the paleo-climate simulations to help inform the future projections and urge all the modeling groups to complete this subset of the CMIP5 runs.
EVALUATING SHORT-TERM CLIMATE VARIABILITY IN THE LATE HOLOCENE OF THE NORTHERN GREAT PLAINS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Joseph H. Hartman
1999-09-01
This literature study investigated methods and areas to deduce climate change and climate patterns, looking for short-term cycle phenomena and the means to interpret them. Many groups are actively engaged in intensive climate-related research. Ongoing research might be (overly) simplified into three categories: (1) historic data on weather that can be used for trend analysis and modeling; (2) detailed geological, biological (subfossil), and analytical (geochemical, radiocarbon, etc.) studies covering the last 10,000 years (about since last glaciation); and (3) geological, paleontological, and analytical (geochemical, radiometric, etc.) studies over millions of years. Of importance is our ultimate ability to join thesemore » various lines of inquiry into an effective means of interpretation. At this point, the process of integration is fraught with methodological troubles and misconceptions about what each group can contribute. This project has met its goals to the extent that it provided an opportunity to study resource materials and consider options for future effort toward the goal of understanding the natural climate variation that has shaped our current civilization. A further outcome of this project is a proposed methodology based on ''climate sections'' that provides spatial and temporal correlation within a region. The method would integrate cultural and climate data to establish the climate history of a region with increasing accuracy with progressive study and scientific advancement (e. g., better integration of regional and global models). The goal of this project is to better understand natural climatic variations in the recent past (last 5000 years). The information generated by this work is intended to provide better context within which to examine global climate change. The ongoing project will help to establish a basis upon which to interpret late Holocene short-term climate variability as evidenced in various studies in the northern Great Plains, northern hemisphere, and elsewhere. Finally these data can be integrated into a history of climate change and predictive climate models. This is not a small undertaking. The goals of researchers and the methods used vary considerably. The primary task of this project was literature research to (1) evaluate existing methodologies used in geologic climate change studies and evidence for short-term cycles produced by these methodologies and (2) evaluate late Holocene climate patterns and their interpretations.« less
NASA Astrophysics Data System (ADS)
Goodman, A.; Lee, H.; Waliser, D. E.; Guttowski, W.
2017-12-01
Observation-based evaluations of global climate models (GCMs) have been a key element for identifying systematic model biases that can be targeted for model improvements and for establishing uncertainty associated with projections of global climate change. However, GCMs are limited in their ability to represent physical phenomena which occur on smaller, regional scales, including many types of extreme weather events. In order to help facilitate projections in changes of such phenomena, simulations from regional climate models (RCMs) for 14 different domains around the world are being provided by the Coordinated Regional Climate Downscaling Experiment (CORDEX; www.cordex.org). However, although CORDEX specifies standard simulation and archiving protocols, these simulations are conducted independently by individual research and modeling groups representing each of these domains often with different output requirements and data archiving and exchange capabilities. Thus, with respect to similar efforts using GCMs (e.g., the Coupled Model Intercomparison Project, CMIP), it is more difficult to achieve a standardized, systematic evaluation of the RCMs for each domain and across all the CORDEX domains. Using the Regional Climate Model Evaluation System (RCMES; rcmes.jpl.nasa.gov) developed at JPL, we are developing easy to use templates for performing systematic evaluations of CORDEX simulations. Results from the application of a number of evaluation metrics (e.g., biases, centered RMS, and pattern correlations) will be shown for a variety of physical quantities and CORDEX domains. These evaluations are performed using products from obs4MIPs, an activity initiated by DOE and NASA, and now shepherded by the World Climate Research Program's Data Advisory Council.
NASA Astrophysics Data System (ADS)
Jayasankar, C. B.; Surendran, Sajani; Rajendran, Kavirajan
2015-05-01
Coupled Model Intercomparison Project phase 5 (Fifth Assessment Report of Intergovernmental Panel on Climate Change) coupled global climate model Representative Concentration Pathway 8.5 simulations are analyzed to derive robust signals of projected changes in Indian summer monsoon rainfall (ISMR) and its variability. Models project clear future temperature increase but diverse changes in ISMR with substantial intermodel spread. Objective measures of interannual variability (IAV) yields nearly equal chance for future increase or decrease. This leads to discrepancy in quantifying changes in ISMR and variability. However, based primarily on the physical association between mean changes in ISMR and its IAV, and objective methods such as k-means clustering with Dunn's validity index, mean seasonal cycle, and reliability ensemble averaging, projections fall into distinct groups. Physically consistent groups of models with the highest reliability project future reduction in the frequency of light rainfall but increase in high to extreme rainfall and thereby future increase in ISMR by 0.74 ± 0.36 mm d-1, along with increased future IAV. These robust estimates of future changes are important for useful impact assessments.
Interannual Variation in Phytoplankton Primary Production at a Global Scale
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile Severine; Gregg, Watson W.
2013-01-01
We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on group-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.
NASA Astrophysics Data System (ADS)
Rasmussen, R.; Ikeda, K.; Liu, C.; Gochis, D.; Chen, F.; Barlage, M. J.; Dai, A.; Dudhia, J.; Clark, M. P.; Gutmann, E. D.; Li, Y.
2015-12-01
The NCAR Water System program strives to improve the full representation of the water cycle in both regional and global models. Our previous high-resolution simulations using the WRF model over the Rocky Mountains revealed that proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing (< 6 km horizontal) and parameterizations. The climate sensitivity experiment consistent with expected climate change showed an altered hydrological cycle with increased fraction of rain versus snow, increased snowfall at high altitudes, earlier melting of snowpack, and decreased total runoff. In order to investigate regional differences between the Rockies and other major mountain barriers and to study climate change impacts over other regions of the contiguous U.S. (CONUS), we have expanded our prior CO Headwaters modeling study to encompass most of North America at a horizontal grid spacing of 4 km. A domain expansion provides the opportunity to assess changes in orographic precipitation across different mountain ranges in the western USA, as well as the very dominant role of convection in the eastern half of the USA. The high resolution WRF-downscaled climate change data will also become a valuable community resource for many university groups who are interested in studying regional climate changes and impacts but unable to perform such long-duration and high-resolution WRF-based downscaling simulations of their own. The scientific goals and details of the model dataset will be presented including some preliminary results.
Socio-Economic Vulnerability to Climate Change in California
NASA Astrophysics Data System (ADS)
Heberger, M. G.; Cooley, H.; Moore, E.; Garzon, C.
2011-12-01
The western United States faces a range of impacts from global climate change, including increases in extreme heat, wildfires, and coastal flooding and erosion; changes are also likely to occur in air quality, water availability, and the spread of infectious diseases. To date, a great deal of research has been done to forecast the physical effects of climate change, while less attention has been given to the factors make different populations more or less vulnerable to harm from such changes. For example, mortality rates from Hurricane Audrey, which struck the coast of Louisiana in 1957, were more than eight times higher among blacks than among whites. While disaster events may not discriminate, impacts on human populations are shaped by "intervening conditions" that determine the human impact of the flood and the specific needs for preparedness, response, and recovery. In this study, we analyze the potential impacts of climate change by using recent downscaled climate model outputs, creating a variety of statistics and visualizations to communicate potential impacts to community groups and decision makers, after several meetings with these groups to ask, "What types of information are most useful to you for planning?" We relate climate impacts to social vulnerability - defined as the intersection of the exposure, sensitivity, and adaptive capacity of a person or group of people - with a focus on the U.S. state of California. Understanding vulnerability factors and the populations that exhibit these factors are critical for crafting effective climate change policies and response strategies. It is also important to the emerging study of climate justice, which is the concept that no group of people should disproportionately bear the burden of climate impacts or the costs of mitigation and adaptation.
Uncertainty quantification of US Southwest climate from IPCC projections.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boslough, Mark Bruce Elrick
2011-01-01
The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statisticalmore » analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.« less
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; ...
2016-09-28
Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. Here, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide rangemore » of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. Furthermore, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. In order to serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.« less
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
DOE Office of Scientific and Technical Information (OSTI.GOV)
O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.
2016-01-01
Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate amore » wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.« less
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
NASA Astrophysics Data System (ADS)
O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; Eyring, Veronika; Friedlingstein, Pierre; Hurtt, George; Knutti, Reto; Kriegler, Elmar; Lamarque, Jean-Francois; Lowe, Jason; Meehl, Gerald A.; Moss, Richard; Riahi, Keywan; Sanderson, Benjamin M.
2016-09-01
Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017-2018 time frame, and output from the climate model projections made available and analyses performed over the 2018-2020 period.
The Effect of Diversity Climate Perception on Alienation of Students to University
ERIC Educational Resources Information Center
Kurtulmus, Mehmet
2016-01-01
The aim of this research is to examine the effect of diversity climate perception on alienation of students to university. The research was carried out with relational survey model. 333 undergraduate students in Faculty of Education, Medical, and Faculty of Theology of Dicle University constituted the participant group. Research data were…
NASA Astrophysics Data System (ADS)
Alexander, K.; Easterbrook, S. M.
2015-01-01
We analyse the source code of eight coupled climate models, selected from those that participated in the CMIP5 (Taylor et al., 2012) or EMICAR5 (Eby et al., 2013; Zickfeld et al., 2013) intercomparison projects. For each model, we sort the preprocessed code into components and subcomponents based on dependency structure. We then create software architecture diagrams which show the relative sizes of these components/subcomponents and the flow of data between them. The diagrams also illustrate several major classes of climate model design; the distribution of complexity between components, which depends on historical development paths as well as the conscious goals of each institution; and the sharing of components between different modelling groups. These diagrams offer insights into the similarities and differences between models, and have the potential to be useful tools for communication between scientists, scientific institutions, and the public.
Global warming, energy use, and economic growth
NASA Astrophysics Data System (ADS)
Khanna, Neha
The dissertation comprises four papers that explore the interactions between global warming, energy use, and economic growth. While the papers are separate entities, they share the underlying theme of highlighting national differences in the growth experience and their implications for long-term energy use and climate change. The first paper provides an overview of some key economic issues in the climate change literature. In doing so, the paper critically appraises the 1995 draft report of Working Group III of the Intergovernmental Panel on Climate Change. The focus is the choice of a pure rate of time preference in the economic modeling of climate change, abatement costs differentials between developed and developing countries, and contrasting implications of standard discount rates and value of life estimates for these two country groups. The second paper develops a global model that takes account of the depletion of oil resources in the context of a geo-economic model for climate change. It is found that in the presence of non-decreasing carbon and energy intensities and declining petroleum availability, the carbon emissions trajectory is much higher than that typically projected by other models of this genre. Furthermore, by introducing price and income sensitive demand functions for fossil fuels, the model provides a framework to assess the effectiveness of fuel specific carbon taxes in reducing the COsb2 emissions trajectory. Cross-price substitution effects necessitate unrealistically high tax rates in order to lower the projected emissions trajectory to the optimal level. The economic structure of five integrated assessment models for climate change is reviewed in the third paper, with a special focus on the macroeconomic and damage assessment modules. The final paper undertakes an econometric estimation of the changing shares of capital, labour, energy, and technical change in explaining the growth patterns of 38 countries. Production elasticities vary by country group and also in response to the levels of factor use. It is found that classifying countries according to the GDP growth rate yields statistically different slope coefficients. Using the estimated translog production function, the capital and labour requirements of reductions in energy use are approximated. Analytical expressions for the elasticity of energy intensity with respect to factor inputs and also autonomous energy efficiency improvements are provided.
NASA Astrophysics Data System (ADS)
Sobie, S. R.; Murdock, T. Q.
2016-12-01
Infrastructure vulnerability assessments and adaptation planning have created demand for detailed information about climate change and extreme events from local and regional governments. Individual communities often have distinct priorities regarding climate change impacts. While projections from climate models are available to investigate these impacts, they are not always applicable or easily interpreted by local agencies. We discuss a series of climate impacts assessments for several regional and local governments in southwestern British Columbia. Each of the assessments was conducted with input from the users on project definition from the start of the process and on interpretation of results throughout each project. To produce sufficient detail for the assessment regions, we produce high-resolution (800m) simulations of precipitation and temperature using downscaled climate model projections. Sets of derived climate parameters tailored to each region are calculated from both standard indices such as CLIMDEX and from an energy-balance snowpack model. Involving user groups from the beginning of the analysis helps to convey the meaning and confidence of each set of climate change parameters to users and also clarifies what projections are feasible or not for impact assessments. We discuss the different levels of involvement and collaboration with each organization, and the resulting decisions implemented following each of the projects.
NASA Astrophysics Data System (ADS)
Lintner, B. R.; Loikith, P. C.; Pike, M.; Aragon, C.
2017-12-01
Climate change information is increasingly required at impact-relevant scales. However, most state-of-the-art climate models are not of sufficiently high spatial resolution to resolve features explicitly at such scales. This challenge is particularly acute in regions of complex topography, such as the Pacific Northwest of the United States. To address this scale mismatch problem, we consider large-scale meteorological patterns (LSMPs), which can be resolved by climate models and associated with the occurrence of local scale climate and climate extremes. In prior work, using self-organizing maps (SOMs), we computed LSMPs over the northwestern United States (NWUS) from daily reanalysis circulation fields and further related these to the occurrence of observed extreme temperatures and precipitation: SOMs were used to group LSMPs into 12 nodes or clusters spanning the continuum of synoptic variability over the regions. Here this observational foundation is utilized as an evaluation target for a suite of global climate models from the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Evaluation is performed in two primary ways. First, daily model circulation fields are assigned to one of the 12 reanalysis nodes based on minimization of the mean square error. From this, a bulk model skill score is computed measuring the similarity between the model and reanalysis nodes. Next, SOMs are applied directly to the model output and compared to the nodes obtained from reanalysis. Results reveal that many of the models have LSMPs analogous to the reanalysis, suggesting that the models reasonably capture observed daily synoptic states.
The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models
NASA Astrophysics Data System (ADS)
Yang, Z.
2011-12-01
I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.
Climate Change Concepts and POGIL: Using climate change to teach general chemistry
NASA Astrophysics Data System (ADS)
King, D. B.; Lewis, J. E.; Anderson, K.; Latch, D.; Sutheimer, S.; Webster, G.; Middlecamp, C.; Moog, R.
2013-12-01
Climate change is a topic that can be used to engage students in a variety of courses and disciplines. Through an NSF-funded project, we have written a set of in-class POGIL (Process Oriented Guided Inquiry Learning) activities that use climate change topics to teach general chemistry concepts. POGIL is a pedagogical approach that uses group activities to teach content and process skills. In these group activities an initial model and a series of critical thinking questions are used to guide students through the introduction to or application of course content. Students complete the activities on their own, with the faculty member as a facilitator of learning, rather than a provider of information. Through assigned group roles and intentionally designed activity structure, process skills, such as teamwork, communication, and information processing, are developed during completion of the activity. While POGIL activities were initially developed for chemistry courses, this approach has now been used to create materials for use in other fields, such as biology, math, engineering and computer science. An additional component of this project is the incorporation of questions that relate to socio-scientific issues, e.g., the economic and social effects of climate change policies. The goal is for students to use evidence-based arguments in situations where opinion-based arguments are common. Key components (i.e., models and the corresponding critical thinking questions) of one activity will be presented. We will also report preliminary feedback based on initial classroom testing of several of the activities.
Global Mean Temperature Timeseries Projections from GCMs: The Implications of Rebasing
NASA Astrophysics Data System (ADS)
Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.
2017-12-01
Global climate models are assessed by comparison with observations through several benchmarks. One highlighted by the InterGovernmental Panel on Climate Change (IPCC) is their ability to reproduce "general features of the global and annual mean surface temperature changes over the historical period" [1,2] and to simulate "a trend in global-mean surface temperature from 1951 to 2012 that agrees with the observed trend" [3]. These aspects of annual mean global mean temperature (GMT) change are presented as one feature demonstrating the relevance of these models for climate projections. Here we consider a formal interpretation of "general features" and discuss the implications of this approach to model assessment and intercomparison, for the interpretation of GCM projections. Following the IPCC, we interpret a major element of "general features" as being the slow timescale response to external forcings. (Shorter timescale behaviour such as the response to volcanic eruptions are also elements of "general features" but are not considered here.) Also following the IPCC, we consider only GMT anomalies. The models have absolute temperatures which range over about 3K so this means their timeseries (and the observations) are rebased. We show that rebasing in combination with general agreement, implies a separation of scales which limits the degree to which sub-global behaviour can feedback on the global response. It also implies a degree of linearity in the GMT slow timescale response. For each individual model these implications only apply over the range of absolute temperatures simulated by the model in historic simulations. Taken together, however, they imply consequences over a wider range of GMTs. [1] IPCC, Fifth Assessment Report, Working Group 1, Technical Summary: Stocker et al. 2013. [2] IPCC, Fifth Assessment Report, Working Group 1, Chapter 9 - "Evaluation of Climate Models": Flato et al. 2013. [3] IPCC, Fifth Assessment Report, Working Group 1, Summary for Policy Makers: IPCC, 2013.
NASA Astrophysics Data System (ADS)
Lee, Lindsay; Mann, Graham; Carslaw, Ken; Toohey, Matthew; Aquila, Valentina
2016-04-01
The World Climate Research Program's SPARC initiative has a new international activity "Stratospheric Sulphur and its Role in Climate" (SSiRC) to better understand changes in stratospheric aerosol and precursor gaseous sulphur species. One component of SSiRC involves an intercomparison "ISA-MIP" of composition-climate models that simulate the stratospheric aerosol layer interactively. Within PoEMS each modelling group will run a "perturbed physics ensemble" (PPE) of interactive stratospheric aerosol (ISA) simulations of the Pinatubo eruption, varying several uncertain parameters associated with the eruption's SO2 emissions and model processes. A powerful new technique to quantify and attribute sources of uncertainty in complex global models is described by Lee et al. (2011, ACP). The analysis uses Gaussian emulation to derive a probability density function (pdf) of predicted quantities, essentially interpolating the PPE results in multi-dimensional parameter space. Once trained on the ensemble, a Monte Carlo simulation with the fast Gaussian emulator enabling a full variance-based sensitivity analysis. The approach has already been used effectively by Carslaw et al., (2013, Nature) to quantify the uncertainty in the cloud albedo effect forcing from a 3D global aerosol-microphysics model allowing to compare the sensitivy of different predicted quantities to uncertainties in natural and anthropogenic emissions types, and structural parameters in the models. Within ISA-MIP, each group will carry out a PPE of runs, with the subsequent analysis with the emulator assessing the uncertainty in the volcanic forcings predicted by each model. In this poster presentation we will give an outline of the "PoEMS" analysis, describing the uncertain parameters to be varied and the relevance to further understanding differences identified in previous international stratospheric aerosol assessments.
Actor groups, related needs, and challenges at the climate downscaling interface
NASA Astrophysics Data System (ADS)
Rössler, Ole; Benestad, Rasmus; Diamando, Vlachogannis; Heike, Hübener; Kanamaru, Hideki; Pagé, Christian; Margarida Cardoso, Rita; Soares, Pedro; Maraun, Douglas; Kreienkamp, Frank; Christodoulides, Paul; Fischer, Andreas; Szabo, Peter
2016-04-01
At the climate downscaling interface, numerous downscaling techniques and different philosophies compete on being the best method in their specific terms. Thereby, it remains unclear to what extent and for which purpose these downscaling techniques are valid or even the most appropriate choice. A common validation framework that compares all the different available methods was missing so far. The initiative VALUE closes this gap with such a common validation framework. An essential part of a validation framework for downscaling techniques is the definition of appropriate validation measures. The selection of validation measures should consider the needs of the stakeholder: some might need a temporal or spatial average of a certain variable, others might need temporal or spatial distributions of some variables, still others might need extremes for the variables of interest or even inter-variable dependencies. Hence, a close interaction of climate data providers and climate data users is necessary. Thus, the challenge in formulating a common validation framework mirrors also the challenges between the climate data providers and the impact assessment community. This poster elaborates the issues and challenges at the downscaling interface as it is seen within the VALUE community. It suggests three different actor groups: one group consisting of the climate data providers, the other two groups being climate data users (impact modellers and societal users). Hence, the downscaling interface faces classical transdisciplinary challenges. We depict a graphical illustration of actors involved and their interactions. In addition, we identified four different types of issues that need to be considered: i.e. data based, knowledge based, communication based, and structural issues. They all may, individually or jointly, hinder an optimal exchange of data and information between the actor groups at the downscaling interface. Finally, some possible ways to tackle these issues are discussed.
NASA Astrophysics Data System (ADS)
Jewell, Jessica; Vinichenko, Vadim; McCollum, David; Bauer, Nico; Riahi, Keywan; Aboumahboub, Tino; Fricko, Oliver; Harmsen, Mathijs; Kober, Tom; Krey, Volker; Marangoni, Giacomo; Tavoni, Massimo; van Vuuren, Detlef P.; van der Zwaan, Bob; Cherp, Aleh
2016-06-01
Ensuring energy security and mitigating climate change are key energy policy priorities. The recent Intergovernmental Panel on Climate Change Working Group III report emphasized that climate policies can deliver energy security as a co-benefit, in large part through reducing energy imports. Using five state-of-the-art global energy-economy models and eight long-term scenarios, we show that although deep cuts in greenhouse gas emissions would reduce energy imports, the reverse is not true: ambitious policies constraining energy imports would have an insignificant impact on climate change. Restricting imports of all fuels would lower twenty-first-century emissions by only 2-15% against the Baseline scenario as compared with a 70% reduction in a 450 stabilization scenario. Restricting only oil imports would have virtually no impact on emissions. The modelled energy independence targets could be achieved at policy costs comparable to those of existing climate pledges but a fraction of the cost of limiting global warming to 2 ∘C.
Development and initial validation of an Aviation Safety Climate Scale.
Evans, Bronwyn; Glendon, A Ian; Creed, Peter A
2007-01-01
A need was identified for a consistent set of safety climate factors to provide a basis for aviation industry benchmarking. Six broad safety climate themes were identified from the literature and consultations with industry safety experts. Items representing each of the themes were prepared and administered to 940 Australian commercial pilots. Data from half of the sample (N=468) were used in an exploratory factor analysis that produced a 3-factor model of Management commitment and communication, Safety training and equipment, and Maintenance. A confirmatory factor analysis on the remaining half of the sample showed the 3-factor model to be an adequate fit to the data. The results of this study have produced a scale of safety climate for aviation that is both reliable and valid. This study developed a tool to assess the level of perceived safety climate, specifically of pilots, but may also, with minor modifications, be used to assess other groups' perceptions of safety climate.
Visual reconciliation of alternative similarity spaces in climate modeling
J Poco; A Dasgupta; Y Wei; William Hargrove; C.R. Schwalm; D.N. Huntzinger; R Cook; E Bertini; C.T. Silva
2015-01-01
Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses...
Woodworth-Jefcoats, Phoebe A; Polovina, Jeffrey J; Dunne, John P; Blanchard, Julia L
2013-03-01
Output from an earth system model is paired with a size-based food web model to investigate the effects of climate change on the abundance of large fish over the 21st century. The earth system model, forced by the Intergovernmental Panel on Climate Change (IPCC) Special report on emission scenario A2, combines a coupled climate model with a biogeochemical model including major nutrients, three phytoplankton functional groups, and zooplankton grazing. The size-based food web model includes linkages between two size-structured pelagic communities: primary producers and consumers. Our investigation focuses on seven sites in the North Pacific, each highlighting a specific aspect of projected climate change, and includes top-down ecosystem depletion through fishing. We project declines in large fish abundance ranging from 0 to 75.8% in the central North Pacific and increases of up to 43.0% in the California Current (CC) region over the 21st century in response to change in phytoplankton size structure and direct physiological effects. We find that fish abundance is especially sensitive to projected changes in large phytoplankton density and our model projects changes in the abundance of large fish being of the same order of magnitude as changes in the abundance of large phytoplankton. Thus, studies that address only climate-induced impacts to primary production without including changes to phytoplankton size structure may not adequately project ecosystem responses. © 2012 Blackwell Publishing Ltd.
ClimateNet: A Machine Learning dataset for Climate Science Research
NASA Astrophysics Data System (ADS)
Prabhat, M.; Biard, J.; Ganguly, S.; Ames, S.; Kashinath, K.; Kim, S. K.; Kahou, S.; Maharaj, T.; Beckham, C.; O'Brien, T. A.; Wehner, M. F.; Williams, D. N.; Kunkel, K.; Collins, W. D.
2017-12-01
Deep Learning techniques have revolutionized commercial applications in Computer vision, speech recognition and control systems. The key for all of these developments was the creation of a curated, labeled dataset ImageNet, for enabling multiple research groups around the world to develop methods, benchmark performance and compete with each other. The success of Deep Learning can be largely attributed to the broad availability of this dataset. Our empirical investigations have revealed that Deep Learning is similarly poised to benefit the task of pattern detection in climate science. Unfortunately, labeled datasets, a key pre-requisite for training, are hard to find. Individual research groups are typically interested in specialized weather patterns, making it hard to unify, and share datasets across groups and institutions. In this work, we are proposing ClimateNet: a labeled dataset that provides labeled instances of extreme weather patterns, as well as associated raw fields in model and observational output. We develop a schema in NetCDF to enumerate weather pattern classes/types, store bounding boxes, and pixel-masks. We are also working on a TensorFlow implementation to natively import such NetCDF datasets, and are providing a reference convolutional architecture for binary classification tasks. Our hope is that researchers in Climate Science, as well as ML/DL, will be able to use (and extend) ClimateNet to make rapid progress in the application of Deep Learning for Climate Science research.
Web Based Data Access to the World Data Center for Climate
NASA Astrophysics Data System (ADS)
Toussaint, F.; Lautenschlager, M.
2006-12-01
The World Data Center for Climate (WDC-Climate, www.wdc-climate.de) is hosted by the Model &Data Group (M&D) of the Max Planck Institute for Meteorology. The M&D department is financed by the German government and uses the computers and mass storage facilities of the German Climate Computing Centre (Deutsches Klimarechenzentrum, DKRZ). The WDC-Climate provides web access to 200 Terabytes of climate data; the total mass storage archive contains nearly 4 Petabytes. Although the majority of the datasets concern model output data, some satellite and observational data are accessible as well. The underlying relational database is distributed on five servers. The CERA relational data model is used to integrate catalogue data and mass data. The flexibility of the model allows to store and access very different types of data and metadata. The CERA metadata catalogue provides easy access to the content of the CERA database as well as to other data in the web. Visit ceramodel.wdc-climate.de for additional information on the CERA data model. The majority of the users access data via the CERA metadata catalogue, which is open without registration. However, prior to retrieving data user are required to check in and apply for a userid and password. The CERA metadata catalogue is servlet based. So it is accessible worldwide through any web browser at cera.wdc-climate.de. In addition to data and metadata access by the web catalogue, WDC-Climate offers a number of other forms of web based data access. All metadata are available via http request as xml files in various metadata formats (ISO, DC, etc., see wini.wdc-climate.de) which allows for easy data interchange with other catalogues. Model data can be retrieved in GRIB, ASCII, NetCDF, and binary (IEEE) format. WDC-Climate serves as data centre for various projects. Since xml files are accessible by http, the integration of data into applications of different projects is very easy. Projects supported by WDC-Climate are e.g. CEOP, IPCC, and CARIBIC. A script tool for data download (jblob) is offered on the web page, to make retrieval of huge data quantities more comfortable.
Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program
NASA Technical Reports Server (NTRS)
Moore, Berrien, III; Sahagian, Dork
1997-01-01
The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.
The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium
DOE Office of Scientific and Technical Information (OSTI.GOV)
Potter, Gerald L; Bader, David C; Riches, Michael
Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session emphasized the scientific ideas that are the basis of PCMDI's success, summarizing their evolution and impact. Four speakers followed the various PCMDI-supported climate model intercomparison projects, beginning with early work on cloud representations in models, presented by Robert D. Cess (Distinguished Professor Emeritus, Stony Brook University), and then the latest Cloud Feedback Model Intercomparison Projects (CFMIPs) led by Sandrine Bony (Laboratoire de M'©t'©orologie Dynamique). Benjamin Santer (LLNL) presented a review of the climate change detection and attribution (D & A) work pioneered at PCMDI, and Gerald A. Meehl (NCAR) ended the day with a look toward the future of climate change research.« less
Van Lange, Paul A M; Rinderu, Maria I; Bushman, Brad J
2017-01-01
Worldwide there are substantial differences within and between countries in aggression and violence. Although there are various exceptions, a general rule is that aggression and violence increase as one moves closer to the equator, which suggests the important role of climate differences. While this pattern is robust, theoretical explanations for these large differences in aggression and violence within countries and around the world are lacking. Most extant explanations focus on the influence of average temperature as a factor that triggers aggression (The General Aggression Model), or the notion that warm temperature allows for more social interaction situations (Routine Activity Theory) in which aggression is likely to unfold. We propose a new model, CLimate, Aggression, and Self-control in Humans (CLASH), that helps us to understand differences within and between countries in aggression and violence in terms of differences in climate. Lower temperatures, and especially larger degrees of seasonal variation in climate, call for individuals and groups to adopt a slower life history strategy, a greater focus on the future (vs. present), and a stronger focus on self-control. The CLASH model further outlines that slow life strategy, future orientation, and strong self-control are important determinants of inhibiting aggression and violence. We also discuss how CLASH differs from other recently developed models that emphasize climate differences for understanding conflict. We conclude by discussing the theoretical and societal importance of climate in shaping individual and societal differences in aggression and violence.
Friocourt, Y F; Skogen, M; Stolte, W; Albretsen, J
2012-01-01
Two hydrodynamic and ecological models were used to investigate the effects of climate change-according to the IPCC A1b emission scenario - on the primary productivity of the North Sea and on harmful algal blooms. Both models were forced with atmospheric fields from a regional downscaling of General Circulation Models to compare two sets of 20-year simulations representative of present climate (1984-2004) conditions and of the 2040s. Both models indicated a general warming of the North Sea by up to 0.8°C and a slight freshening by the 2040s. The models suggested that the eastern North Sea would be subjected to more temperature and salinity changes than the western part. In addition, the ecological modules of the models indicated that the warming up of the sea would result in a slightly earlier spring bloom. The one model that also computes the distribution of four different phytoplankton groups suggests an increase in the abundance of dinoflagellates, whereas the abundance of diatoms, flagellates and Phaeocystis sp. remains comparable to current levels, or decrease. Assuming that Dinophysis spp. would experience a similar increase in abundance as the modelled group of dinoflagellates, it is hypothesised that blooms of Dinophysis spp. may occur more frequently in the North Sea by 2040. However, implications for shellfish toxicity remain unclear.
ERIC Educational Resources Information Center
Huxster, Joanna
2013-01-01
A consensus has been reached within the scientific community concerning the occurrence of climate change and its anthropogenic causes. Outside of this community, however, there continues to be considerable debate and confusion surrounding the topic. The government mitigation strategies and political leadership needed for this issue will require…
It is likely that the total amount of freshwater runoff that reaches many estuaries, the timing of that input, and the amount of variability (i.e. flashiness) associated with its delivery will all be altered in response to climate change. However, global change models are not con...
Evaluating Arctic warming mechanisms in CMIP5 models
NASA Astrophysics Data System (ADS)
Franzke, Christian L. E.; Lee, Sukyoung; Feldstein, Steven B.
2017-05-01
Arctic warming is one of the most striking signals of global warming. The Arctic is one of the fastest warming regions on Earth and constitutes, thus, a good test bed to evaluate the ability of climate models to reproduce the physics and dynamics involved in Arctic warming. Different physical and dynamical mechanisms have been proposed to explain Arctic amplification. These mechanisms include the surface albedo feedback and poleward sensible and latent heat transport processes. During the winter season when Arctic amplification is most pronounced, the first mechanism relies on an enhancement in upward surface heat flux, while the second mechanism does not. In these mechanisms, it has been proposed that downward infrared radiation (IR) plays a role to a varying degree. Here, we show that the current generation of CMIP5 climate models all reproduce Arctic warming and there are high pattern correlations—typically greater than 0.9—between the surface air temperature (SAT) trend and the downward IR trend. However, we find that there are two groups of CMIP5 models: one with small pattern correlations between the Arctic SAT trend and the surface vertical heat flux trend (Group 1), and the other with large correlations (Group 2) between the same two variables. The Group 1 models exhibit higher pattern correlations between Arctic SAT and 500 hPa geopotential height trends, than do the Group 2 models. These findings suggest that Arctic warming in Group 1 models is more closely related to changes in the large-scale atmospheric circulation, whereas in Group 2, the albedo feedback effect plays a more important role. Interestingly, while Group 1 models have a warm or weak bias in their Arctic SAT, Group 2 models show large cold biases. This stark difference in model bias leads us to hypothesize that for a given model, the dominant Arctic warming mechanism and trend may be dependent on the bias of the model mean state.
Kabir, Md Iqbal; Rahman, Md Bayzidur; Smith, Wayne; Lusha, Mirza Afreen Fatima; Milton, Abul Hasnat
2015-01-01
Background Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation. Methods This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model. Results None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model. Conclusions These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic. PMID:26252381
Kabir, Md Iqbal; Rahman, Md Bayzidur; Smith, Wayne; Lusha, Mirza Afreen Fatima; Milton, Abul Hasnat
2015-01-01
Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation. This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model. None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model. These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic.
NASA Technical Reports Server (NTRS)
Rousseaux, C. S.; Gregg, W. W.
2012-01-01
Compared the interannual variation in diatoms, cyanobacteria, coccolithophores and chlorophytes from the NASA Ocean Biogeochemical Model with those derived from satellite data (Hirata et al. 2011) between 1998 and 2006 in the Equatorial Pacific. Using NOBM, La Ni a events were characterized by an increase in diatoms (correlation with MEI, r=-0.81, P<0.05), while cyanobacteria concentrations decreased significantly (r=0.61; P<0.05). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. This represented a radical shift in the phytoplankton community in response to climate variability. However, satellite-derived phytoplankton groups were all negatively correlated with climate variability (r ranged from -0.39 for diatoms to -0.64 for coccolithophores, P<0.05). Spatially, the satellite-derived approach was closer to an independent in situ dataset for all phytoplankton groups except diatoms than NOBM. However, the different responses of phytoplankton to intense interannual events in the Equatorial Pacific raises questions about the representation of phytoplankton dynamics in models and algorithms: is a phytoplankton community shift as in the model or an across-the-board change in abundances of all phytoplankton as in the satellite-derived approach.
García-Navas, Vicente; Westerman, Michael
2018-05-28
The progressive expansion of the Australian arid zone during the last 20 Ma appears to have spurred the diversification of several families of plants, vertebrates and invertebrates, yet such taxonomic groups appear to show limited niche radiation. Here, we test whether speciation is associated with niche conservatism (constraints on ecological divergence) or niche divergence in a tribe of marsupial mice (Sminthopsini; 23 taxa) that includes the most speciose genus of living dasyurids, the sminthopsins. To that end, we integrated phylogenetic data with ecological niche modelling, to enable us to reconstruct the evolution of climatic suitability within Sminthopsini. Niche overlap among species was low-moderate (but generally higher than expected given environmental background similarity), and the degree of phylogenetic clustering increased with aridity. Climatic niche reconstruction illustrates that there has been little apparent evolution of climatic tolerance within clades. Accordingly, climatic disparity tends to be accumulated among clades, suggesting considerable niche conservatism. Our results also indicate that evolution of climatic tolerances has been heterogeneous across different dimensions of climate (temperature vs. precipitation) and across phylogenetic clusters (Sminthopsis murina group vs. other groups). Although some results point to the existence of shifts in climatic niches during the speciation of sminthopsins, our study provides evidence for substantial phylogenetic niche conservatism in the group. We conclude that niche diversification had a low impact on the speciation of this tribe of small, but highly mobile marsupials. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.
Determinants of climate change awareness level in upper Nyakach Division, Kisumu County, Kenya.
Ajuang, Chadwick O; Abuom, Paul O; Bosire, Esna K; Dida, Gabriel O; Anyona, Douglas N
2016-01-01
Improving the understanding of climate change awareness is one of the top priorities in climate change research. While the African continent is among the regions with the highest vulnerability to climate change, research on climate knowledge and awareness is lacking. Kenya is already grappling with the impacts of climate change, which are projected to increase in a non-linear and non-predictable manner. This study sought to determine climate change awareness levels among households residing in Upper Nyakach Division, Kisumu County, Kenya using common climate change markers viz heavy rainfall, floods, droughts and temperature. A cross-sectional survey design was adopted in which 384 household heads were selected as respondents from 11 sub-locations; all located within Upper Nyakach Division. A questionnaire was used to collect data. Most (90.9 %) respondents had observed changes in the overall climate. Awareness level of climate change varied significantly across the 11 sub-locations. To further gain insight unto which variables were the most significant determinant of climate change awareness in upper Nyakach division, Kisumu county, a Generalized Linear Model (GLM) with Poisson error distribution was built. The model indicated that sex of the household head, education level and age significantly influenced respondents' awareness to climate change markers. Most (87 %) households reported rising temperatures over the past 20 years. Over half (55.2 %) the respondents had observed declining rains, with significant differences being observed across age groups. Up to 75 % of the respondents reported increased droughts frequency over the last 20 years, with significant differences observed across gender. Most (86.7 %) respondents reported having observed changes in water sources with significant differences reported across age groups. The respondents reported an increased prevalence of malaria with significant differences being observed among the education levels and households' main livelihoods. The general population of the Upper Nyakach Divison is aware of changing global climate. However, more effort is required in mitigating climate change as per the local settings. Awareness campaign aimed at increasing knowledge of climate change markers among community members is recommended.
Projections of future meteorological drought and wet periods in the Amazon
Duffy, Philip B.; Brando, Paulo; Asner, Gregory P.; Field, Christopher B.
2015-01-01
Future intensification of Amazon drought resulting from climate change may cause increased fire activity, tree mortality, and emissions of carbon to the atmosphere across large areas of Amazonia. To provide a basis for addressing these issues, we examine properties of recent and future meteorological droughts in the Amazon in 35 climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that the CMIP5 climate models, as a group, simulate important properties of historical meteorological droughts in the Amazon. In addition, this group of models reproduces observed relationships between Amazon precipitation and regional sea surface temperature anomalies in the tropical Pacific and the North Atlantic oceans. Assuming the Representative Concentration Pathway 8.5 scenario for future drivers of climate change, the models project increases in the frequency and geographic extent of meteorological drought in the eastern Amazon, and the opposite in the West. For the region as a whole, the CMIP5 models suggest that the area affected by mild and severe meteorological drought will nearly double and triple, respectively, by 2100. Extremes of wetness are also projected to increase after 2040. Specifically, the frequency of periods of unusual wetness and the area affected by unusual wetness are projected to increase after 2040 in the Amazon as a whole, including in locations where annual mean precipitation is projected to decrease. Our analyses suggest that continued emissions of greenhouse gases will increase the likelihood of extreme events that have been shown to alter and degrade Amazonian forests. PMID:26460046
Guy, S Z Y; Li, L; Thomson, P C; Hermesch, S
2017-12-01
Environmental descriptors derived from mean performances of contemporary groups (CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia (n = 31,230). Firstly, CG estimates of average daily gain (ADG) and backfat (BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model (p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a practical approach for the genetic improvement of disease resilience. © 2017 Blackwell Verlag GmbH.
Cloud-radiation interactions and their parameterization in climate models
NASA Technical Reports Server (NTRS)
1994-01-01
This report contains papers from the International Workshop on Cloud-Radiation Interactions and Their Parameterization in Climate Models met on 18-20 October 1993 in Camp Springs, Maryland, USA. It was organized by the Joint Working Group on Clouds and Radiation of the International Association of Meteorology and Atmospheric Sciences. Recommendations were grouped into three broad areas: (1) general circulation models (GCMs), (2) satellite studies, and (3) process studies. Each of the panels developed recommendations on the themes of the workshop. Explicitly or implicitly, each panel independently recommended observations of basic cloud microphysical properties (water content, phase, size) on the scales resolved by GCMs. Such observations are necessary to validate cloud parameterizations in GCMs, to use satellite data to infer radiative forcing in the atmosphere and at the earth's surface, and to refine the process models which are used to develop advanced cloud parameterizations.
NASA Astrophysics Data System (ADS)
Han, B.; Flores, A. N.; Benner, S. G.
2017-12-01
In semiarid and arid regions where water supply is intensively managed, future water scarcity is a product of complex interactions between climate change and human activities. Evaluating future water scarcity under alternative scenarios of climate change, therefore, necessitates modeling approaches that explicitly represent the coupled biophysical and social processes responsible for the redistribution of water in these regions. At regional scales a particular challenge lies in adequately capturing not only the central tendencies of change in projections of climate change, but also the associated plausible range of variability in those projections. This study develops a framework that combines a stochastic weather generator, historical climate observations, and statistically downscaled General Circulation Model (GCM) projections. The method generates a large ensemble of daily climate realizations, avoiding deficiencies of using a few or mean values of individual GCM realizations. Three climate change scenario groups reflecting the historical, RCP4.5, and RCP8.5 future projections are developed. Importantly, the model explicitly captures the spatiotemporally varying irrigation activities as constrained by local water rights in a rapidly growing, semi-arid human-environment system in southwest Idaho. We use this modeling framework to project water use and scarcity patterns under the three future climate change scenarios. The model is built using the Envision alternative futures modeling framework. Climate projections for the region show future increases in both precipitation and temperature, especially under the RCP8.5 scenario. The increase of temperature has a direct influence on the increase of the irrigation water use and water scarcity, while the influence of increased precipitation on water use is less clear. The predicted changes are potentially useful in identifying areas in the watershed particularly sensitive to water scarcity, the relative importance of changes in precipitation versus temperature as a driver of scarcity, and potential shortcomings of the current water management framework in the region.
3ARM: A Fast, Accurate Radiative Transfer Model for Use in Climate Models
NASA Technical Reports Server (NTRS)
Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.
1996-01-01
A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.
3ARM: A Fast, Accurate Radiative Transfer Model for use in Climate Models
NASA Technical Reports Server (NTRS)
Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.
1996-01-01
A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.
3ARM: A Fast, Accurate Radiative Transfer Model For Use in Climate Models
NASA Technical Reports Server (NTRS)
Bergstrom, R. W.; Kinne, S.; Sokolik, I. N.; Toon, O. B.; Mlawer, E. J.; Clough, S. A.; Ackerman, T. P.; Mather, J.
1996-01-01
A new radiative transfer model combining the efforts of three groups of researchers is discussed. The model accurately computes radiative transfer in a inhomogeneous absorbing, scattering and emitting atmospheres. As an illustration of the model, results are shown for the effects of dust on the thermal radiation.
An overview of the South Atlantic Ocean climate variability and air-sea interaction processes
NASA Astrophysics Data System (ADS)
Pezzi, L. P.; Parise, C. K.; Souza, R.; Gherardi, D. F.; Camargo, R.; Soares, H. C.; Silveira, I.
2013-05-01
The Ocean Modeling Group at the National Institute of Space Research (INPE) in Brazil has been developing several studies to understand the role of the Atlantic ocean on the South America climate. Studies include simulating the dynamics of the Tropical South-Atlantic Ocean and Southern Ocean. This is part of an ongoing international cooperation, in which Brazil participates with in situ observations, numerical modeling and statistical analyses. We have focused on the understanding of the impacts of extreme weather events over the Tropical South Atlantic Ocean and their prediction on different time-scales. One such study is aimed at analyzing the climate signal generated by imposing an extreme condition on the Antarctic sea ice and considering different complexities of the sea ice model. The influence of the Brazil-Malvinas Confluence (BMC) region on the marine atmospheric boundary layer (MABL) is also investigated through in situ data analysis of different cruises and numerical experiments with a regional numerical model. There is also an ongoing investigation that revealed basin-scale interannual climate variation with impacts on the Brazilian Large Marine Ecosystems (LMEs), which are strongly correlated with climate indices such as ENSO, AAO and PDO.
Military Psychology: An Overview,
1984-05-01
intelligence tests that were widely used in World War I and also served as the models for most group intelligence tests developed after the war for military and...in such areas as supervision, job satisfaction, organizational climate , and work-group effectiveness. For more information write: LMDC/AN, Maxwell Air...primate. Animal models and methods from the disciplines of behavioral toxicology, behavioral pharmacology, physiological psychology, and neurophysiology
Interannual Variation in Phytoplankton Class-Specific Primary Production at a Global Scale
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile Severine; Gregg, Watson W.
2014-01-01
We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. First we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms were the group that contributed the most to the total phytoplankton production (50, the equivalent of 20 PgC y-1. Coccolithophores and chlorophytes each contributed to 20 (7 PgC y-1 of the total primary production and cyanobacteria represented about 10 (4 PgC y(sub-1) of the total primary production. Primary production by diatoms was highest in high latitude (45) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4 (1-2 PgC y-1. We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nio Index, MEI) and regional climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p 0.05) between the MEI and the class-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatomscyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on the class-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.
NASA Astrophysics Data System (ADS)
Achutarao, K. M.; Singh, R.
2017-12-01
There are various sources of uncertainty in model projections of future climate change. These include differences in the formulation of climate models, internal variability, and differences in scenarios. Internal variability in a climate system represents the unforced change due to the chaotic nature of the climate system and is considered irreducible (Deser et al., 2012). Internal variability becomes important at regional scales where it can dominate forced changes. Therefore it needs to be carefully assessed in future projections. In this study we segregate the role of internal variability in the future temperature and precipitation projections over the Indian region. We make use of the Coupled Model Inter-comparison Project - phase 5 (CMIP5; Taylor et al., 2012) database containing climate model simulations carried out by various modeling centers around the world. While the CMIP5 experimental protocol recommended producing numerous ensemble members, only a handful of the modeling groups provided multiple realizations. Having a small number of realizations is a limitation in producing a quantification of internal variability. We therefore exploit the Community Earth System Model Large Ensemble (CESM-LE; Kay et al., 2014) dataset which contains a 40 member ensemble of a single model- CESM1 (CAM5) to explore the role of internal variability in Future Projections. Surface air temperature and precipitation change projections over regional and sub-regional scale are analyzed under the IPCC emission scenario (RCP8.5) for different seasons and homogeneous climatic zones over India. We analyze the spread in projections due to internal variability in the CESM-LE and CMIP5 datasets over these regions.
Fifth IPCC Assessment Report Now Out
NASA Astrophysics Data System (ADS)
Kundzewicz, Zbigniew W.
2014-01-01
The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) is now available. It provides policymakers with an assessment of information on climate change, its impacts and possible response options (adaptation and mitigation). Summaries for policymakers of three reports of IPCC working groups and of the Synthesis Report have now been approved by IPCC plenaries. This present paper reports on the most essential findings in AR5. It briefly informs on the contents of reports of all IPCC working groups. It discusses the physical science findings, therein observed changes (ubiquitous warming, shrinking cryosphere, sea level rise, changes in precipitation and extremes, and biogeochemical cycles). It deals with the drivers of climate change, progress in climate system understanding (evaluation of climate models, quantification of climate system responses), and projections for the future. It reviews impacts, adaptation and vulnerability, including observed changes, key risks, key reasons for concern, sectors and systems, and managing risks and building resilience. Finally, mitigation of climate change is discussed, including greenhouse gas emissions in the past, present and future, and mitigation in sectors. It is hoped that the present article will encourage the readership of this journal to dive into the AR5 report that provides a wealth of useful information.
Past Climate Change and Plant Evolution in Western North America: A Case Study in Rosaceae
Töpel, Mats; Antonelli, Alexandre; Yesson, Chris; Eriksen, Bente
2012-01-01
Species in the ivesioid clade of Potentilla (Rosaceae) are endemic to western North America, an area that underwent widespread aridification during the global temperature decrease following the Mid-Miocene Climatic Optimum. Several morphological features interpreted as adaptations to drought are found in the clade, and many species occupy extremely dry habitats. Recent phylogenetic analyses have shown that the sister group of this clade is Potentilla section Rivales, a group with distinct moist habitat preferences. This has led to the hypothesis that the ivesioids (genera Ivesia, Horkelia and Horkeliella) diversified in response to the late Tertiary aridification of western North America. We used phyloclimatic modeling and a fossil-calibrated dated phylogeny of the family Rosaceae to investigate the evolution of the ivesioid clade. We have combined occurrence- and climate data from extant species, and used ancestral state reconstruction to model past climate preferences. These models have been projected into paleo-climatic scenarios in order to identify areas where the ivesioids may have occurred. Our analysis suggests a split between the ivesioids and Potentilla sect. Rivales around Late Oligocene/Early Miocene (∼23 million years ago, Ma), and that the ivesioids then diversified at a time when summer drought started to appear in the region. The clade is inferred to have originated on the western slopes of the Rocky Mountains from where a westward range expansion to the Sierra Nevada and the coast of California took place between ∼12-2 Ma. Our results support the idea that climatic changes in southwestern North America have played an important role in the evolution of the local flora, by means of in situ adaptation followed by diversification. PMID:23236369
National Centers for Environmental Prediction
Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Ice group works on sea ice analysis from satellite, sea ice modeling, and ice-atmosphere-ocean / VISION | About EMC Analysis Drift Model KISS Model Numerical Forecast Systems The Polar and Great Lakes
CMIP6 Citation Services and the Data Services of the IPCC Data Distribution Centre for AR6
NASA Astrophysics Data System (ADS)
Stockhause, Martina; Lautenschlager, Michael
2017-04-01
As a result of the experiences from CMIP5 the two services contributed by DKRZ to the CMIP research infrastructure have been improved for CMIP6: the Citation Services and the Services of the IPCC Data Distribution Centre (DDC, http://ipcc-data.org). 1. Data Citation Services: Within CMIP5 it took a couple of years before the data was citable with their DataCite DOIs. The DataCite DOI registration by the WDC Climate at DKRZ (World Data Center Climate at the Climate Computing Center) requires data transfer and long-term archival at DKRZ according to DDC's quality standards. Based on a request from WGCM (Working Group on Climate Models) an additional early citation possibility for the evolving CMIP6 data was added to the citation service (http://cmip6cite.wdc-climate.de). 2. IPCC DDC Services: WDC Climate has been hosting the IPCC DDC's Reference Data Archive for the climate model output underlying the IPCC Assessment Reports (ARs) since the Second Assessment Report in 1995. One task of the DDC is the support of the IPCC Working Groups (WGs) and their authors. The WG support was not sufficient for AR5 resulting in WG I setting up and maintaining their own CMIP5 data repository hosting a data subset. The DDC will open DKRZ's CMIP data pool as an additional DDC service for the IPCC authors using a synergy with the interests of the national climate community. Within the PICO the Citation and the IPCC DDC services will be presented from a user's perspective. The connections to and integration into the infrastructure for CMIP6 (see https://www.earthsystemcog.org/projects/wip/) will be explained.
Wallin, Carl-Johan; Kalman, Sigridur; Sandelin, Annika; Färnert, May-Lena; Dahlstrand, Ursula; Jylli, Leena
2015-03-01
Positive safety and a teamwork climate in the training environment may be a precursor for successful teamwork training. This pilot project aimed to implement and test whether a new interdisciplinary and team-based approach would result in a positive training climate in the operating theatre. A 3-day educational module for training the complete surgical team of specialist nursing students and residents in safe teamwork skills in an authentic operative theatre, named Co-Op, was implemented in a university hospital. Participants' (n=22) perceptions of the 'safety climate' and the 'teamwork climate', together with their 'readiness for inter-professional learning', were measured to examine if the Co-Op module produced a positive training environment compared with the perceptions of a control group (n=11) attending the conventional curriculum. The participants' perceptions of 'safety climate' and 'teamwork climate' and their 'readiness for inter-professional learning' scores were significantly higher following the Co-Op module compared with their perceptions following the conventional curriculum, and compared with the control group's perceptions following the conventional curriculum. The Co-Op module improved 'safety climate' and 'teamwork climate' in the operating theatre, which suggests that a deliberate and designed educational intervention can shape a learning environment as a model for the establishment of a safety culture.
ERIC Educational Resources Information Center
Turner, Isobel; Reynolds, Katherine J.; Lee, Eunro; Subasic, Emina; Bromhead, David
2014-01-01
The present study concerns longitudinal research on bullying perpetration and peer victimization. A focus is on school factors of school climate (academic support, group support) and school identification (connectedness or belonging), which are conceptualized as related but distinct constructs. Analysis of change on these factors as well as…
Afforestation, restoration and regeneration -- Not all trees are created equal
Shaneka Lawson; Charles H. Michler
2014-01-01
Undulations in weather patterns have caused climate shifts of increased frequency and duration around the world. The need for additional research and model data on this pressing problem has resulted in a plethora of research groups examining a particular tree species or biome for negative effects of climate change. This review aims to (1) collect and merge recent...
National Variation in Crop Yield Production Functions
NASA Astrophysics Data System (ADS)
Devineni, N.; Rising, J. A.
2017-12-01
A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.
Collaborative Education in Climate Change Sciences and Adaptation through Interactive Learning
NASA Astrophysics Data System (ADS)
Ozbay, G.; Sriharan, S.; Fan, C.
2014-12-01
As a result of several funded climate change education grants, collaboration between VSU, DSU, and MSU, was established to provide the innovative and cohesive education and research opportunities to underrepresented groups in the climate related sciences. Prior to offering climate change and adaptation related topics to the students, faculty members of the three collaborating institutions participated at a number of faculty training and preparation workshops for teaching climate change sciences (i.e. AMS Diversity Project Workshop, NCAR Faculty-Student Team on Climate Change, NASA-NICE Program). In order to enhance the teaching and student learning on various issues in the Environmental Sciences Programs, Climatology, Climate Change Sciences and Adaptation or related courses were developed at Delaware State University and its partner institutions (Virginia State University and Morgan State University). These courses were prepared to deliver information on physical basis for the earth's climate system and current climate change instruction modules by AMS and historic climate information (NOAA Climate Services, U.S. and World Weather Data, NCAR and NASA Climate Models). By using Global Seminar as a Model, faculty members worked in teams to engage students in videoconferencing on climate change through Contemporary Global Studies and climate courses including Climate Change and Adaptation Science, Sustainable Agriculture, Introduction to Environmental Sciences, Climatology, and Ecology and Adaptation courses. All climate change courses have extensive hands-on practices and research integrated into the student learning experiences. Some of these students have presented their classroom projects during Earth Day, Student Climate Change Symposium, Undergraduate Summer Symposium, and other national conferences.
NASA Astrophysics Data System (ADS)
Peña, M.; Saha, S.; Wu, X.; Wang, J.; Tripp, P.; Moorthi, S.; Bhattacharjee, P.
2016-12-01
The next version of the operational Climate Forecast System (version 3, CFSv3) will be a fully coupled six-components system with diverse applications to earth system modeling, including weather and climate predictions. This system will couple the earth's atmosphere, land, ocean, sea-ice, waves and aerosols for both data assimilation and modeling. It will also use the NOAA Environmental Modeling System (NEMS) software super structure to couple these components. The CFSv3 is part of the next Unified Global Coupled System (UGCS), which will unify the global prediction systems that are now operational at NCEP. The UGCS is being developed through the efforts of dedicated research and engineering teams and through coordination across many CPO/MAPP and NGGPS groups. During this development phase, the UGCS is being tested for seasonal purposes and undergoes frequent revisions. Each new revision is evaluated to quickly discover, isolate and solve problems that negatively impact its performance. In the UGCS-seasonal model, components (e.g., ocean, sea-ice, atmosphere, etc.) are coupled through a NEMS-based "mediator". In this numerical infrastructure, model diagnostics and forecast validation are carried out, both component by component, and as a whole. The next stage, model optimization, will require enhanced performance diagnostics tools to help prioritize areas of numerical improvements. After the technical development of the UGCS-seasonal is completed, it will become the first realization of the CFSv3. All future development of this system will be carried out by the climate team at NCEP, in scientific collaboration with the groups that developed the individual components, as well as the climate community. A unique challenge to evaluate this unified weather-climate system is the large number of variables, which evolve over a wide range of temporal and spatial scales. A small set of performance measures and scorecard displays are been created, and collaboration and software contributions from research and operational centers are being incorporated. A status of the CFSv3/UGCS-seasonal development and examples of its performance and measuring tools will be presented.
NASA Astrophysics Data System (ADS)
Heyn, K.; Campbell, E.
2016-12-01
The Portland Water Bureau has been studying the anticipated effects of climate change on its primary surface water source, the Bull Run Watershed, since the early 2000's. Early efforts by the bureau were almost exclusively reliant on outside expertise from climate modelers and researchers, particularly those at the Climate Impacts Group (CIG) at the University of Washington. Early work products from CIG formed the basis of the bureau's understanding of the most likely and consequential impacts to the watershed from continued GHG-caused warming. However, by mid-decade, as key supply and demand conditions for the bureau changed, it found it lacked the technical capacity and tools to conduct more refined and updated research to build on the outside analysis it had obtained. Beginning in 2010 through its participation in the Pilot Utility Modeling Applications (PUMA) project, the bureau identified and began working to address the holes in its technical and institutional capacity by embarking on a process to assess and select a hydrologic model while obtaining downscaled climate change data to utilize within it. Parallel to the development of these technical elements, the bureau made investments in qualified staff to lead the model selection, development and utilization, while working to establish productive, collegial and collaborative relationships with key climate research staff at the Oregon Climate Change Research Institute (OCCRI), the University of Washington and the University of Idaho. This presentation describes the learning process of a major metropolitan area drinking water utility as its approach to addressing the complex problem of climate change evolves, matures, and begins to influence broader aspects of the organization's planning efforts.
People On The Move: Some Thoughts On Human Dispersal In Relation To Rapid Climatic Change
NASA Astrophysics Data System (ADS)
Davies, W.
It is still generally assumed that the default situation for past humans must have been to be sedentary. That is to say, given a chance people would have settled in one area (with a good supply of resources) and established clearly-defined territories. Such concepts presuppose that much of human existence was conducted in climatic conditions sim- ilar to the relatively stable ones seen in the Holocene. What effects do rapid climatic fluctuations have upon environmental carrying capacity, and thus upon human mobil- ity and exploitation patterns? Such an approach could be called 'non-analogue', as it does not seek to impose [current] Holocene patterns upon the Pleistocene, in the same way that 'non-analogue' animal and plant communities are now routinely described for the same period. If one adopts non-analogue perspectives, perhaps one could also argue that in many cases mobility was the rule and not the exception. Turning the conventional wisdom around, we can ask why people should remain in an area. What are the characteristics of that area which could have encouraged people to become less mobile? I do not argue that all groups were mobile: some cannot have been, and not every member of other groups would have been equally mobile (differentiation on grounds of age and sex). In addition, mobility patterns must also have varied over time, although we should not necessarily expect a discernible linear trend either towards or away from greater mobility, because such behaviour operates within a climatic and environmental framework as well as a socio-economic one. If climate oscillated rapidly, it is feasible to suggest that such fluctuations affected environmental stability and thus carrying capacity. The resource species present and their availability would therefore affect the possibilities for human mobility. When discussing the possibilities for human dispersal into new regions, we essentially have a choice between two competing models: the Wave of Advance (sensu Boserup, Cavalli-Svorza &Ammermann) or Directional dispersal. The former model posits a slow, group-fission-based dispersal across the landscape, driven by 'push' factors such as population pressure. We should not expect resources to be evenly-distributed across the landscape, and thus if one adopts a Wave of Advance interpretation, one would have to consider the possibility of rapid, directional jumps between favoured resource 1 patches, seriously damaging the model's viability. On the other hand, Directional dis- persal models expect more focused movement, with certain ecotones (such as rivers or coasts) being preferred, and are driven more by 'pull' factors which draw people across the landscape relatively rapidly. In the latter model, 'infill' occupation between the initially occupied areas can occur if demanded by socio-economic requirements of the group[s]. This paper will explore all these issues, and discuss how we might identify and test them in the archaeological record, and set them in the climatic context. The effects of climatic factors on past human behaviour have to be qualified or discounted before we can really start to discuss social or 'cultural' explanations. 2
Robinson, Jason L; Fordyce, James A
2017-01-01
Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.
Howard, Michelle; Brazil, Kevin; Akhtar-Danesh, Noori; Agarwal, Gina
2011-05-01
To determine the organizational predictors of higher scores on team climate measures as an indicator of the functioning of a family health team (FHT). Cross-sectional study using a mailed survey. Family health teams in Ontario. Twenty-one of 144 consecutively approached FHTs; 628 team members were surveyed. Scores on the team climate inventory, which assessed organizational culture type (group, developmental, rational, or hierarchical); leadership perceptions; and organizational factors, such as use of electronic medical records (EMRs), team composition, governance of the FHT, location, meetings, and time since FHT initiation. All analyses were adjusted for clustering of respondents within the FHT using a mixed random-intercepts model. The response rate was 65.8% (413 of 628); 2 were excluded from analysis, for a total of 411 participants. At the time of survey completion, there was a median of 4 physicians, 11 other health professionals, and 4 management and clerical staff per FHT. The average team climate score was 3.8 out of a possible 5. In multivariable regression analysis, leadership score, group and developmental culture types, and use of more EMR capabilities were associated with higher team climate scores. Other organizational factors, such as number of sites and size of group, were not associated with the team climate score. Culture, leadership, and EMR functionality, rather than organizational composition of the teams (eg, number of professionals on staff, practice size), were the most important factors in predicting climate in primary care teams.
Modeling of Regional Climate Change Effects on Ground-Level Ozone and Childhood Asthma
Sheffield, Perry E.; Knowlton, Kim; Carr, Jessie L.; Kinney, Patrick L.
2011-01-01
Background The adverse respiratory effects of ground-level ozone are well-established. Ozone is the air pollutant most consistently projected to increase under future climate change. Purpose To project future pediatric asthma emergency department visits associated with ground-level ozone changes, comparing 1990s to 2020s. Methods This study assessed future numbers of asthma emergency department visits for children aged 0–17 years using (1) baseline New York City metropolitan area emergency department rates, (2) a dose–response relationship between ozone levels and pediatric asthma emergency department visits, and (3) projected daily 8-hour maximum ozone concentrations for the 2020s as simulated by a global-to-regional climate change and atmospheric chemistry model. Sensitivity analyses included population projections and ozone precursor changes. This analysis occurred in 2010. Results In this model, climate change could cause an increase in regional summer ozone-related asthma emergency department visits for children aged 0–17 years of 7.3% across the New York City metropolitan region by the 2020s. This effect diminished with inclusion of ozone precursor changes. When population growth is included, the projections of morbidity related to ozone are even larger. Conclusions The results of this analysis demonstrate that the use of regional climate and atmospheric chemistry models make possible the projection of local climate change health effects for specific age groups and specific disease outcomes – such as emergency department visits for asthma. Efforts should be made to improve on this type of modeling to inform local and wider-scale climate change mitigation and adaptation policy. PMID:21855738
NASA Astrophysics Data System (ADS)
Ferguson, D. B.; Guido, Z. S.; Buizer, J.; Roy, M.
2010-12-01
Bringing climate change issues into focus for decision makers is a growing challenge. Decision makers are often confronted with unique informational needs, a lack of useable information, and needs for customized climate change training, among other issues. Despite significant progress in improving climate literacy among certain stakeholders such as water managers, recent reports have highlighted the growing demand for climate-change information in regions and sectors across the US. In recent years many ventures have sprung up to address these gaps and have predominantly focused on K-12 education and resource management agencies such as the National Park Service and National Weather Service. However, two groups that are critical for integrating climate information into actions have received less attention: (1) policy makers and (2) outreach experts, such as Cooperative Extension agents. Climate Change Boot Camps (CCBC) is a joint effort between the Climate Assessment for the Southwest (CLIMAS)—a NOAA Regionally Integrated Sciences and Assessments (RISA) program—and researchers at Arizona State University to diagnose climate literacy and training gaps in Arizona and develop a process that converts these deficiencies into actionable knowledge among the two aforementioned groups. This presentation will highlight the initial phases of the CCBC process, which has as its outcomes the identification of effective strategies for reaching legislators, climate literacy and training needs for both policy makers and trainers, and effective metrics to evaluate the success of these efforts. Specific attention is given to evaluating the process from initial needs assessment to the effectiveness of the workshops. Web curriculum and training models made available on the internet will also be developed, drawing on extensive existing Web resources for other training efforts and converted to meet the needs of these two groups. CCBC will also leverage CLIMAS’ long history of engaging with stakeholders in the Southwest to facilitate to use of climate information in the decision process.
NASA Astrophysics Data System (ADS)
Qian, Y.; Wang, L.; Leung, L. R.; Lin, G.; Lu, J.; Gao, Y.; Zhang, Y.
2017-12-01
Projecting precipitation changes is challenging because of incomplete understanding of the climate system and biases and uncertainty in climate models. In East Asia where summer precipitation is dominantly influenced by the monsoon circulation and the global models from Coupled Model Intercomparison Project Phase 5 (CMIP5), however, give various projection of precipitation change for 21th century. It is critical for community to know which models' projection are more reliable in response to natural and anthropogenic forcings. In this study we defined multiple-dimensional metrics, measuring the model performance in simulating the present-day of large-scale circulation, regional precipitation and relationship between them. The large-scale circulation features examined in this study include the lower tropospheric southwesterly winds, the western North Pacific subtropical high, the South China Sea Subtropical High, and the East Asian westerly jet in the upper troposphere. Each of these circulation features transport moisture to East Asia, enhancing the moist static energy and strengthening the Meiyu moisture front that is the primary mechanism for precipitation generation in eastern China. Based on these metrics, 30 models in CMIP5 ensemble are classified into three groups. Models in the top performing group projected regional precipitation patterns that are more similar to each other than the bottom or middle performing group and consistently projected statistically significant increasing trends in two of the large-scale circulation indices and precipitation. In contrast, models in the bottom or middle performing group projected small drying or no trends in precipitation. We also find the models that only reasonably reproduce the observed precipitation climatology does not guarantee more reliable projection of future precipitation because good simulation skill could be achieved through compensating errors from multiple sources. Herein the potential for more robust projections of precipitation changes at regional scale is demonstrated through the use of discriminating metric to subsample the multi-model ensemble. The results from this study provides insights for how to select models from CMIP ensemble to project regional climate and hydrological cycle changes.
Setting up a model intercomparison project for the last deglaciation
NASA Astrophysics Data System (ADS)
Ivanovic, R. F.; Gregoire, L. J.; Valdes, P. J.; Roche, D. M.; Kageyama, M.
2014-12-01
The last deglaciation (~ 21-9 ka) presents a series of opportunities to study the underlying mechanisms of abrupt climate changes and long-term trends in the Earth System. Most of the forcings are relatively well constrained and geological archives record responses over a range of timescales. Despite this, large uncertainties remain over the feedback loops that culminated in the collapse of the great Northern Hemisphere ice sheets, and a consensus has yet to be reached on the chains of events that led to rapid surface warming and cooling during this period.Climate models are powerful tools for quantitatively assessing these outstanding issues through their ability to temporally resolve cause and effect, as well as break down the contributions from different forcings. This is well demonstrated by pioneering work; for example by Liu et al. (2009), Roche et al. (2011), Gregoire et al. (2012) and Menviel et al. (2011). However, such work is not without challenges; model-geological data mismatches remain unsolved and it is difficult to compare results from different models with unique experiment designs. Therefore, we have established a multidisciplinary Paleoclimate Model Intercomparison Project working group to coordinate transient climate model simulations and geological archive compilations of the last deglaciation. Here, we present the plans and progress of the working group in its first phase of activity; the investigation of Heinrich Stadial 1 and the lead into the Bolling warming event. We describe the set-up of the core deglacial experiment, explain our approach for dealing with uncertain climate forcings and outline our solutions to challenges posed by this research. By defining a common experiment design, we have built a framework to include models of different speeds, complexities and resolution, maximising the reward of this varied approach. One of the next challenges is to compile transient proxy records and develop a methodology for dealing with uncertainty and error in model-geological data comparisons. Through this global and interdisciplinary initiative, we combine multi-proxy records with a suite of different modelling techniques to test hypotheses for abrupt climate changes and reconstruct the chain of events that deglaciated the Earth 21-9 ka.
The implications of rebasing global mean temperature timeseries for GCM based climate projections
NASA Astrophysics Data System (ADS)
Stainforth, David; Chapman, Sandra; Watkins, Nicholas
2017-04-01
Global climate and earth system models are assessed by comparison with observations through a number of metrics. The InterGovernmental Panel on Climate Change (IPCC) highlights in particular their ability to reproduce "general features of the global and annual mean surface temperature changes over the historical period" [1,2] and to simulate "a trend in global-mean surface temperature from 1951 to 2012 that agrees with the observed trend" [3]. This focus on annual mean global mean temperature (hereafter GMT) change is presented as an important element in demonstrating the relevance of these models for climate projections. Any new model or new model version whose historic simulations fail to reproduce the "general features " and 20th century trends is likely therefore to undergo further tuning. Thus this focus could have implications for model development. Here we consider a formal interpretation of "general features" and discuss the implications of this approach to model assessment and intercomparison, for the interpretation of GCM projections. Following the IPCC, we interpret a major element of "general features" as being the slow timescale response to external forcings. (Shorter timescale behaviour such as the response to volcanic eruptions are also elements of "general features" but are not considered here.) Also following the IPCC, we consider only GMT anomalies i.e. changes with respect to some period. Since the models have absolute temperatures which range over about 3K (roughly observed GMT +/- 1.5K) this means their timeseries (and the observations) are rebased. We present timeseries of the slow timescale response of the CMIP5 models rebased to late-20th century temperatures and to mid-19th century temperatures. We provide a mathematical interpretation of this approach to model assessment and discuss two consequences. First is a separation of scales which limits the degree to which sub-global behaviour can feedback on the global response. Second, is an implication of linearity in the GMT response (to the extent that the slow-timescale response of the historic simulations is consistent with observations, and given their uncertainties). For each individual model these consequences only apply over the range of absolute temperatures simulated by the model in historic simulations. Taken together, however, they imply consequences over a much wider range of GMTs. The analysis suggests that this aspect of model evaluation risks providing a model development pressure which acts against a wide exploration of physically plausible responses; in particular against an exploration of potentially globally significant nonlinear responses and feedbacks. [1] IPCC, Fifth Assessment Report, Working Group 1, Technical Summary: Stocker et al. 2013. [2] IPCC, Fifth Assessment Report, Working Group 1, Chapter 9 - "Evaluation of Climate Models": Flato et al. 2013. [3] IPCC, Fifth Assessment Report, Working Group 1, Summary for Policy Makers: IPCC, 2013.
Bahamians and Climate Change: An Analysis of Risk Perception and Climate Change Literacy
NASA Astrophysics Data System (ADS)
Neely, R.; Owens, M. A.
2011-12-01
The Commonwealth of the Bahamas is forecasted to be adversely impacted by the effects of climate change. This presentation will present the results of an assessment of the risk perception toward climate change and climate change literacy among Bahamians. 499 Bahamians from the health care and hospitality industries participated in surveys and/or focus groups and three (3) areas of climate change literacy (attitude, behavior and knowledge) were analyzed as well as risk perception. In general, 1) Bahamians demonstrated an elementary understanding of the underlying causes of climate change, 2) possessed positive attitudes toward adopting new climate change policies, and 3) are already adjusting their behaviors in light of the current predictions. This research also resulted in the development of a model of the relationships between the climate literacy subscales (attitude, behavior and knowledge) and risk perception. This study also examined information sources and their impacts on climate change literacy. As the source of information is important in assessing the quality of the information, participants also identified the source(s) of most of their climate change information. The TV news was cited as the most common source for climate change information among Bahamians. As there is limited active research generating specific climate change information in the Bahamas, all the information Bahamians receive as it pertains to climate change is generated abroad. As a result, Bahamians must decipher through to make sense of it on an individual level. From the focus groups, many of the participants have been able to view possible changes through a cultural lens and are willing to make adjustments to maintain the uniqueness and viability of the Bahamas and to preserve it for generations. Continued study of Bahamians' climate change literacy will inform adaption and mitigation policy as well as individual action.
Prestoration: Using species in restoration that will persist now and into the future
Butterfield, B.J.; Copeland, Stella; Munson, Seth M.; Roybal, C.M.; Wood, Troy E.
2017-01-01
Climate change presents new challenges for selecting species for restoration. If migration fails to keep pace with climate change, as models predict, the most suitable sources for restoration may not occur locally at all. To address this issue we propose a strategy of “prestoration”: utilizing species in restoration for which a site represents suitable habitat now and into the future. Using the Colorado Plateau, USA as a case study, we assess the ability of grass species currently used regionally in restoration to persist into the future using projections of ecological niche models (or climate envelope models) across a suite of climate change scenarios. We then present a technique for identifying new species that best compensate for future losses of suitable habitat by current target species. We found that the current suite of species, selected by a group of experts, is predicted to perform reasonably well in the short-term, but that losses of prestorable habitat by mid-century would approach 40%. Using an algorithm to identify additional species, we found that fewer than ten species could compensate for nearly all of the losses incurred by the current target species. This case study highlights the utility of integrating ecological niche modeling and future climate forecasts to predict the utility of species in restoring under climate change across a wide range of spatial and temporal scales.
NASA Astrophysics Data System (ADS)
Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander
2016-04-01
Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.
Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology
NASA Astrophysics Data System (ADS)
Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix
2018-03-01
During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.
Communicating Climate Change: the Problem of Knowing and Doing.
NASA Astrophysics Data System (ADS)
Wildcat, D.
2008-12-01
The challenge of global warming and climate change may illustrate better than any recent phenomenon that quite independent of the science associated with our assessment, modeling, mitigation strategies and adaptation to the multiple complex processes that characterize this phenomenon, our greatest challenge resides in creating systems where knowledge can be usefully communicated to the general public. Knowledge transfer will pose significant challenges when addressing a topic that often leaves the ill-informed and non-scientist overwhelmed with pieces of information and paralyzed with a sense that there is nothing to be done to address this global problem. This communication problem is very acute in North American indigenous communities where a first-hand, on-the-ground, experience of climate change is indisputable, but where the charts, graphs and sophisticated models presented by scientists are treated with suspicion and often not explained very well. This presentation will discuss the efforts of the American Indian and Alaska Native Climate Change Working Group to prepare future generations of AI/AN geoscience professionals, educators, and a geoscience literate AI/AN workforce, while insuring that our Indigenous tribal knowledges of land- and sea-scapes, and climates are valued, used and incorporated into our tribal exercise of geoscience education and research. The Working Group's efforts are already suggesting the communication problem for Indigenous communities will best be solved by 'growing' our own culturally competent Indigenous geoscience professionals.
NASA Astrophysics Data System (ADS)
Weihs, R. R.
2013-12-01
A variety of Florida-focused climate change activities will be featured as part of the ASK Florida global and regional climate change professional development workshops. In a combined effort from Florida State University's Center for Ocean-Atmospheric Prediction Studies (COAPS) and University of South Florida's Coalition for Science Literacy (CSL), and supported by NASA's NICE initiative, the ASK Florida professional development workshops are a series of workshops designed to enhance and support climate change information and related pedagogical skills for middle school science teachers from Title-I schools in Florida. These workshops took place during a two-year period from 2011 to 2013 and consisted of two cohorts in Hillsborough and Volusia counties in Florida. Featured activities include lab-style exercises demonstrating topics such as storm surge and coastal geometry, sea level rise from thermal expansion, and the greenhouse effect. These types of labs are modified so that they allow more independent, inquiry thinking as they require teachers to design their own experiment in order to test a hypothesis. Lecture based activities are used to cover a broad range of topics including hurricanes, climate modeling, and sink holes. The more innovative activities are group activities that utilize roll-playing, technology and resources, and group discussion. For example, 'Climate Gallery Walk' is an activity that features group discussions on each of the climate literacy principles established by the United States Global Change Research Program. By observing discussions between individuals and groups, this activity helps the facilitators gather information on their previous knowledge and identify possible misconceptions that will be addressed within the workshops. Furthermore, 'Fact or Misconception' presents the challenge of identifying whether a given statement is fact or misconception based on the material covered throughout the workshops. It serves as a way to evaluate retention of knowledge as well as clarification and reinforcement of topics. Another featured activity is 'Climate Change Scenario' in which teachers roll play as groups from various facets of local government, who decide how to deal with a given climate change scenario in the Miami-Dade county area. This activity demonstrates the complexities of negotiations that policy makers must make for the greater good of the local economy and ecology. Finally, we highlight activities that utilize online resources for both scientific information and pedagogical strategies for teaching climate change at the middle school level. Such resources include MYNASADATA, hurricane tracking websites, other scientist-vetted climate change lessons, and outreach events like NOAA's Adopt-a-drifter. These activities are highlighted for other scientists, educators, and professional development groups in the hopes that they will inspire further collaboration and further commitment to enhancing climate change education for our nation's youth.
Jaakkola, Timo; Wang, C K John; Soini, Markus; Liukkonen, Jarmo
2015-09-01
The purpose of this study was to identify student clusters with homogenous profiles in perceptions of task- and ego-involving, autonomy, and social relatedness supporting motivational climate in school physical education. Additionally, we investigated whether different motivational climate groups differed in their enjoyment in PE. Participants of the study were 2 594 girls and 1 803 boys, aged 14-15 years. Students responded to questionnaires assessing their perception of motivational climate and enjoyment in physical education. Latent profile analyses produced a five-cluster solution labeled 1) 'low autonomy, relatedness, task, and moderate ego climate' group', 2) 'low autonomy, relatedness, and high task and ego climate, 3) 'moderate autonomy, relatedness, task and ego climate' group 4) 'high autonomy, relatedness, task, and moderate ego climate' group, and 5) 'high relatedness and task but moderate autonomy and ego climate' group. Analyses of variance showed that students in clusters 4 and 5 perceived the highest level of enjoyment whereas students in cluster 1 experienced the lowest level of enjoyment. The results showed that the students' perceptions of various motivational climates created differential levels of enjoyment in PE classes. Key pointsLatent profile analyses produced a five-cluster solution labeled 1) 'low autonomy, relatedness, task, and moderate ego climate' group', 2) 'low autonomy, relatedness, and high task and ego climate, 3) 'moderate autonomy, relatedness, task and ego climate' group 4) 'high autonomy, relatedness, task, and moderate ego climate' group, and 5) 'high relatedness and task but moderate autonomy and ego climate' group.Analyses of variance showed that clusters 4 and 5 perceived the highest level of enjoyment whereas cluster 1 experienced the lowest level of enjoyment. The results showed that the students' perceptions of motivational climate create differential levels of enjoyment in PE classes.
NASA Technical Reports Server (NTRS)
Badr, Hamada S.; Dezfuli, Amin K.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.
2016-01-01
Many studies have documented dramatic climatic and environmental changes that have affected Africa over different time scales. These studies often raise questions regarding the spatial extent and regional connectivity of changes inferred from observations and proxies and/or derived from climate models. Objective regionalization offers a tool for addressing these questions. To demonstrate this potential, applications of hierarchical climate regionalizations of Africa using observations and GCM historical simulations and future projections are presented. First, Africa is regionalized based on interannual precipitation variability using Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data for the period 19812014. A number of data processing techniques and clustering algorithms are tested to ensure a robust definition of climate regions. These regionalization results highlight the seasonal and even month-to-month specificity of regional climate associations across the continent, emphasizing the need to consider time of year as well as research question when defining a coherent region for climate analysis. CHIRPS regions are then compared to those of five GCMs for the historic period, with a focus on boreal summer. Results show that some GCMs capture the climatic coherence of the Sahel and associated teleconnections in a manner that is similar to observations, while other models break the Sahel into uncorrelated subregions or produce a Sahel-like region of variability that is spatially displaced from observations. Finally, shifts in climate regions under projected twenty-first-century climate change for different GCMs and emissions pathways are examined. A projected change is found in the coherence of the Sahel, in which the western and eastern Sahel become distinct regions with different teleconnections. This pattern is most pronounced in high-emissions scenarios.
Deaf college students' attitudes toward racial/ethnic diversity, campus climate, and role models.
Parasnis, Ila; Samar, Vincent J; Fischer, Susan D
2005-01-01
Deaf college students' attitudes toward a variety of issues related to racial/ethnic diversity were surveyed by contacting all racial/ethnic minority deaf students and a random sample of Caucasian deaf students attending the National Technical Institute for the Deaf (NTID), Rochester Institute of Technology; 38% completed the survey. Although racial/ethnic groups similarly perceived NTID's commitment and efforts related to diversity, they differed significantly on some items related to campus climate and role models. Furthermore, the racial/ethnic minority groups differed from each other in their perceptions of campus comfort level, racial conflict, friendship patterns, and availability of role models. Educational satisfaction was positively correlated with campus comfort level; both correlated negatively with perception of discrimination and racial conflict. Qualitative data analyses supported quantitative data analyses and provided rich detail that facilitated interpretation of deaf students' experiences related to racial/ethnic diversity.
Rebecca Flitcroft; Kelly Burnett; Kelly Christiansen
2013-01-01
Diadromous aquatic species that cross a diverse range of habitats (including marine, estuarine, and freshwater) face different effects of climate change in each environment. One such group of species is the anadromous Pacific salmon (Oncorhynchus spp.). Studies of the potential effects of climate change on salmonids have focused on both marine and...
Public attention to science and political news and support for climate change mitigation
NASA Astrophysics Data System (ADS)
Hart, P. Sol; Nisbet, Erik C.; Myers, Teresa A.
2015-06-01
We examine how attention to science and political news may influence public knowledge, perceived harm, and support for climate mitigation policies. Previous research examining these relationships has not fully accounted for how political ideology shapes the mental processes through which the public interprets media discourses about climate change. We incorporate political ideology and the concept of motivated cognition into our analysis to compare and contrast two prominent models of opinion formation, the scientific literacy model, which posits that disseminating scientific information will move public opinion towards the scientific consensus, and the motivated reasoning model, which posits that individuals will interpret information in a biased manner. Our analysis finds support for both models of opinion formation with key differences across ideological groups. Attention to science news was associated with greater perceptions of harm and knowledge for conservatives, but only additional knowledge for liberals. Supporting the literacy model, greater knowledge was associated with more support for climate mitigation for liberals. In contrast, consistent with motivated reasoning, more knowledgeable conservatives were less supportive of mitigation policy. In addition, attention to political news had a negative association with perceived harm for conservatives but not for liberals.
Next Generation Climate Change Experiments Needed to Advance Knowledge and for Assessment of CMIP6
DOE Office of Scientific and Technical Information (OSTI.GOV)
Katzenberger, John; Arnott, James; Wright, Alyson
2014-10-30
The Aspen Global Change Institute hosted a technical science workshop entitled, “Next generation climate change experiments needed to advance knowledge and for assessment of CMIP6,” on August 4-9, 2013 in Aspen, CO. Jerry Meehl (NCAR), Richard Moss (PNNL), and Karl Taylor (LLNL) served as co-chairs for the workshop which included the participation of 32 scientists representing most of the major climate modeling centers for a total of 160 participant days. In August 2013, AGCI gathered a high level meeting of representatives from major climate modeling centers around the world to assess achievements and lessons learned from the most recent generationmore » of coordinated modeling experiments known as the Coupled Model Intercomparison Project – 5 (CMIP5) as well as to scope out the science questions and coordination structure desired for the next anticipated phase of modeling experiments called CMIP6. The workshop allowed for reflection on the coordination of the CMIP5 process as well as intercomparison of model results, such as were assessed in the most recent IPCC 5th Assessment Report, Working Group 1. For example, this slide from Masahiro Watanabe examines performance on a range of models capturing Atlantic Meridional Overturning Circulation (AMOC).« less
Human Health and Climate Change: Leverage Points for Adaptation in Urban Environments
Proust, Katrina; Newell, Barry; Brown, Helen; Capon, Anthony; Browne, Chris; Burton, Anthony; Dixon, Jane; Mu, Lisa; Zarafu, Monica
2012-01-01
The design of adaptation strategies that promote urban health and well-being in the face of climate change requires an understanding of the feedback interactions that take place between the dynamical state of a city, the health of its people, and the state of the planet. Complexity, contingency and uncertainty combine to impede the growth of such systemic understandings. In this paper we suggest that the collaborative development of conceptual models can help a group to identify potential leverage points for effective adaptation. We describe a three-step procedure that leads from the development of a high-level system template, through the selection of a problem space that contains one or more of the group’s adaptive challenges, to a specific conceptual model of a sub-system of importance to the group. This procedure is illustrated by a case study of urban dwellers’ maladaptive dependence on private motor vehicles. We conclude that a system dynamics approach, revolving around the collaborative construction of a set of conceptual models, can help communities to improve their adaptive capacity, and so better meet the challenge of maintaining, and even improving, urban health in the face of climate change. PMID:22829795
Regional analysis of drought and heat impacts on forests: current and future science directions.
Law, Beverly E
2014-12-01
Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Quantitative assessment of Vulnerability of Forest ecosystem to Climate Change in Korea
NASA Astrophysics Data System (ADS)
Byun, J.; Lee, W.; Choi, S.; Oh, S.; Climate Change Model Team
2011-12-01
The purpose of this study was to assess the vulnerability of forest ecosystem to climate change in Korea using outputs of vegetation models(HyTAG and MC1) and socio-ecological indicators. Also it suggested adaptation strategies in forest management through analysis of three vulnerability components: exposure, sensitivity and adaptive capacity. For the model simulation of past years(1971-2000), the climatic data was prepared by the Korea Meteorological Administration(KMA). In addition, for the future simulation, the Fifth-Generation NCAR/Penn State Mesoscale Model(MM5) coupling with atmosphere-ocean circulation model(ECHO-G) provide the future climatic data under the A1B scenarios. HyTAG (Hydrological and Thermal Analogy Groups), korean model of forest distribution on a regional-scale, could show extent of sensitivity and adaptive capacity in connection with changing frequency and changing direction of vegetation. MC1 model could provide variation and direction of NPP(Net Primary Production) and SCS(Soil Carbon Storage). In addition, the sensitivity and adaptation capacity were evaluated for each. Besides indicators from models, many other indicators such as financial affairs and number of officers were included in the vulnerability components. As a result of the vulnerability assessment, south western part and Je-ju island of Korea had relatively high vulnerability. This finding is considered to come from a distinctively adaptative capacity. Using these results, we could propose actions against climate change and develop decision making systems on forest management.
Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model
NASA Astrophysics Data System (ADS)
Lim, Hyung-Gyu; Park, Jong-Yeon; Kug, Jong-Seong
2017-12-01
Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM's intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air-sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.
NASA Astrophysics Data System (ADS)
Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.
2018-02-01
Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.
The Urbino Summer School in Paleoclimatology: Investing in the future of paleoclimatology
NASA Astrophysics Data System (ADS)
Schellenberg, S. A.; Galeotti, S.; Brinkhuis, H.; Leckie, R. M.
2010-12-01
Improving our understanding of global climate dynamics is increasingly critical as we continue to perturb the Earth system on geologically rapid time-scales. One approach is the modeling of climate dynamics; another is the exploitation of natural archives of climate history. To promote the synergistic integration of these approaches in the next generation of paleoclimatologists, a group of international teacher-scholars have developed the Urbino Summer School in Paleoclimatology (USSP), which has been offered since 2004 at the Università degli Studi di Urbino in Urbino, Italy. The USSP provides international graduate students with an intensive three-week experience in reconstructing the history and dynamics of climate through an integrated series of lectures, investigations, and field and laboratory analyses. Complementing these formal components, informal scientific discussions and collaborations are promoted among faculty and students through group meals, coffee breaks, socials, and evening presentations. The first week begins with a broad overview of climate history and dynamics, and then focuses on the principles and methods that transform geographically- and materially-diverse data into globally time-ordinated paleoclimatic information. Lectures largely serve as “connective tissue” for student-centered investigations that use ocean drilling data and student-collected field data from the spectacular exposures of the surrounding Umbre-Marche Basin. The second week provides sessions and investigations on various biotic and geochemical proxies, and marks the start of student “working groups,” each of whom focus on current understanding of, and outstanding questions regarding, a particular geologic time-interval. Parallel sessions also commence, wherein students self-select to attend one of three concurrently-offered more specialized topics. The third week is an intensive exploration of geochemical, climate, and ocean modeling that stresses the integration of paleoclimate modeling and proxy data. The third week also includes the “Cioppino” conference comprised of lectures by experts from various fields that presenting “new and exciting ideas for digestion.” The course concludes with a series of lectures, discussion, and student presentations examining the relevance of paleoclimate to understanding modern climate dynamics and anthropogenic impacts. Student costs are increasingly being reduced per capita through governmental/institutional underwriting and individually through competitive awards (e.g., recent NSF USSP scholarships). Based on student and faculty evaluations, the current USSP structure appears largely optimized for our initial goal of promoting the integration of paleoclimate proxy data and modeling. Current planning efforts focus on strengthening course connections to Anthropocene issues and managing the large number of international faculty who donate their time and energy as an investment in the future of paleoclimatology.
Safety climate and firefighting: Focus group results.
DeJoy, David M; Smith, Todd D; Dyal, Mari-Amanda
2017-09-01
Firefighting is a hazardous occupation and there have been numerous calls for fundamental changes in how fire service organizations approach safety and balance safety with other operational priorities. These calls, however, have yielded little systematic research. As part of a larger project to develop and test a model of safety climate for the fire service, focus groups were used to identify potentially important dimensions of safety climate pertinent to firefighting. Analyses revealed nine overarching themes. Competency/professionalism, physical/psychological readiness, and that positive traits sometimes produce negative consequences were themes at the individual level; cohesion and supervisor leadership/support at the workgroup level; and politics/bureaucracy, resources, leadership, and hiring/promotion at the organizational level. A multi-level perspective seems appropriate for examining safety climate in firefighting. Safety climate in firefighting appears to be multi-dimensional and some dimensions prominent in the general safety climate literature also seem relevant to firefighting. These results also suggest that the fire service may be undergoing transitions encompassing mission, personnel, and its fundamental approach to safety and risk. These results help point the way to the development of safety climate measures specific to firefighting and to interventions for improving safety performance. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Milinski, Manfred
2014-12-01
Climate change is a global problem. Because of unlimited use of fossil energy and resulting greenhouse gas emissions the global temperature is rising causing floods, draughts and storms in all parts of the world with increasing frequency and strength. Dangerous climate change will occur with high probability after the global temperature has passed a certain threshold [1]. To avoid dangerous climate change global greenhouse gas emissions must be reduced to a level of 50% or less of the year-2000 emissions by 2050 [2-4]. All people on earth take part in this global target public goods game, "a game that we cannot afford to loose" [5]. Simulating this scenario in a nutshell a collective risk social dilemma game has shown that a small group of subjects can achieve a collective goal by sequential individual contributions but only when the risk of loosing their not invested money is high, e.g. 90% [6]. Cooperation in public goods games usually decreases with increasing group size [7]. Thus, does this mean that the global game will be lost?
Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B
2017-06-01
Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands. © 2017 by the Ecological Society of America.
Itter, Malcolm S.; Finley, Andrew O.; D'Amato, Anthony W.; Foster, Jane R.; Bradford, John B.
2017-01-01
Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.
NASA Astrophysics Data System (ADS)
Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer
2018-02-01
Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.
NASA Astrophysics Data System (ADS)
Keener, V. W.; Finucane, M.; Brewington, L.
2014-12-01
For the last century, the island of Maui, Hawaii, has been the center of environmental, agricultural, and legal conflict with respect to surface and groundwater allocation. Planning for adequate future freshwater resources requires flexible and adaptive policies that emphasize partnerships and knowledge transfer between scientists and non-scientists. In 2012 the Hawai'i state legislature passed the Climate Change Adaptation Priority Guidelines (Act 286) law requiring county and state policy makers to include island-wide climate change scenarios in their planning processes. This research details the ongoing work by researchers in the NOAA funded Pacific RISA to support the development of Hawaii's first island-wide water use plan under the new climate adaptation directive. This integrated project combines several models with participatory future scenario planning. The dynamically downscaled triply nested Hawaii Regional Climate Model (HRCM) was modified from the WRF community model and calibrated to simulate the many microclimates on the Hawaiian archipelago. For the island of Maui, the HRCM was validated using 20 years of hindcast data, and daily projections were created at a 1 km scale to capture the steep topography and diverse rainfall regimes. Downscaled climate data are input into a USGS hydrological model to quantify groundwater recharge. This model was previously used for groundwater management, and is being expanded utilizing future climate projections, current land use maps and future scenario maps informed by stakeholder input. Participatory scenario planning began in 2012 to bring together a diverse group of over 50 decision-makers in government, conservation, and agriculture to 1) determine the type of information they would find helpful in planning for climate change, and 2) develop a set of scenarios that represent alternative climate/management futures. This is an iterative process, resulting in flexible and transparent narratives at multiple scales. The resulting climate, land use, and groundwater recharge maps give stakeholders a common set of future scenarios that they understand through the participatory scenario process, and identify the vulnerabilities, trade-offs, and adaptive priorities for different groundwater management and land uses in an uncertain future.
Dalmaris, Eleftheria; Ramalho, Cristina E; Poot, Pieter; Veneklaas, Erik J; Byrne, Margaret
2015-11-01
A worldwide increase in tree decline and mortality has been linked to climate change and, where these represent foundation species, this can have important implications for ecosystem functions. This study tests a combined approach of phylogeographic analysis and species distribution modelling to provide a climate change context for an observed decline in crown health and an increase in mortality in Eucalyptus wandoo, an endemic tree of south-western Australia. Phylogeographic analyses were undertaken using restriction fragment length polymorphism analysis of chloroplast DNA in 26 populations across the species distribution. Parsimony analysis of haplotype relationships was conducted, a haplotype network was prepared, and haplotype and nucleotide diversity were calculated. Species distribution modelling was undertaken using Maxent models based on extant species occurrences and projected to climate models of the last glacial maximum (LGM). A structured pattern of diversity was identified, with the presence of two groups that followed a climatic gradient from mesic to semi-arid regions. Most populations were represented by a single haplotype, but many haplotypes were shared among populations, with some having widespread distributions. A putative refugial area with high haplotype diversity was identified at the centre of the species distribution. Species distribution modelling showed high climatic suitability at the LGM and high climatic stability in the central region where higher genetic diversity was found, and low suitability elsewhere, consistent with a pattern of range contraction. Combination of phylogeography and paleo-distribution modelling can provide an evolutionary context for climate-driven tree decline, as both can be used to cross-validate evidence for refugia and contraction under harsh climatic conditions. This approach identified a central refugial area in the test species E. wandoo, with more recent expansion into peripheral areas from where it had contracted at the LGM. This signature of contraction from lower rainfall areas is consistent with current observations of decline on the semi-arid margin of the range, and indicates low capacity to tolerate forecast climatic change. Identification of a paleo-historical context for current tree decline enables conservation interventions to focus on maintaining genetic diversity, which provides the evolutionary potential for adaptation to climate change. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Understanding and Improving Ocean Mixing Parameterizations for modeling Climate Change
NASA Astrophysics Data System (ADS)
Howard, A. M.; Fells, J.; Clarke, J.; Cheng, Y.; Canuto, V.; Dubovikov, M. S.
2017-12-01
Climate is vital. Earth is only habitable due to the atmosphere&oceans' distribution of energy. Our Greenhouse Gas emissions shift overall the balance between absorbed and emitted radiation causing Global Warming. How much of these emissions are stored in the ocean vs. entering the atmosphere to cause warming and how the extra heat is distributed depends on atmosphere&ocean dynamics, which we must understand to know risks of both progressive Climate Change and Climate Variability which affect us all in many ways including extreme weather, floods, droughts, sea-level rise and ecosystem disruption. Citizens must be informed to make decisions such as "business as usual" vs. mitigating emissions to avert catastrophe. Simulations of Climate Change provide needed knowledge but in turn need reliable parameterizations of key physical processes, including ocean mixing, which greatly impacts transport&storage of heat and dissolved CO2. The turbulence group at NASA-GISS seeks to use physical theory to improve parameterizations of ocean mixing, including smallscale convective, shear driven, double diffusive, internal wave and tidal driven vertical mixing, as well as mixing by submesoscale eddies, and lateral mixing along isopycnals by mesoscale eddies. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. We write our own programs in MATLAB and FORTRAN to visualize and process output of ocean simulations including producing statistics to help judge impacts of different parameterizations on fidelity in reproducing realistic temperatures&salinities, diffusivities and turbulent power. The results can help upgrade the parameterizations. Students are introduced to complex system modeling and gain deeper appreciation of climate science and programming skills, while furthering climate science. We are incorporating climate projects into the Medgar Evers college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293 And NASA Award NNX17AC81G.
NASA Astrophysics Data System (ADS)
Cohn, A.; Bragança, A.; Jeffries, G. R.
2017-12-01
An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.
Path Dependence of Regional Climate Change
NASA Astrophysics Data System (ADS)
Herrington, Tyler; Zickfeld, Kirsten
2013-04-01
Path dependence of the climate response to CO2 forcing has been investigated from a global mean perspective, with evidence suggesting that long-term global mean temperature and precipitation changes are proportional to cumulative CO2 emissions, and independent of emissions pathway. Little research, however, has been done on path dependence of regional climate changes, particularly in areas that could be affected by tipping points. Here, we utilize the UVic Earth System Climate Model version 2.9, an Earth System Model of Intermediate Complexity. It consists of a 3-dimensional ocean general circulation model, coupled with a dynamic-thermodynamic sea ice model, and a thermodynamic energy-moisture balance model of the atmosphere. This is then coupled with a terrestrial carbon cycle model and an ocean carbon-cycle model containing an inorganic carbon and marine ecosystem component. Model coverage is global with a zonal resolution of 3.6 degrees and meridional resolution of 1.8 degrees. The model is forced with idealized emissions scenarios across five cumulative emission groups (1300 GtC, 2300 GtC, 3300 GtC, 4300 GtC, and 5300 GtC) to explore the path dependence of (and the possibility of hysteresis in) regional climate changes. Emission curves include both fossil carbon emissions and emissions from land use changes, and span a variety of peak and decline scenarios with varying emission rates, as well as overshoot and instantaneous pulse scenarios. Tipping points being explored include those responsible for the disappearance of summer Arctic sea-ice, the irreversible melt of the Greenland Ice Sheet, the collapse of the Atlantic Thermohaline Circulation, and the dieback of the Amazonian Rainforest. Preliminary results suggest that global mean climate change after cessation of CO2 emissions is independent of the emissions pathway, only varying with total cumulative emissions, in accordance with results from earlier studies. Forthcoming analysis will investigate path dependence of regional climate change. Some evidence exists to support the idea of hysteresis in the Greenland Ice Sheet, and since tipping points represent non-linear elements of the climate system, we suspect that the other tipping points might also show path dependence.
Modelling the climatic niche of turtles: a deep-time perspective
Schmidt, Daniela N.; Valdes, Paul J.; Holroyd, Patricia A.; Farnsworth, Alexander
2016-01-01
Ectotherms have close physiological ties with the thermal environment; consequently, the impact of future climate change on their biogeographic distributions is of major interest. Here, we use the modern and deep-time fossil record of testudines (turtles, tortoises, and terrapins) to provide the first test of climate on the niche limits of both extant and extinct (Late Cretaceous, Maastrichtian) taxa. Ecological niche models are used to assess niche overlap in model projections for key testudine ecotypes and families. An ordination framework is applied to quantify metrics of niche change (stability, expansion, and unfilling) between the Maastrichtian and present day. Results indicate that niche stability over evolutionary timescales varies between testudine clades. Groups that originated in the Early Cretaceous show climatic niche stability, whereas those diversifying towards the end of the Cretaceous display larger niche expansion towards the modern. Temperature is the dominant driver of modern and past distributions, whereas precipitation is important for freshwater turtle ranges. Our findings demonstrate that testudines were able to occupy warmer climates than present day in the geological record. However, the projected rate and magnitude of future environmental change, in concert with other conservation threats, presents challenges for acclimation or adaptation. PMID:27655766
Mihailović, D T; Drešković, N; Arsenić, I; Ćirić, V; Djurdjević, V; Mimić, G; Pap, I; Balaž, I
2016-11-15
We considered temporal and spatial variations to the thermal and moisture regimes of the most common RSGs (Reference Soil Groups) in Serbia under the A1B scenario for the 2021-2050 and 2071-2100 periods, with respect to the 1961-1990 period. We utilized dynamically downscaled global climate simulations from the ECHAM5 model using the coupled regional climate model EBU-POM (Eta Belgrade University-Princeton Ocean Model). We analysed the soil temperature and moisture time series using simple statistics and a Kolmogorov complexity (KC) analysis. The corresponding metrics were calculated for 150 sites. In the future, warmer and drier regimes can be expected for all RSGs in Serbia. The calculated soil temperature and moisture variations include increases in the mean annual soil temperature (up to 3.8°C) and decreases in the mean annual soil moisture (up to 11.3%). Based on the KC values, the soils in Serbia are classified with respect to climate change impacts as (1) less sensitive (Vertisols, Umbrisols and Dystric Cambisols) or (2) more sensitive (Chernozems, Eutric Cambisols and Planosols). Copyright © 2016 Elsevier B.V. All rights reserved.
Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review
NASA Astrophysics Data System (ADS)
Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van
2013-04-01
Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions; adaptive approach that provides inherent flexibility and reversibility and avoids closing off options; importance of active learning. References: Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012). Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, 252 p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263 Willems, P., Arnbjerg-Nielsen, K., Olsson, J., Nguyen, V.T.V. (2012), 'Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings', Atmospheric Research, 103, 106-118
Flexible climate modeling systems: Lessons from Snowball Earth, Titan and Mars
NASA Astrophysics Data System (ADS)
Pierrehumbert, R. T.
2007-12-01
Climate models are only useful to the extent that real understanding can be extracted from them. Most leading- edge problems in climate change, paleoclimate and planetary climate require a high degree of flexibility in terms of incorporating model physics -- for example in allowing methane or CO2 to be a condensible substance instead of water vapor. This puts a premium on model design that allows easy modification, and on physical parameterizations that are close to fundamentals with as little empirical ad-hoc formulation as possible. I will provide examples from two approaches to this problem we have been using at the University of Chicago. The first is the FOAM general circulation model, which is a clean single-executable Fortran-77/c code supported by auxiliary applications in Python and Java. The second is a new approach based on using Python as a shell for assembling building blocks in compiled-code into full models. Applications to Snowball Earth, Titan and Mars, as well as pedagogical uses, will be discussed. One painful lesson we have learned is that Fortran-95 is a major impediment to portability and cross-language interoperability; in this light the trend toward Fortran-95 in major modelling groups is seen as a significant step backwards. In this talk, I will focus on modeling projects employing a full representation of atmospheric fluid dynamics, rather than "intermediate complexity" models in which the associated transports are parameterized.
NASA Astrophysics Data System (ADS)
Prokopy, L. S.; Widhalm, M.
2014-12-01
There is a close connection between weather and climate patterns and successful agricultural production. Therefore, incorporating climate information into farm management is likely to reduce the risk of economic losses and increase profitability. While weather and climate information is becoming ever more abundant and accessible, the use of such information in the agricultural community remains limited. Useful to Usable (U2U): Transforming Climate Variability and Change Information for Cereal Crop Producers is a USDA-NIFA funded research and extension project focused on improving the use of climate information for agricultural production in the Midwestern United States by developing user-driven decision tools and training resources. The U2U team is a diverse and uniquely qualified group of climatologists, crop modelers, agronomists, and social scientists from 9 Midwestern universities and two NOAA Regional Climate Centers. Together, we strive to help producers make better long-term plans on what, when and where to plant and also how to manage crops for maximum yields and minimum environmental damage. To ensure relevance and usability of U2U products, our social science team is using a number of techniques including surveys and focus groups to integrate stakeholder interests, needs, and concerns into all aspects of U2U research. It is through this coupling of physical and social science disciplines that we strive to transform existing climate information into actionable knowledge.
NASA Astrophysics Data System (ADS)
Kim, Go-Un; Seo, Kyong-Hwan
2018-01-01
A key physical factor in regulating the performance of Madden-Julian oscillation (MJO) simulation is examined by using 26 climate model simulations from the World Meteorological Organization's Working Group for Numerical Experimentation/Global Energy and Water Cycle Experiment Atmospheric System Study (WGNE and MJO-Task Force/GASS) global model comparison project. For this, intraseasonal moisture budget equation is analyzed and a simple, efficient physical quantity is developed. The result shows that MJO skill is most sensitive to vertically integrated intraseasonal zonal wind convergence (ZC). In particular, a specific threshold value of the strength of the ZC can be used as distinguishing between good and poor models. An additional finding is that good models exhibit the correct simultaneous convection and large-scale circulation phase relationship. In poor models, however, the peak circulation response appears 3 days after peak rainfall, suggesting unfavorable coupling between convection and circulation. For an improving simulation of the MJO in climate models, we propose that this delay of circulation in response to convection needs to be corrected in the cumulus parameterization scheme.
NASA Astrophysics Data System (ADS)
Williams, D. N.
2015-12-01
Progress in understanding and predicting climate change requires advanced tools to securely store, manage, access, process, analyze, and visualize enormous and distributed data sets. Only then can climate researchers understand the effects of climate change across all scales and use this information to inform policy decisions. With the advent of major international climate modeling intercomparisons, a need emerged within the climate-change research community to develop efficient, community-based tools to obtain relevant meteorological and other observational data, develop custom computational models, and export analysis tools for climate-change simulations. While many nascent efforts to fill these gaps appeared, they were not integrated and therefore did not benefit from collaborative development. Sharing huge data sets was difficult, and the lack of data standards prevented the merger of output data from different modeling groups. Thus began one of the largest-ever collaborative data efforts in climate science, resulting in the Earth System Grid Federation (ESGF), which is now used to disseminate model, observational, and reanalysis data for research assessed by the Intergovernmental Panel on Climate Change (IPCC). Today, ESGF is an open-source petabyte-level data storage and dissemination operational code-base that manages secure resources essential for climate change study. It is designed to remain robust even as data volumes grow exponentially. The internationally distributed, peer-to-peer ESGF "data cloud" archive represents the culmination of an effort that began in the late 1990s. ESGF portals are gateways to scientific data collections hosted at sites around the globe that allow the user to register and potentially access the entire ESGF network of data and services. The growing international interest in ESGF development efforts has attracted many others who want to make their data more widely available and easy to use. For example, the World Climate Research Program, which provides governance for CMIP, has now endorsed the ESGF software foundation to be used for ~70 other model intercomparison projects (MIPs), such as obs4MIPs, TAMIP, CFMIP, and GeoMIP. At present, more than 40 projects disseminate their data via ESGF.
Diagnostic indicators for integrated assessment models of climate policy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kriegler, Elmar; Petermann, Nils; Krey, Volker
2015-01-01
Integrated assessments of how climate policy interacts with energy-economic systems can be performed by a variety of models with different functional structures. This article proposes a diagnostic scheme that can be applied to a wide range of integrated assessment models to classify differences among models based on their carbon price responses. Model diagnostics can uncover patterns and provide insights into why, under a given scenario, certain types of models behave in observed ways. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnosticmore » indicators to characterize model responses to carbon price signals and test these in a diagnostic study with 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to more easily explain variations among policy-relevant model results.« less
Development of a system emulating the global carbon cycle in Earth system models
NASA Astrophysics Data System (ADS)
Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.
2010-08-01
Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).
ERIC Educational Resources Information Center
Higdon, Julia Dianne
2015-01-01
European nations, built on democratic foundations, rely on participation that is inclusive of all groups. Among efforts to support social cohesion in Europe, investigating the development of intercultural attitudes--attitudes toward others on the basis of their intersecting group memberships--is a crucial area of research. Further, examining…
Evteev, Andrej A; Movsesian, Alla A; Grosheva, Alexandra N
2017-06-01
The climate of northeastern Europe is likely to resemble in many ways Late Pleistocene periglacial conditions in Europe, but there have been relatively few studies exploring the association between climate and morphology in the mid-face of modern northeastern European populations. To fill this gap, we sampled 540 male skulls from 22 European and Near Eastern groups, including 314 skulls from 11 populations from northeastern Europe, to test for possible climate-morphology association at the continental scale. Our results found a moderate and highly significant association (R = 0.48, p = 0.0013, Mantel test) between sets of 23 mid-facial measurements and eight climatic variables. A partial least squares analysis revealed this association to be mostly driven by differences between groups from northeastern Europe and populations from the Mediterranean and the Caucasus. Matrices of between-group genetic distances based on Y-chromosome and mtDNA markers, as well as cranial non-metric and geographic distance matrices, were used to control for the possible influence of shared population history. Irrespective of which measure of neutral between-population distances is taken into account, the association between cranial variables and climate remains significant. The pattern of association between climate and morphology of the mid-face in western Eurasia was then compared to that in east and north Asia. Although differences between the two were found, there were also similarities that support existing functional interpretations of morphology for the bony parts of the upper airways. Last, in a preliminary analysis using a reduced set of measurements, mid-facial morphology of several Upper Paleolithic European Homo sapiens specimens was found to be more similar to groups from northern and northeastern Europe than to southern European populations. Thus, the population of northeastern Europe rather than east and north Asian groups should be used as a model when studying climate-mediated mid-facial morphology of Upper Paleolithic European H. sapiens. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Rosenzweig, C.
2011-12-01
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 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. Recent progress and the current status of AgMIP will be presented, highlighting three areas of activity: preliminary results from crop pilot studies, outcomes from regional workshops, and emerging scientific challenges. AgMIP crop modeling efforts are being led by pilot studies, which have been established for wheat, maize, rice, and sugarcane. These crop-specific initiatives have proven instrumental in testing and contributing to AgMIP protocols, as well as creating preliminary results for aggregation and input to agricultural trade models. Regional workshops are being held to encourage collaborations and set research activities in motion for key agricultural areas. The first of these workshops was hosted by Embrapa and UNICAMP and held in Campinas, Brazil. Outcomes from this meeting have informed crop modeling research activities within South America, AgMIP protocols, and future regional workshops. Several scientific challenges have emerged and are currently being addressed by AgMIP researchers. Areas of particular interest include geospatial weather generation, ensemble methods for climate scenarios and crop models, spatial aggregation of field-scale yields to regional and global production, and characterization of future changes in climate variability.
Multilevel models in the explanation of the relationship between safety climate and safe behavior.
Cheyne, Alistair; Tomás, José M; Oliver, Amparo
2013-01-01
This study examines the relationships between components of organizational safety climate, including employee attitudes to organizational safety issues; perceptions of the physical working environment, and evaluations of worker engagement with safety issues; and relates these to self-reported levels of safety behavior. It attempts to explore the relationships between these variables in 1189 workers across 78 work groups in a large transportation organization. Evaluations of safety climate, the working environment and worker engagement, as well as safe behaviors, were collected using a self report questionnaire. The multilevel analysis showed that both levels of evaluation (the work group and the individual), and some cross-level interactions, were significant in explaining safe behaviors. Analyses revealed that a number of variables, at both levels, were associated with worker engagement and safe behaviors. The results suggest that, while individual evaluations of safety issues are important, there is also a role for the fostering of collective safety climates in encouraging safe behaviors and therefore reducing accidents.
NASA Astrophysics Data System (ADS)
Tuddenham, P.; Bishop, K.; Walters, H.; Carley, S.
2011-12-01
The Great Lakes Climate Change Science and Education Systemic Network (GLCCSESN) project is an NSF-funded CCEP program awarded to Eastern Michigan University in 2010. The College of Exploration is one of the project partners and has conducted a series of online surveys, workshop and focus group to identify a wide range of organizations, individuals, resources and needs related to climate change education and research activities in and about the Great Lakes Region and to provide information about climate change science to the education community. One of the first steps taken to build this community was to build a web site that features a dynamic online map of individuals and organizations concerned about climate change as well as interested in resources and activities specific to the Great Lakes. Individuals and organizations have been, and are still, invited to put themselves on the map at http://greatlakesclimate.org This map of the Great Lakes region provides both a visual representation of activities and resources as well as a database of climate change activities. This map will grow over time as more people and organizations put themselves on the map. The use of online technologies has helped broaden the participation and representation in the GLCCSESN from all states/provinces in the Great Lakes region, encouraging diverse audiences and stakeholders, including scientists, educators, and journalists, etc.to engage with the project. In the fall of 2011 a combined online professional development workshop and focus group is planned. Educators and scientists working on climate change studies and issues related to the Great Lakes will be sharing their work and expertise in an online workshop and focus group. Following the professional development activity a focus group will be conducted online using a model developed as part of a NSF funded COSEE project. The focus group purpose is to review current educational resources and to identify gaps and needs for further educational programs, materials and resources. The online format will encourage and support widespread participation across the Great Lakes region. Data from the needs assessment surveys will provide a foundation for online focus group discussion questions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
van der Zwaan, Bob; Calvin, Katherine V.; Clarke, Leon E.
The CLIMACAP-LAMP project, completed in December 2015, was an inter-model comparison exercise that focused on energy and climate change economics issues in Latin America. The project partners – co-financed by the EC / EuropeAid (CLIMACAP part) and EPA / USAID (LAMP part) and co-coordinated by respectively the Energy research Centre of the Netherlands (ECN) and the Pacific Northwest National Laboratory (PNNL) – report their main and detailed findings in this Special Issue of Energy Economics, exclusively dedicated to climate mitigation, low-carbon development and implications for energy and land use in Latin America. Our research endeavor included several of the mostmore » prominent regional energy modeling groups from Latin America, as well as a representative set of global integrated assessment modeling groups from a number of institutions from Europe and the US. About two dozen universities, research groups and environmental or consulting organizations took part in the CLIMACAP-LAMP cross-model comparison project, from both sides of the Atlantic. Over a handful of workshops were organized over the past four years in several countries in Latin America, attended by between 30 and 50 participants from, amongst others, Argentina, Brazil, Colombia, Mexico, the EU, and the US.« less
NASA Astrophysics Data System (ADS)
Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre; Bopp, Laurent; Brovkin, Victor; Dunne, John; Graven, Heather; Hoffman, Forrest; Ilyina, Tatiana; John, Jasmin G.; Jung, Martin; Kawamiya, Michio; Koven, Charlie; Pongratz, Julia; Raddatz, Thomas; Randerson, James T.; Zaehle, Sönke
2016-08-01
Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.
Supervising simulations with the Prodiguer Messaging Platform
NASA Astrophysics Data System (ADS)
Greenslade, Mark; Carenton, Nicolas; Denvil, Sebastien
2015-04-01
At any one moment in time, researchers affiliated with the Institut Pierre Simon Laplace (IPSL) climate modeling group, are running hundreds of global climate simulations. These simulations execute upon a heterogeneous set of High Performance Computing (HPC) environments spread throughout France. The IPSL's simulation execution runtime is called libIGCM (library for IPSL Global Climate Modeling group). libIGCM has recently been enhanced so as to support realtime operational use cases. Such use cases include simulation monitoring, data publication, environment metrics collection, automated simulation control … etc. At the core of this enhancement is the Prodiguer messaging platform. libIGCM now emits information, in the form of messages, for remote processing at IPSL servers in Paris. The remote message processing takes several forms, for example: 1. Persisting message content to database(s); 2. Notifying an operator of changes in a simulation's execution status; 3. Launching rollback jobs upon simulation failure; 4. Dynamically updating controlled vocabularies; 5. Notifying downstream applications such as the Prodiguer web portal; We will describe how the messaging platform has been implemented from a technical perspective and demonstrate the Prodiguer web portal receiving realtime notifications.
From the Last Interglacial to the Anthropocene: Modelling a Complete Glacial Cycle (PalMod)
NASA Astrophysics Data System (ADS)
Brücher, Tim; Latif, Mojib
2017-04-01
We will give a short overview and update on the current status of the national climate modelling initiative PalMod (Paleo Modelling, www.palmod.de). PalMod focuses on the understanding of the climate system dynamics and its variability during the last glacial cycle. The initiative is funded by the German Federal Ministry of Education and Research (BMBF) and its specific topics are: (i) to identify and quantify the relative contributions of the fundamental processes which determined the Earth's climate trajectory and variability during the last glacial cycle, (ii) to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial - the Eemian warm period - up to the present, including the changes in the spectrum of variability, and (iii) to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way. The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. PalMod kicked off in February 2016. The first phase focuses on the last deglaciation (app. the last 23.000 years). From the ESM perspective PalMod pushes forward model development by coupling ESM with dynamical ice sheet models. Computer scientists work on speeding up climate models using different concepts (like parallelisation in time) and one working group is dedicated to perform a comprehensive data synthesis to validate model performance. The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community. The consortium consists of 18 partners including all major modelling centers within Germany. The funding comprises approximately 65 PostDoc positions and more than 120 scientists are involved. PalMod is coordinated at the Helmholtz Centre for Ocean Research Kiel (GEOMAR).
Maguire, Kaitlin C; Shinneman, Douglas J; Potter, Kevin M; Hipkins, Valerie D
2018-03-14
Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.
Maguire, Kaitlin C.; Shinneman, Douglas; Potter, Kevin M.; Hipkins, Valerie D.
2018-01-01
Unique responses to climate change can occur across intraspecific levels, resulting in individualistic adaptation or movement patterns among populations within a given species. Thus, the need to model potential responses among genetically distinct populations within a species is increasingly recognized. However, predictive models of future distributions are regularly fit at the species level, often because intraspecific variation is unknown or is identified only within limited sample locations. In this study, we considered the role of intraspecific variation to shape the geographic distribution of ponderosa pine (Pinus ponderosa), an ecologically and economically important tree species in North America. Morphological and genetic variation across the distribution of ponderosa pine suggest the need to model intraspecific populations: the two varieties (var. ponderosa and var. scopulorum) and several haplotype groups within each variety have been shown to occupy unique climatic niches, suggesting populations have distinct evolutionary lineages adapted to different environmental conditions. We utilized a recently-available, geographically-widespread dataset of intraspecific variation (haplotypes) for ponderosa pine and a recently-devised lineage distance modeling approach to derive additional, likely intraspecific occurrence locations. We confirmed the relative uniqueness of each haplotype-climate relationship using a niche-overlap analysis, and developed ecological niche models (ENMs) to project the distribution for two varieties and eight haplotypes under future climate forecasts. Future projections of haplotype niche distributions generally revealed greater potential range loss than predicted for the varieties. This difference may reflect intraspecific responses of distinct evolutionary lineages. However, directional trends are generally consistent across intraspecific levels, and include a loss of distributional area and an upward shift in elevation. Our results demonstrate the utility in modeling intraspecific response to changing climate and they inform management and conservation strategies, by identifying haplotypes and geographic areas that may be most at risk, or most secure, under projected climate change.
Structural Model Error and Decision Relevancy
NASA Astrophysics Data System (ADS)
Goldsby, M.; Lusk, G.
2017-12-01
The extent to which climate models can underwrite specific climate policies has long been a contentious issue. Skeptics frequently deny that climate models are trustworthy in an attempt to undermine climate action, whereas policy makers often desire information that exceeds the capabilities of extant models. While not skeptics, a group of mathematicians and philosophers [Frigg et al. (2014)] recently argued that even tiny differences between the structure of a complex dynamical model and its target system can lead to dramatic predictive errors, possibly resulting in disastrous consequences when policy decisions are based upon those predictions. They call this result the Hawkmoth effect (HME), and seemingly use it to rebuke rightwing proposals to forgo mitigation in favor of adaptation. However, a vigorous debate has emerged between Frigg et al. on one side and another philosopher-mathematician pair [Winsberg and Goodwin (2016)] on the other. On one hand, Frigg et al. argue that their result shifts the burden to climate scientists to demonstrate that their models do not fall prey to the HME. On the other hand, Winsberg and Goodwin suggest that arguments like those asserted by Frigg et al. can be, if taken seriously, "dangerous": they fail to consider the variety of purposes for which models can be used, and thus too hastily undermine large swaths of climate science. They put the burden back on Frigg et al. to show their result has any effect on climate science. This paper seeks to attenuate this debate by establishing an irenic middle position; we find that there is more agreement between sides than it first seems. We distinguish a `decision standard' from a `burden of proof', which helps clarify the contributions to the debate from both sides. In making this distinction, we argue that scientists bear the burden of assessing the consequences of HME, but that the standard Frigg et al. adopt for decision relevancy is too strict.
Climate Variability and Human Migration in the Netherlands, 1865–1937
Jennings, Julia A.; Gray, Clark L.
2014-01-01
Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689
NASA Astrophysics Data System (ADS)
Bussi, Gianbattista; Whitehead, Paul; Dadson, Simon
2016-04-01
In this study, we assess the impact of changes in precipitation and temperature on the phytoplankton concentration of the River Thames (UK) by means of a physically-based model. A scenario-neutral approach was employed to evaluate the effects of climate variability on flow, phosphorus concentration and phytoplankton concentration. In particular, the impact of uniform changes in precipitation and temperature on five groups of phytoplankton (diatoms and large chlorophytes, other chlorophytes, picoalgae, Microcystis-like cyanobacteria and other cyanobacteria) was assessed under three different land-use/land-management scenarios (1 - current land use and phosphorus reduction practices; 2 - expansion of agricultural land and current phosphorus reduction practices; 3 - expansion of agricultural land and optimal phosphorus reduction practices). The model results were assessed within the framework of future climate projections, using the UK Climate Projections 09 (UKCP09) for the 2030s. The results of the model demonstrate that an increase in average phytoplankton concentration due to climate change is highly likely to occur, and its magnitude varies depending on the river reach. Cyanobacteria show significant increases under future climate change and land-use change. An expansion of intensive agriculture accentuates the growth in phytoplankton, especially in the upper reaches of the River Thames. However, an optimal phosphorus removal mitigation strategy, which combines reduction of fertiliser application and phosphorus removal from wastewater, can help to reduce this increase in phytoplankton concentration, and in some cases, compensate for the effect of rising temperature.
The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0
NASA Astrophysics Data System (ADS)
Valdes, Paul J.; Armstrong, Edward; Badger, Marcus P. S.; Bradshaw, Catherine D.; Bragg, Fran; Crucifix, Michel; Davies-Barnard, Taraka; Day, Jonathan J.; Farnsworth, Alex; Gordon, Chris; Hopcroft, Peter O.; Kennedy, Alan T.; Lord, Natalie S.; Lunt, Dan J.; Marzocchi, Alice; Parry, Louise M.; Pope, Vicky; Roberts, William H. G.; Stone, Emma J.; Tourte, Gregory J. L.; Williams, Jonny H. T.
2017-10-01
Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.
Do Responses to Different Anthropogenic Forcings Add Linearly in Climate Models?
NASA Technical Reports Server (NTRS)
Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; Bonfils, Celine; LeGrande, Allegra N.; Nazarenko, Larissa; Tsigaridis, Kostas
2015-01-01
Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings; however, we demonstrate that there are significant nonlinearities in precipitation responses to di?erent forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to di?erences in ozone forcing arising from interactions between forcing agents. Our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.
Do responses to different anthropogenic forcings add linearly in climate models?
Marvel, Kate; Schmidt, Gavin A.; Shindell, Drew; ...
2015-10-14
Many detection and attribution and pattern scaling studies assume that the global climate response to multiple forcings is additive: that the response over the historical period is statistically indistinguishable from the sum of the responses to individual forcings. Here, we use the NASA Goddard Institute for Space Studies (GISS) and National Center for Atmospheric Research Community Climate System Model (CCSM4) simulations from the CMIP5 archive to test this assumption for multi-year trends in global-average, annual-average temperature and precipitation at multiple timescales. We find that responses in models forced by pre-computed aerosol and ozone concentrations are generally additive across forcings. However,more » we demonstrate that there are significant nonlinearities in precipitation responses to different forcings in a configuration of the GISS model that interactively computes these concentrations from precursor emissions. We attribute these to differences in ozone forcing arising from interactions between forcing agents. Lastly, our results suggest that attribution to specific forcings may be complicated in a model with fully interactive chemistry and may provide motivation for other modeling groups to conduct further single-forcing experiments.« less
Fight Swack, Adapt to Climate Change or How to Use Humor to Engage the Public in Climate Issues
NASA Astrophysics Data System (ADS)
Ellis, R.; Elinich, K.; Johnson, R.; Fink, J.; Crawford, J.
2014-12-01
We are carefully considering how a humor-based campaign can help us communicate important climate change messages. Using pilot campaign strategies, we have engaged local residents in focus groups and interviews to understand how effective the approach can be. Growing educational research suggests learning about climate change can lead to feelings of depression, fear and inaction. Climate change seems too big of a task to take on. But with sweaty back (or "swack" as it's known in some circles), there's a public enemy that can be defeated. As only one piece of an innovative model for informal climate change education, the Climate and Urban Systems Partnership repositions the war on climate change by declaring a war on swack instead. This way, we can talk about climate change in a way it has never been talked about before that will certainly get people's attention. It also answers the common question of, "Yeah, but how does it affect me?" We're educating about responses to climate change because heat waves, floods, and excessive back sweat all kinda suck a lot.
Global Crop Yields, Climatic Trends and Technology Enhancement
NASA Astrophysics Data System (ADS)
Najafi, E.; Devineni, N.; Khanbilvardi, R.; Kogan, F.
2016-12-01
During the last decades the global agricultural production has soared up and technology enhancement is still making positive contribution to yield growth. However, continuing population, water crisis, deforestation and climate change threaten the global food security. Attempts to predict food availability in the future around the world can be partly understood from the impact of changes to date. A new multilevel model for yield prediction at the country scale using climate covariates and technology trend is presented in this paper. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling and/or clustering to automatically group and reduce estimation uncertainties. El Niño Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), Geopotential height (GPH), historical CO2 level and time-trend as a relatively reliable approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2007. Results show that these indicators can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications.
Predicting summer residential electricity demand across the U.S.A using climate information
NASA Astrophysics Data System (ADS)
Sun, X.; Wang, S.; Lall, U.
2017-12-01
We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.
A test of the cross-scale resilience model: Functional richness in Mediterranean-climate ecosystems
Wardwell, D.A.; Allen, Craig R.; Peterson, G.D.; Tyre, A.J.
2008-01-01
Ecological resilience has been proposed to be generated, in part, in the discontinuous structure of complex systems. Environmental discontinuities are reflected in discontinuous, aggregated animal body mass distributions. Diversity of functional groups within body mass aggregations (scales) and redundancy of functional groups across body mass aggregations (scales) has been proposed to increase resilience. We evaluate that proposition by analyzing mammalian and avian communities of Mediterranean-climate ecosystems. We first determined that body mass distributions for each animal community were discontinuous. We then calculated the variance in richness of function across aggregations in each community, and compared observed values with distributions created by 1000 simulations using a null of random distribution of function, with the same n, number of discontinuities and number of functional groups as the observed data. Variance in the richness of functional groups across scales was significantly lower in real communities than in simulations in eight of nine sites. The distribution of function across body mass aggregations in the animal communities we analyzed was non-random, and supports the contentions of the cross-scale resilience model. ?? 2007 Elsevier B.V. All rights reserved.
Yang, Guo-Jing; Utzinger, Jürg; Lv, Shan; Qian, Ying-Jun; Li, Shi-Zhu; Wang, Qiang; Bergquist, Robert; Vounatsou, Penelope; Li, Wei; Yang, Kun; Zhou, Xiao-Nong
2010-01-01
Climate change-according to conventional wisdom-will result in an expansion of tropical parasitic diseases in terms of latitude and altitude, with vector-borne diseases particularly prone to change. However, although a significant rise in temperature occurred over the past century, there is little empirical evidence whether climate change has indeed favoured infectious diseases. This might be explained by the complex relationship between climate change and the frequency and the transmission dynamics of infectious diseases, which is characterised by nonlinear associations and countless other complex factors governing the distribution of infectious diseases. Here, we explore whether and how climate change might impact on diseases targeted by the Regional Network for Asian Schistosomiasis and Other Helminth Zoonoses (RNAS(+)). We start our review with a short summary of the current evidence-base how climate change affects the distribution of infectious diseases. Next, we introduce biology-based models for predicting the distribution of infectious diseases in a future, warmer world. Two case studies are presented: the classical RNAS(+) disease schistosomiasis and an emerging disease, angiostrongyliasis, focussing on their occurrences in the People's Republic of China. Strengths and limitations of current models for predicting the impact of climate change on infectious diseases are discussed, and we propose model extensions to include social and ecological factors. Finally, we recommend that mitigation and adaptation strategies to diminish potential negative effects of climate change need to be developed in concert with key stakeholders so that surveillance and early-warning systems can be strengthened and the most vulnerable population groups protected. Copyright 2010 Elsevier Ltd. All rights reserved.
Participatory Scenario Planning for Climate Change Adaptation: the Maui Groundwater Project
NASA Astrophysics Data System (ADS)
Keener, V. W.; Brewington, L.; Finucane, M.
2015-12-01
For the last century, the island of Maui in Hawai'i has been the center of environmental, agricultural, and legal conflict with respect to both surface and groundwater allocation. Planning for sustainable future freshwater supply in Hawai'i requires adaptive policies and decision-making that emphasizes private and public partnerships and knowledge transfer between scientists and non-scientists. We have downscaled dynamical climate models to 1 km resolution in Maui and coupled them with a USGS Water Budget model and a participatory scenario building process to quantify future changes in island-scale climate and groundwater recharge under different land uses. Although these projections are uncertain, the integrated nature of the Pacific RISA research program has allowed us to take a multi-pronged approach to facilitate the uptake of climate information into policy and management. This presentation details the ongoing work to support the development of Hawai'i's first island-wide water use plan under the new climate adaptation directive. Participatory scenario planning began in 2012 to bring together a diverse group of ~100 decision-makers in state and local government, watershed restoration, agriculture, and conservation to 1) determine the type of information (climate variables, land use and development, agricultural practices) they would find helpful in planning for climate change, and 2) develop a set of nested scenarios that represent alternative climate and management futures. This integration of knowledge is an iterative process, resulting in flexible and transparent narratives of complex futures comprised of information at multiple scales. We will present an overview of the downscaling, scenario building, hydrological modeling processes, and stakeholder response.
Selection of climate policies under the uncertainties in the Fifth Assessment Report of the IPCC
NASA Astrophysics Data System (ADS)
Drouet, L.; Bosetti, V.; Tavoni, M.
2015-10-01
Strategies for dealing with climate change must incorporate and quantify all the relevant uncertainties, and be designed to manage the resulting risks. Here we employ the best available knowledge so far, summarized by the three working groups of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5; refs , , ), to quantify the uncertainty of mitigation costs, climate change dynamics, and economic damage for alternative carbon budgets. We rank climate policies according to different decision-making criteria concerning uncertainty, risk aversion and intertemporal preferences. Our findings show that preferences over uncertainties are as important as the choice of the widely discussed time discount factor. Climate policies consistent with limiting warming to 2 °C above preindustrial levels are compatible with a subset of decision-making criteria and some model parametrizations, but not with the commonly adopted expected utility framework.
Final Technical Report for Project "Improving the Simulation of Arctic Clouds in CCSM3"
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stephen J. Vavrus
2008-11-15
This project has focused on the simulation of Arctic clouds in CCSM3 and how the modeled cloud amount (and climate) can be improved substantially by altering the parameterized low cloud fraction. The new formula, dubbed 'freeezedry', alleviates the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic (Fig. 1). The cloud reduction causes an Arctic-wide drop of 15 W m{sup -2} in surface cloud radiativemore » forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2-8 K over the Arctic Ocean, thus significantly reducing the model's pronounced warm bias (Fig. 1). While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions (Fig. 2) or during summer (Fig. 3), which are space and time domains that were not targeted. Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness, based on the results from the CMIP3 archive (Vavrus et al., 2008). Freezedry also affects CCSM3's sensitivity to greenhouse forcing. In a transient-CO{sub 2} experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5 K and 0.5 K smaller warming, respectively) (Fig. 4). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during non-summer months (when clouds warm the surface), apparently because of the colder modern reference climate. These results of the freezedry parameterization have recently been published (Vavrus and D. Waliser, 2008: An improved parameterization for simulating Arctic cloud amount in the CCSM3 climate model. J. Climate, 21, 5673-5687.). The article also provides a novel synthesis of surface- and satellite-based Arctic cloud observations that show how much the new freezedry parameterization improves the simulated cloud amount in high latitudes (Fig. 3). Freezedry has been incorporated into the CCSM3.5 version, in which it successfully limits the excessive polar clouds, and may be used in CCSM4. Material from this work is also appearing in a synthesis article on future Arctic cloud changes (Vavrus, D. Waliser, J. Francis, and A. Schweiger, 'Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4', accepted in Climate Dynamics) and was used in a collaborative paper on Arctic cloud-sea ice coupling (Schweiger, A., R. Lindsay, S. Vavrus, and J. Francis, 2008: Relationships between Arctic sea ice and clouds during autumn. J. Climate, 21, 4799-4810.). This research was presented at the 2007 CCSM Annual Workshop, as well as the CCSM's 2007 Atmospheric Model Working Group and Polar Working Group Meetings. The findings were also shown at the 2007 Climate Change Prediction Program's Science Team Meeting. In addition, I served as an instructor at the International Arctic Research Center's (IARC) Summer School on Arctic Climate Modeling in Fairbanks this summer, where I presented on the challenges and techniques used in simulating polar clouds. I also contributed to the development of a new Arctic System Model by attending a workshop in Colorado this summer on this fledgling project. Finally, an outreach activity for the general public has been the development of an interactive web site (
Travers-Trolet, Morgane; Shin, Yunne-Jai; Shannon, Lynne J; Moloney, Coleen L; Field, John G
2014-01-01
The effects of climate and fishing on marine ecosystems have usually been studied separately, but their interactions make ecosystem dynamics difficult to understand and predict. Of particular interest to management, the potential synergism or antagonism between fishing pressure and climate forcing is analysed in this paper, using an end-to-end ecosystem model of the southern Benguela ecosystem, built from coupling hydrodynamic, biogeochemical and multispecies fish models (ROMS-N2P2Z2D2-OSMOSE). Scenarios of different intensities of upwelling-favourable wind stress combined with scenarios of fishing top-predator fish were tested. Analyses of isolated drivers show that the bottom-up effect of the climate forcing propagates up the food chain whereas the top-down effect of fishing cascades down to zooplankton in unfavourable environmental conditions but dampens before it reaches phytoplankton. When considering both climate and fishing drivers together, it appears that top-down control dominates the link between top-predator fish and forage fish, whereas interactions between the lower trophic levels are dominated by bottom-up control. The forage fish functional group appears to be a central component of this ecosystem, being the meeting point of two opposite trophic controls. The set of combined scenarios shows that fishing pressure and upwelling-favourable wind stress have mostly dampened effects on fish populations, compared to predictions from the separate effects of the stressors. Dampened effects result in biomass accumulation at the top predator fish level but a depletion of biomass at the forage fish level. This should draw our attention to the evolution of this functional group, which appears as both structurally important in the trophic functioning of the ecosystem, and very sensitive to climate and fishing pressures. In particular, diagnoses considering fishing pressure only might be more optimistic than those that consider combined effects of fishing and environmental variability.
Travers-Trolet, Morgane; Shin, Yunne-Jai; Shannon, Lynne J.; Moloney, Coleen L.; Field, John G.
2014-01-01
The effects of climate and fishing on marine ecosystems have usually been studied separately, but their interactions make ecosystem dynamics difficult to understand and predict. Of particular interest to management, the potential synergism or antagonism between fishing pressure and climate forcing is analysed in this paper, using an end-to-end ecosystem model of the southern Benguela ecosystem, built from coupling hydrodynamic, biogeochemical and multispecies fish models (ROMS-N2P2Z2D2-OSMOSE). Scenarios of different intensities of upwelling-favourable wind stress combined with scenarios of fishing top-predator fish were tested. Analyses of isolated drivers show that the bottom-up effect of the climate forcing propagates up the food chain whereas the top-down effect of fishing cascades down to zooplankton in unfavourable environmental conditions but dampens before it reaches phytoplankton. When considering both climate and fishing drivers together, it appears that top-down control dominates the link between top-predator fish and forage fish, whereas interactions between the lower trophic levels are dominated by bottom-up control. The forage fish functional group appears to be a central component of this ecosystem, being the meeting point of two opposite trophic controls. The set of combined scenarios shows that fishing pressure and upwelling-favourable wind stress have mostly dampened effects on fish populations, compared to predictions from the separate effects of the stressors. Dampened effects result in biomass accumulation at the top predator fish level but a depletion of biomass at the forage fish level. This should draw our attention to the evolution of this functional group, which appears as both structurally important in the trophic functioning of the ecosystem, and very sensitive to climate and fishing pressures. In particular, diagnoses considering fishing pressure only might be more optimistic than those that consider combined effects of fishing and environmental variability. PMID:24710351
NASA Astrophysics Data System (ADS)
Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara
2013-04-01
Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through unified graphical web-interface. Partial support of RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2 and Projects 69, 131, 140 and APN CBA2012-16NSY project is acknowledged.
A New Framework for Cumulus Parametrization - A CPT in action
NASA Astrophysics Data System (ADS)
Jakob, C.; Peters, K.; Protat, A.; Kumar, V.
2016-12-01
The representation of convection in climate model remains a major Achilles Heel in our pursuit of better predictions of global and regional climate. The basic principle underpinning the parametrisation of tropical convection in global weather and climate models is that there exist discernible interactions between the resolved model scale and the parametrised cumulus scale. Furthermore, there must be at least some predictive power in the larger scales for the statistical behaviour on small scales for us to be able to formally close the parametrised equations. The presentation will discuss a new framework for cumulus parametrisation based on the idea of separating the prediction of cloud area from that of velocity. This idea is put into practice by combining an existing multi-scale stochastic cloud model with observations to arrive at the prediction of the area fraction for deep precipitating convection. Using mid-tropospheric humidity and vertical motion as predictors, the model is shown to reproduce the observed behaviour of both mean and variability of deep convective area fraction well. The framework allows for the inclusion of convective organisation and can - in principle - be made resolution-aware or resolution-independent. When combined with simple assumptions about cloud-base vertical motion the model can be used as a closure assumption in any existing cumulus parametrisation. Results of applying this idea in the the ECHAM model indicate significant improvements in the simulation of tropical variability, including but not limited to the MJO. This presentation will highlight how the close collaboration of the observational, theoretical and model development community in the spirit of the climate process teams can lead to significant progress in long-standing issues in climate modelling while preserving the freedom of individual groups in pursuing their specific implementation of an agreed framework.
Advances in Cross-Cutting Ideas for Computational Climate Science
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ng, Esmond; Evans, Katherine J.; Caldwell, Peter
This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less
Advances in Cross-Cutting Ideas for Computational Climate Science
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ng, E.; Evans, K.; Caldwell, P.
This report presents results from the DOE-sponsored workshop titled, Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1)more » process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.« less
Fu, Baihua; Pollino, Carmel A; Cuddy, Susan M; Andrews, Felix
2015-07-01
Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Williams, J. W.; Blois, J.; Ferrier, S.; Manion, G.; Fitzpatrick, M.; Veloz, S.; He, F.; Liu, Z.; Otto-Bliesner, B. L.
2011-12-01
In Quaternary paleoecology and paleoclimatology, compositionally dissimilar fossil assemblages usually indicate dissimilar environments; this relationship underpins assemblage-level techniques for paleoenvironmental reconstruction such as mutual climatic ranges or the modern analog technique. However, there has been relatively little investigation into the form of the relationship between compositional dissimilarity and climatic dissimilarity. Here we apply generalized dissimilarity modeling (GDM; Ferrier et al. 2007) as a tool for modeling the expected non-linear relationships between compositional and climatic dissimilarity. We use the CCSM3.0 transient paleoclimatic simulations from the SynTrace working group (Liu et al. 2009) and a new generation of fossil pollen maps from eastern North America (Blois et al. 2011) to 1) assess the spatial relationships between compositional dissimilarity and climatic dissimilarity and 2) whether these spatial relationships change over time. We used a taxonomic list of 106 genus-level pollen types, six climatic variables (winter precipitation and mean temperature, summer precipitation and temperature, seasonality of precipitation, and seasonality of temperature) that were chosen to minimize collinearity, and a cross-referenced pollen and climate dataset mapped for time slices spaced 1000 years apart. When GDM was trained for one time slice, the correlation between predicted and observed spatial patterns of community dissimilarity for other times ranged between 0.3 and 0.73. The selection of climatic predictor variables changed over time, as did the form of the relationship between compositional turnover and climatic predictors. Summer temperature was the only variable selected for all time periods. These results thus suggest that the relationship between compositional dissimilarity in pollen assemblages (and, by implication, beta diversity in plant communities) and climatic dissimilarity can change over time, for reasons to be further studied.
Isoprene derived secondary organic aerosol in a global aerosol chemistry climate model
NASA Astrophysics Data System (ADS)
Stadtler, Scarlet; Kühn, Thomas; Taraborrelli, Domenico; Kokkola, Harri; Schultz, Martin
2017-04-01
Secondary organic aerosol (SOA) impacts earth's climate and human health. Since its precursor chemistry and its formation are not fully understood, climate models cannot catch its direct and indirect effects. Global isoprene emissions are higher than any other non-methane hydrocarbons. Therefore, SOA from isoprene-derived, low volatile species (iSOA) is simulated using a global aerosol chemistry climate model ECHAM6-HAM-SALSA-MOZ. Isoprene oxidation in the chemistry model MOZ is following a novel semi-explicit scheme, embedded in a detailed atmospheric chemical mechanism. For iSOA formation four low volatile isoprene oxidation products were identified. The group method by Nanoonlal et al. 2008 was used to estimate their evaporation enthalpies ΔHvap. To calculate the saturation concentration C∗(T) the sectional aerosol model SALSA uses the gas phase concentrations simulated by MOZ and their corresponding ΔHvap to obtain the saturation vapor pressure p∗(T) from the Clausius Clapeyron equation. Subsequently, the saturation concentration is used to calculate the explicit kinetic partitioning of these compounds forming iSOA. Furthermore, the irreversible heterogeneous reactions of IEPOX and glyoxal from isoprene were included. The possibility of reversible heterogeneous uptake was ignored at this stage, leading to an upper estimate of the contribution of glyoxal to iSOA mass.
Continuously on-going regional climate hindcast simulations for impact applications
NASA Astrophysics Data System (ADS)
Anders, Ivonne; Piringer, Martin; Kaufmann, Hildegard; Knauder, Werner; Resch, Gernot; Andre, Konrad
2017-04-01
Observational data for e.g. temperature, precipitation, radiation, or wind are often used as meteorological forcing for different impact models, like e.g. crop models, urban models, economic models and energy system models. To assess a climate signal, the time period covered by the observation is often too short, they have gaps in between, and are inhomogeneous over time, due to changes in the measurements itself or in the near surrounding. Thus output from global and regional climate models can close the gap and provide homogeneous and physically consistent time series of meteorological parameters. CORDEX evaluation runs performed for the IPCC-AR5 provide a good base for the regional scale. However, with respect to climate services, continuously on-going hindcast simulations are required for regularly updated applications. The Climate Research group at the national Austrian weather service, ZAMG, is focusing on high mountain regions and, especially on the Alps. The hindcast-simulation performed with the regional climate model COSMO-CLM is forced by ERAinterim and optimized for the Alpine Region. The simulation available for the period of 1979-2015 in a spatial resolution of about 10km is prolonged ongoing and fullfils the customer's needs with respect of output variables, levels, intervals and statistical measures. One of the main tasks is to capture strong precipitation events which often occur during summer when low pressure systems develop over the Golf of Genoa, moving to the Northeast. This leads to floods and landslide events in Austria, Czech Republic and Germany. Such events are not sufficiently represented in the CORDEX-evaluation runs. ZAMG use high quality gridded precipitation and temperature data for the Alpine Region (1-6km) to evaluate the model performance. Data is provided e.g. to hydrological modellers (high water, low water), but also to assess icing capability of infrastructure or the calculation the separation distances between livestock farming and residential area.
Impacts of Stratospheric Black Carbon on Agriculture
NASA Astrophysics Data System (ADS)
Xia, L.; Robock, A.; Elliott, J. W.
2017-12-01
A regional nuclear war between India and Pakistan could inject 5 Tg of soot into the stratosphere, which would absorb sunlight, decrease global surface temperature by about 1°C for 5-10 years and have major impacts on precipitation and the amount of solar radiation reaching Earth's surface. Using two global gridded crop models forced by one global climate model simulation, we investigate the impacts on agricultural productivity in various nations. The crop model in the Community Land Model 4.5 (CLM-crop4.5) and the parallel Decision Support System for Agricultural Technology (pDSSAT) in the parallel System for Integrating Impact Models and Sectors are participating in the Global Gridded Crop Model Intercomparison. We force these two crop models with output from the Whole Atmospheric Community Climate Model to characterize the global agricultural impact from climate changes due to a regional nuclear war. Crops in CLM-crop4.5 include maize, rice, soybean, cotton and sugarcane, and crops in pDSSAT include maize, rice, soybean and wheat. Although the two crop models require a different time frequency of weather input, we downscale the climate model output to provide consistent temperature, precipitation and solar radiation inputs. In general, CLM-crop4.5 simulates a larger global average reduction of maize and soybean production relative to pDSSAT. Global rice production shows negligible change with climate anomalies from a regional nuclear war. Cotton and sugarcane benefit from a regional nuclear war from CLM-crop4.5 simulation, and global wheat production would decrease significantly in the pDSSAT simulation. The regional crop yield responses to a regional nuclear conflict are different for each crop, and we present the changes in production on a national basis. These models do not include the crop responses to changes in ozone, ultraviolet radiation, or diffuse radiation, and we would like to encourage more modelers to improve crop models to account for those impacts. We present these results as a demonstration of using different crop models to study this problem, and we invite more global crop modeling groups to use the same climate forcing, which we would be happy to provide, to gain a better understanding of global agricultural responses under different future climate scenarios with stratospheric aerosols.
How much does climate change threaten European forest tree species distributions?
Dyderski, Marcin K; Paź, Sonia; Frelich, Lee E; Jagodziński, Andrzej M
2018-03-01
Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN, and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios-optimistic (RCP2.6), moderate (RCP4.5), and pessimistic (RPC8.5)-using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: "winners"-mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur, and Quercus petraea; "losers"-mostly pioneer species: Betula pendula, Larix decidua, Picea abies, and Pinus sylvestris; and alien species-Pseudotsuga menziesii, Quercus rubra, and Robinia pseudoacacia, which may be also considered as "winners." Assuming limited migration, most of the species studied would face a significant decrease in suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. © 2017 John Wiley & Sons Ltd.
AgMIP: New Results from Sub-Saharan Africa and South Asia Regional Integrated Assessments
NASA Astrophysics Data System (ADS)
Rosenzweig, C.
2014-12-01
AgMIP conducted the first set of comprehensive regional integrated assessments of climate change impacts on smallholder farmers in Sub-Saharan Africa and South Asia led by researchers from the regions themselves. The project developed new methods integrating climate, crop, livestock and economic models to conduct climate change impact assessments that characterize impacts on smallholder groups. AgMIP projections of climate change impacts on agriculture are more realistic than previous assessments because they take agricultural development into account. Using the best available data and models, the assessments directly evaluated yield, income, and poverty outcomes including the effects of adaptation packages and development pathways. Results show that even with agricultural development, climate change generally will exert negative pressure on yields of smallholder farmers in Sub-Saharan Africa and South Asia. Without adaptation, climate change leads to increased poverty in some locations in Sub-Saharan Africa and South Asia compared to a future in which climate change does not occur. Adaptation can significantly improve smallholder farmer responses to climate change. AgMIP expert teams identified improved varieties, sowing practices, fertilizer application, and irrigation applications as prioritized adaptation strategies. These targeted adaptation packages were able to overcome a portion of detrimental impacts but could not compensate completely in many locations. Even in cases where average impact is near zero, vulnerability (i.e., those at risk of loss) can be substantial even when mean impacts are positive.
A cross-assessment of CCI-ECVs and RCSM simulations over the Mediterranean area
NASA Astrophysics Data System (ADS)
D'Errico, Miriam; Planton, Serge; Nabat, Pierre
2017-04-01
A first objective of this study, conducted in the framework of the Climate Modelling Users Group (CMUG), one of the projects of the European Space Agency Climate Change Initiative (ESA CCI) program, is a cross-assessment of simulations of a Med-CORDEX regional climate system model (CNRM-RCSM5) and a sub-set of atmosphere, marine and surface interrelated Satellite-Derived Essential Climate Variables (CCI-ECVs) (i.e. sea surface temperature, sea level, aerosols and soil moisture content) over the Mediterranean area. The consistency between the model and the CCI-ECVs is evaluated through the analysis of a climate specific event that can be observed with the CCI-ECVs, in atmospheric reanalysis and reproduced in the RCSM simulations. In this presentation we focus on the July 2006 heat wave that affected the western part of the Mediterranean continental and marine area. The application of a spectral nudging method using ERA-Interim reanalysis in our simulation allows to reproduce this event with a proper chronology. As a result we show that the consistency between the simulated model aerosol optical depth and the ECV products (being produced by the ESA Aerosol CCI project consortium) depends on the choice of the algorithm used to infer the variable from the satellite observations. In particular the heat wave main characteristics become consistent between the model and the satellite-derived observations for sea surface temperature, soil moisture and sea level. The link between the atmospheric circulation and the aerosols distribution is also investigated.
Psychosocial effects of workplace physical exercise among workers with chronic pain
Andersen, Lars L.; Persson, Roger; Jakobsen, Markus D.; Sundstrup, Emil
2017-01-01
Abstract While workplace physical exercise can help manage musculoskeletal disorders, less is known about psychosocial effects of such interventions. This aim of this study was to investigate the effect of workplace physical exercise on psychosocial factors among workers with chronic musculoskeletal pain. The trial design was a 2-armed parallel-group randomized controlled trial with allocation concealment. A total of 66 slaughterhouse workers (51 men and 15 women, mean age 45 years [standard deviation (SD) 10]) with upper limb chronic musculoskeletal pain were randomly allocated to group-based strength training (physical exercise group) or individual ergonomic training and education (reference group) for 10 weeks. Social climate was assessed with the General Nordic Questionnaire for Psychological and Social Factors at Work, and vitality and mental health were assessed with the 36-item Short Form Health Survey. All scales were converted to 0 to 100 (higher scores are better). Between-group differences from baseline to follow-up were determined using linear mixed models adjusted for workplace, age, gender, and baseline values of the outcome. Mean baseline scores of social climate, mental health, and vitality were 52.2 (SD 14.9), 79.5 (SD 13.7), and 53.9 (SD 19.7), respectively. Complete baseline and follow-up data were obtained from 30 and 31 from the physical exercise and reference groups, respectively. The between-group differences from baseline to follow-up between physical exercise and reference were 7.6 (95% CI 0.3 to 14.9), −2.3 (95% CI -10.3 to 5.8), and 10.1 (95% CI 0.6 to 19.5) for social climate, mental health, and vitality, respectively. For social climate and vitality, this corresponded to moderate effect sizes (Cohen d = 0.51 for both) in favor of physical exercise. There were no reported adverse events. In conclusion, workplace physical exercise performed together with colleagues improves social climate and vitality among workers with chronic musculoskeletal pain. Mental health remained unchanged. PMID:28072707
Andersen, Lars L; Persson, Roger; Jakobsen, Markus D; Sundstrup, Emil
2017-01-01
While workplace physical exercise can help manage musculoskeletal disorders, less is known about psychosocial effects of such interventions. This aim of this study was to investigate the effect of workplace physical exercise on psychosocial factors among workers with chronic musculoskeletal pain.The trial design was a 2-armed parallel-group randomized controlled trial with allocation concealment. A total of 66 slaughterhouse workers (51 men and 15 women, mean age 45 years [standard deviation (SD) 10]) with upper limb chronic musculoskeletal pain were randomly allocated to group-based strength training (physical exercise group) or individual ergonomic training and education (reference group) for 10 weeks. Social climate was assessed with the General Nordic Questionnaire for Psychological and Social Factors at Work, and vitality and mental health were assessed with the 36-item Short Form Health Survey. All scales were converted to 0 to 100 (higher scores are better). Between-group differences from baseline to follow-up were determined using linear mixed models adjusted for workplace, age, gender, and baseline values of the outcome.Mean baseline scores of social climate, mental health, and vitality were 52.2 (SD 14.9), 79.5 (SD 13.7), and 53.9 (SD 19.7), respectively. Complete baseline and follow-up data were obtained from 30 and 31 from the physical exercise and reference groups, respectively. The between-group differences from baseline to follow-up between physical exercise and reference were 7.6 (95% CI 0.3 to 14.9), -2.3 (95% CI -10.3 to 5.8), and 10.1 (95% CI 0.6 to 19.5) for social climate, mental health, and vitality, respectively. For social climate and vitality, this corresponded to moderate effect sizes (Cohen d = 0.51 for both) in favor of physical exercise. There were no reported adverse events.In conclusion, workplace physical exercise performed together with colleagues improves social climate and vitality among workers with chronic musculoskeletal pain. Mental health remained unchanged.
NASA Astrophysics Data System (ADS)
Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.
2014-07-01
Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low resolution climate dynamics and high complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.
NASA Astrophysics Data System (ADS)
Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.
2014-12-01
Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.
The Decadal Climate Prediction Project (DCPP) contribution to CMIP6
Boer, George J.; Smith, Douglas M.; Cassou, Christophe; ...
2016-01-01
The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less
2014-01-01
Background Despite its high number of endemic deciduous broad-leaved species in China’s warm-temperate zone, far less attention has been paid to phylogeographic studies in this region. In this work, the phylogeographic history of Forsythia suspensa endemic to China’s warm-temperate zone was investigated to explore the effect of climate change during the Pleistocene on the distribution of this deciduous broad-leaved species in China. Results The cpDNA data revealed seven phylogeographical groups corresponding to geographical regions. By contrast, the nrDNA data supported the samples clustered into three groups, which was inconsistent with separate geographical regions supported by cpDNA data. Ecological niche modeling showed that the climatically suitable area during the cold period was larger than that during the warm period. Conclusions Both molecular data and ecological niche modeling indicated that F. suspensa expanded to nearby low-elevation plains in the glacial periods, and retreated to mountaintops during interglacial warmer stages. This study thus supported that F. suspensa persisted in situ during the glacial of the Pleistocene with enlarged distribution area, contrary to the hypothesis of long distance southward migration or large-scale range contraction. PMID:24885704
Wallace, J Craig; Popp, Eric; Mondore, Scott
2006-05-01
Building on recent work in occupational safety and climate, the authors examined 2 organizational foundation climates thought to be antecedents of specific safety climate and the relationships among these climates and occupational accidents. It is believed that both foundation climates (i.e., management-employee relations and organizational support) will predict safety climate, which will in turn mediate the relationship between occupational accidents and these 2 distal foundation climates. Using a sample of 9,429 transportation workers in 253 work groups, the authors tested the proposed relationships at the group level. Results supported all hypotheses. Overall it appears that different climates have direct and indirect effects on occupational accidents.
NASA Technical Reports Server (NTRS)
Schwartz, Joel D.; Lee, Mihye; Kinney, Patrick L.; Yang, Suijia; Mills, David; Sarofim, Marcus C.; Jones, Russell; Streeter, Richard; St. Juliana, Alexis; Peers, Jennifer;
2015-01-01
Background: A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships. Methods: We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100. Results: We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April - September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October-March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city. Conclusions: We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change.
NASA Astrophysics Data System (ADS)
Garcia-Mozo, H.; Orlandi, F.; Galan, C.; Fornaciari, M.; Romano, B.; Ruiz, L.; Diaz de La Guardia, C.; Trigo, M. M.; Chuine, I.
2009-03-01
Phenology data are sensitive data to identify how plants are adapted to local climate and how they respond to climatic changes. Modeling flowering phenology allows us to identify the meteorological variables determining the reproductive cycle. Phenology of temperate of woody plants is assumed to be locally adapted to climate. Nevertheless, recent research shows that local adaptation may not be an important constraint in predicting phenological responses. We analyzed variations in flowering dates of Olea europaea L. at different sites of Spain and Italy, testing for a genetic differentiation of flowering phenology among olive varieties to estimate whether local modeling is necessary for olive or not. We build models for the onset and peak dates flowering in different sites of Andalusia and Puglia. Process-based phenological models using temperature as input variable and photoperiod as the threshold date to start temperature accumulation were developed to predict both dates. Our results confirm and update previous results that indicated an advance in olive onset dates. The results indicate that both internal and external validity were higher in the models that used the photoperiod as an indicator to start to cumulate temperature. The use of the unified model for modeling the start and peak dates in the different localities provides standardized results for the comparative study. The use of regional models grouping localities by varieties and climate similarities indicate that local adaptation would not be an important factor in predicting olive phenological responses face to the global temperature increase.
Hilário, R R; Toledo, J J
2016-01-01
Palms, bromeliads and bamboos are key elements of tropical forests and understanding the effects of climate, anthropogenic pressure and forest structure on these groups is crucial to forecast structural changes in tropical forests. Therefore, we investigated the effects of these factors on the abundance of these groups in 22 Atlantic forest fragments of Northeastern Brazil. Abundance of bromeliads and bamboos were assessed through indexes. Palms were counted within a radius of 20 m. We also obtained measures of vegetation structure, fragment size, annual precipitation, precipitation seasonality and human population density. We tested the effects of these predictors on plant groups using path analysis. Palm abundance was higher in taller forests with larger trees, closed canopy and sparse understory, which may be a result of the presence of seed dispersers and specific attributes of local palm species. Bromeliads were negatively affected by both annual precipitation and precipitation seasonality, what may reflect adaptations of these plants to use water efficiently, but also the need to capture water in a regular basis. Bamboos were not related to any predictor variable. As climate and forest structure affected the abundance of bromeliads and palms, human-induced climatic changes and disturbances in forest structure may modify the abundance of these groups. In addition, soil properties and direct measurements of human disturbance should be used in future studies in order to improve the predictability of models about plant groups in Northeastern Atlantic Forest.
NASA Astrophysics Data System (ADS)
Foster, S. Q.; Johnson, R. M.; Carbone, L.; Munoz, R.; Eastburn, T.; Ammann, C.; Lu, G.; Richmond, A.; Committee, S.
2004-12-01
The study of climate and global change is an important on-going focus for scientists at the National Center for Atmospheric Research (NCAR). Programs overseen by the University Corporation for Atmospheric Research Office of Education and Outreach (UCAR-EO) help to translate NCAR's scientific programs, methodologies, and technologies and their societal benefits to over 80,000 visitors to the NCAR Mesa Laboratory each year, including about 10,000 K-12 students. This is currently accomplished through the implementation of an increasingly integrated system of exhibits, guided tours, an audiotour, programs for school groups, and a teachers' guide to the exhibits, which is currently in development. The Climate Discovery Exhibit unveiled in July 2003 and expanded in 2004 offers visitors visually engaging and informative text panels, graphics, artifacts, and interactives describing Sun-Earth connections, dynamic processes that contribute to and mediate climate change, and the Earth's climate history. The exhibit seeks to help visitors to understand why scientists model the global climate system and how information about past and current climate is used to validate models and build scenarios for Earth's future climate. Exhibit-viewers are challenged to ask questions and reflect upon decision making challenges while considering the roles various natural and human-induced factors play in shaping these predictions. With support from NASA and NCAR, a K-12 Teacher's Guide has been developed corresponding the Climate Discovery exhibit's sections addressing the Sun-Earth connection and past climates (the Little Ice Age, in particular). This presentation will review efforts to identify the challenges of communicating with the public and school groups about climate change, while also describing several successful strategies for utilizing visitor questionnaires and interviews to learn how to develop and refine educational resources that will target their interests, bolster their knowledge, and address their misconceptions. Visitors view the exhibit every day of the year on their own, using an audiotour, or with a tour guide. NCAR/UCAR's educational content about climate change is increasingly available to national audiences through the new NCAR EO web site (www.ncar.ucar.edu/eo), Windows to the Universe (www.windows.ucar.edu), UCAR-EO's summer teachers workshops, and sessions at the National Science Teacher Association meetings and other professional education venues.
Jen Der Pan, Peter; Fan, Ai Chun; Bhat, Christine Suniti; Chang, Shona Shih Hua
2012-12-01
In this study, relations among group members' self-concept, verbal behaviors, and group climate early in the group counseling process were assessed for college students who were randomly assigned to four counseling groups. Based on measures from the hill interaction matrix, it was observed that family, social, and action self-concepts, as well as engagement, avoidance, and conflict group climate, were correlated with several verbal behaviors. Silence and quadrant 4 (Q4), which consists of speculative and confrontative verbal behaviors at personal and relationship levels, significantly predicted and explained 43% of the variance in engagement group climate. Silence and Q3, comprised of conventional and assertive verbal behaviors at personal and relationship levels, and Q1, conventional and assertive verbal behaviors at topic and group levels, explained 66% of variance in avoidance climate. Q4 and Silence explained 33% of conflict climate variance early in the group sessions. Implications for research and counseling practice are suggested.
Teesson, M; Newton, N C; Slade, T; Carragher, N; Barrett, E L; Champion, K E; Kelly, E V; Nair, N K; Stapinski, L A; Conrod, P J
2017-07-01
No existing models of alcohol prevention concurrently adopt universal and selective approaches. This study aims to evaluate the first combined universal and selective approach to alcohol prevention. A total of 26 Australian schools with 2190 students (mean age: 13.3 years) were randomized to receive: universal prevention (Climate Schools); selective prevention (Preventure); combined prevention (Climate Schools and Preventure; CAP); or health education as usual (control). Primary outcomes were alcohol use, binge drinking and alcohol-related harms at 6, 12 and 24 months. Climate, Preventure and CAP students demonstrated significantly lower growth in their likelihood to drink and binge drink, relative to controls over 24 months. Preventure students displayed significantly lower growth in their likelihood to experience alcohol harms, relative to controls. While adolescents in both the CAP and Climate groups demonstrated slower growth in drinking compared with adolescents in the control group over the 2-year study period, CAP adolescents demonstrated faster growth in drinking compared with Climate adolescents. Findings support universal, selective and combined approaches to alcohol prevention. Particularly novel are the findings of no advantage of the combined approach over universal or selective prevention alone.
The New APS Topical Group on the Physics of Climate: History, Objectives and Panel Discussion
NASA Astrophysics Data System (ADS)
Brasseur, James; Behringer, Robert
2013-03-01
The GPC Chair will introduce the new APS Topical Group on the Physics of Climate (GPC), describe its history and objectives, and introduce the current GPC leadership before opening the floor to a panel discussion. The GPC resulted from two petitions that emerged from the controversy that followed the APS Statement on Climate Change (see APS website). The two proposals were merged and an organization committee formed by the APS leadership. After a long organizational period in 2011, the GPC bylaws were finalized with the following key objective: The objective of the GPC shall be to promote the advancement and diffusion of knowledge concerning the physics, measurement, and modeling of climate processes, within the domain of natural science and outside the domains of societal impact and policy, legislation and broader societal issues. The objective includes the integration of scientific knowledge and analysis methods across disciplines to address the dynamical complexities and uncertainties of climate physics. The GPC Invited and Focus Sessions at this March meeting are the inaugural GPC events. The Program Committee Chair will moderate a panel between the attending GPC leadership and audience to solicit suggestions for potential future GPC events that advance the GPC objectives.
The highs and lows of cloud radiative feedback: Comparing observational data and CMIP5 models
NASA Astrophysics Data System (ADS)
Jenney, A.; Randall, D. A.
2014-12-01
Clouds play a complex role in the climate system, and remain one of the more difficult aspects of the future climate to predict. Over subtropical eastern ocean basins, particularly next to California, Peru, and Southwest Africa, low marine stratocumulus clouds (MSC) help to reduce the amount of solar radiation that reaches the surface by reflecting incident sunlight. The climate feedback associated with these clouds is thought to be positive. This project looks at CMIP5 models and compares them to observational data from CERES and ERA-Interim to try and find observational evidence and model agreement for low, marine stratocumulus cloud feedback. Although current evidence suggests that the low cloud feedback is positive (IPCC, 2014), an analysis of the simulated relationship between July lower tropospheric stability (LTS) and shortwave cloud forcing in MSC regions suggests that this feedback is not due to changes in LTS. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.
Projected increase in El Niño-driven tropical cyclone frequency in the Pacific
NASA Astrophysics Data System (ADS)
Chand, Savin S.; Tory, Kevin J.; Ye, Hua; Walsh, Kevin J. E.
2017-02-01
The El Niño/Southern Oscillation (ENSO) drives substantial variability in tropical cyclone (TC) activity around the world. However, it remains uncertain how the projected future changes in ENSO under greenhouse warming will affect TC activity, apart from an expectation that the overall frequency of TCs is likely to decrease for most ocean basins. Here we show robust changes in ENSO-driven variability in TC occurrence by the late twenty-first century. In particular, we show that TCs become more frequent (~20-40%) during future-climate El Niño events compared with present-climate El Niño events--and less frequent during future-climate La Niña events--around a group of small island nations (for example, Fiji, Vanuatu, Marshall Islands and Hawaii) in the Pacific. We examine TCs across 20 models from the Coupled Model Intercomparison Project phase 5 database, forced under historical and greenhouse warming conditions. The 12 most realistic models identified show a strong consensus on El Niño-driven changes in future-climate large-scale environmental conditions that modulate development of TCs over the off-equatorial western Pacific and the central North Pacific regions. These results have important implications for climate change and adaptation pathways for the vulnerable Pacific island nations.
Staunton, Kyran M; Nakamura, Akihiro; Burwell, Chris J; Robson, Simon K A; Williams, Stephen E
2016-01-01
Understanding how the environment influences patterns of diversity is vital for effective conservation management, especially in a changing global climate. While assemblage structure and species richness patterns are often correlated with current environmental factors, historical influences may also be considerable, especially for taxa with poor dispersal abilities. Mountain-top regions throughout tropical rainforests can act as important refugia for taxa characterised by low dispersal capacities such as flightless ground beetles (Carabidae), an ecologically significant predatory group. We surveyed flightless ground beetles along elevational gradients in five different subregions within the Australian Wet Tropics World Heritage Area to investigate (1) whether the diversity and composition of flightless ground beetles are elevationally stratified, and, if so, (2) what environmental factors (other than elevation per se) are associated with these patterns. Generalised linear models and model averaging techniques were used to relate patterns of diversity to environmental factors. Unlike most taxonomic groups, flightless ground beetles increased in species richness and abundance with elevation. Additionally, each subregion consisted of relatively distinct assemblages containing a high level of regional endemic species. Species richness was most strongly and positively associated with historical and current climatic stabilities and negatively associated with severity of recent disturbance (treefalls). Assemblage composition was associated with latitude and historical and current climatic conditions. Although the results need to be interpreted carefully due to inter-correlation between historical and current climatic variables, our study is in agreement with the hypothesis that upland refugia provided stable climatic conditions since the last glacial maximum, and supported a diverse fauna of flightless beetle species. These findings are important for conservation management as upland habitats become increasingly threatened by climate change.
Staunton, Kyran M.; Nakamura, Akihiro; Burwell, Chris J.; Robson, Simon K. A.; Williams, Stephen E.
2016-01-01
Understanding how the environment influences patterns of diversity is vital for effective conservation management, especially in a changing global climate. While assemblage structure and species richness patterns are often correlated with current environmental factors, historical influences may also be considerable, especially for taxa with poor dispersal abilities. Mountain-top regions throughout tropical rainforests can act as important refugia for taxa characterised by low dispersal capacities such as flightless ground beetles (Carabidae), an ecologically significant predatory group. We surveyed flightless ground beetles along elevational gradients in five different subregions within the Australian Wet Tropics World Heritage Area to investigate (1) whether the diversity and composition of flightless ground beetles are elevationally stratified, and, if so, (2) what environmental factors (other than elevation per se) are associated with these patterns. Generalised linear models and model averaging techniques were used to relate patterns of diversity to environmental factors. Unlike most taxonomic groups, flightless ground beetles increased in species richness and abundance with elevation. Additionally, each subregion consisted of relatively distinct assemblages containing a high level of regional endemic species. Species richness was most strongly and positively associated with historical and current climatic stabilities and negatively associated with severity of recent disturbance (treefalls). Assemblage composition was associated with latitude and historical and current climatic conditions. Although the results need to be interpreted carefully due to inter-correlation between historical and current climatic variables, our study is in agreement with the hypothesis that upland refugia provided stable climatic conditions since the last glacial maximum, and supported a diverse fauna of flightless beetle species. These findings are important for conservation management as upland habitats become increasingly threatened by climate change. PMID:27192085
Ecological genomics predicts climate vulnerability in an endangered southwestern songbird.
Ruegg, Kristen; Bay, Rachael A; Anderson, Eric C; Saracco, James F; Harrigan, Ryan J; Whitfield, Mary; Paxton, Eben H; Smith, Thomas B
2018-05-09
Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (Empidonax traillii), and find the endangered desert southwestern subspecies (E. t. extimus) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability - the mismatch between current and predicted future genotype-environment relationships - indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate-associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype-environment relationships into landscape-scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups. © 2018 John Wiley & Sons Ltd/CNRS.
Multilevel multi-informant structure of the authoritative school climate survey.
Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan
2014-09-01
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 these 4 constructs was examined with exploratory and confirmatory factor analyses in a statewide sample of 39,364 students (Grades 7 and 8) attending 423 schools. Notably, the analyses used a multilevel structural approach to model the nesting of students in schools for purposes of evaluating factor structure, demonstrating convergent and concurrent validity and gauging the structural invariance of concurrent validity coefficients across gender. These findings provide schools with a core group of school climate measures guided by authoritative discipline theory. PsycINFO Database Record (c) 2014 APA, all rights reserved.
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.
NASA Astrophysics Data System (ADS)
Nativi, S.; Santoro, M.
2009-12-01
Currently, one of the major challenges for scientific community is the study of climate change effects on life on Earth. To achieve this, it is crucial to understand how climate change will impact on biodiversity and, in this context, several application scenarios require modeling the impact of climate change on distribution of individual species. In the context of GEOSS AIP-2 (Global Earth Observation System of Systems, Architecture Implementation Pilot- Phase 2), the Climate Change & Biodiversity thematic Working Group developed three significant user scenarios. A couple of them make use of a GEOSS-based framework to study the impact of climate change factors on regional species distribution. The presentation introduces and discusses this framework which provides an interoperability infrastructures to loosely couple standard services and components to discover and access climate and biodiversity data, and run forecast and processing models. The framework is comprised of the following main components and services: a)GEO Portal: through this component end user is able to search, find and access the needed services for the scenario execution; b)Graphical User Interface (GUI): this component provides user interaction functionalities. It controls the workflow manager to perform the required operations for the scenario implementation; c)Use Scenario controller: this component acts as a workflow controller implementing the scenario business process -i.e. a typical climate change & biodiversity projection scenario; d)Service Broker implementing Mediation Services: this component realizes a distributed catalogue which federates several discovery and access components (exposing them through a unique CSW standard interface). Federated components publish climate, environmental and biodiversity datasets; e)Ecological Niche Model Server: this component is able to run one or more Ecological Niche Models (ENM) on selected biodiversity and climate datasets; f)Data Access Transaction server: this component publishes the model outputs. The framework was successfully tested in two use scenarios of the GEOSS AIP-2 Climate Change and Biodiversity WG aiming to predict species distribution changes due to Climate Change factors, with the scientific patronage of the University of Colorado and the University of Alaska. The first scenario dealt with the Pikas specie regional distribution in the Great Basin area (North America). While, the second one concerned the modeling of the Arctic Food Chain species in the North Pole area -the relationships between different environmental parameters and Polar Bears distribution was analyzed. Results are published in the GEOSS AIP-2 web site: http://www.ogcnetwork.net/AIP2develop .
Perry, Cary; LeMay, Nancy; Rodway, Greg; Tracy, Allison; Galer, Joan
2005-01-01
Background This article describes the validation of an instrument to measure work group climate in public health organizations in developing countries. The instrument, the Work Group Climate Assessment Tool (WCA), was applied in Brazil, Mozambique, and Guinea to assess the intermediate outcomes of a program to develop leadership for performance improvement. Data were collected from 305 individuals in 42 work groups, who completed a self-administered questionnaire. Methods The WCA was initially validated using Cronbach's alpha reliability coefficient and exploratory factor analysis. This article presents the results of a second validation study to refine the initial analyses to account for nested data, to provide item-level psychometrics, and to establish construct validity. Analyses included eigenvalue decomposition analysis, confirmatory factor analysis, and validity and reliability analyses. Results This study confirmed the validity and reliability of the WCA across work groups with different demographic characteristics (gender, education, management level, and geographical location). The study showed that there is agreement between the theoretical construct of work climate and the items in the WCA tool across different populations. The WCA captures a single perception of climate rather than individual sub-scales of clarity, support, and challenge. Conclusion The WCA is useful for comparing the climates of different work groups, tracking the changes in climate in a single work group over time, or examining differences among individuals' perceptions of their work group climate. Application of the WCA before and after a leadership development process can help work groups hold a discussion about current climate and select a target for improvement. The WCA provides work groups with a tool to take ownership of their own group climate through a process that is simple and objective and that protects individual confidentiality. PMID:16223447
NASA Astrophysics Data System (ADS)
Davis, R.
2013-12-01
The purpose of this study is to test the conjecture that environmentally sustainable decisions and behaviors are related to individuals' conceptions of the natural world, in this case climate change; individuals' attitudes towards climate change; and the situations in which these decisions are made. The nature of mental models is an ongoing subject of disagreement. Some argue that mental models are coherent theories, much like scientific theories, that individuals employ systematically when reasoning about the world (Gopnik & Meltzoff, 1998). Others maintain that mental models are cobbled together from fragmented collections of ideas that are only loosely connected and context dependent (Disessa, 1988; Minstrell, 2000). It is likely that individuals sometimes reason about complex phenomena using systematic mental models and at other times reason using knowledge that is organized in fragmented pieces (Steedle & Shavelson, 2009). Thus, in measuring mental models of complex environmental systems, such as climate change, the assumption of systematicity may not be justified. Individuals may apply certain chains of reasoning in some contexts but not in others. The current study hypothesizes that an accurate mental model of climate change enables an individual to make effective evaluative judgments of environmental behavior options. The more an individual's mental model resembles that of an expert, the more consistent, accurate and automatic these judgments become. However, an accurate mental model is not sufficient to change environmental behavior. Real decisions and behaviors are products of a person-situation interaction: an interplay between psychosocial factors (such as knowledge and attitudes) and the situation in which the decision is made. This study investigates the relationship between both psychosocial and situational factors for climate change decisions. Data was collected from 436 adult participants through an online survey. The survey was comprised of demographic questions; three discreet instruments measuring (1) mental models of climate change, (2) attitudes and beliefs about climate change, and (3) self-reported behaviors; and an experimental intervention, followed by a behavioral intention question. Latent class analysis (LCA) and item-response theory (IRT) will be employed to analyze multiple-choice responses to the mental model survey to create groupings of individuals assumed to hold similar mental of climate change. A principal component analysis (PCA) using oblique rotation was employed to identify five scales (Chronbach's alpha > 0.80) within the attitude/belief instrument. Total and sub-scale scores were also calculated for self-reported behaviors. The relationships between mental models, attitudes and behaviors will be analyzed using multiple regression models. This work presents not only the development and validation of three novel instruments for accurately and efficiently measuring mental models, attitudes, and self-reported behaviors, but also provides insight into the types of mental models individuals hold. Understanding how climate change is conceptualized and how such knowledge influences attitudes and behaviors gives educators tools for guiding students towards more expert understandings while also enabling environmentalists to craft more effective messages.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Özkan, Şeyda
Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire basedmore » exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. - Highlights: • Experts identified challenges for health and pathogen modelling under climate change. • Eighteen key challenges and associated research priorities were identified. • Increasing capacity will require improved organisation and sharing knowledge. • Better communication across the diverse topics and approaches in this field is needed.« less
NASA Technical Reports Server (NTRS)
Lunt, Daniel J.; Huber, Matthew; Anagnostou, Eleni; Baatsen, Michiel L. J.; Caballero, Rodrigo; DeConto, Rob; Dijkstra, Henk A.; Donnadieu, Yannick; Evans, David; Feng, Ran;
2017-01-01
Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high ( greater than 800 ppmv) atmospheric CO2 concentrations. Although a post hoc intercomparison of Eocene (approximately 50 Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the early Eocene and the latest Paleocene (the EECO, PETM, and pre-PETM). Together with the CMIP6 pre-industrial control and abrupt 4(times) CO2 simulations, and additional sensitivity studies, these form the first phase of DeepMIP - the Deep-time Model Intercomparison Project, itself a group within the wider Paleoclimate Modeling Intercomparison Project (PMIP). The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, astronomical configuration, solar constant, land surface processes, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological data sets, which will be used to evaluate the simulations, will be developed.
The Multitrophic Effects of Climate Change and Glacier Retreat in Mountain Rivers
2017-01-01
Abstract Climate change is driving the thinning and retreat of many glaciers globally. Reductions of ice-melt inputs to mountain rivers are changing their physicochemical characteristics and, in turn, aquatic communities. Glacier-fed rivers can serve as model systems for investigations of climate-change effects on ecosystems because of their strong atmospheric–cryospheric links, high biodiversity of multiple taxonomic groups, and significant conservation interest concerning endemic species. From a synthesis of existing knowledge, we develop a new conceptual understanding of how reducing glacier cover affects organisms spanning multiple trophic groups. Although the response of macroinvertebrates to glacier retreat has been well described, we show that there remains a relative paucity of information for biofilm, microinvertebrate, and vertebrate taxa. Enhanced understanding of whole river food webs will improve the prediction of river-ecosystem responses to deglaciation while offering the potential to identify and protect a wider range of sensitive and threatened species. PMID:29599537
The Multitrophic Effects of Climate Change and Glacier Retreat in Mountain Rivers.
Fell, Sarah C; Carrivick, Jonathan L; Brown, Lee E
2017-10-01
Climate change is driving the thinning and retreat of many glaciers globally. Reductions of ice-melt inputs to mountain rivers are changing their physicochemical characteristics and, in turn, aquatic communities. Glacier-fed rivers can serve as model systems for investigations of climate-change effects on ecosystems because of their strong atmospheric-cryospheric links, high biodiversity of multiple taxonomic groups, and significant conservation interest concerning endemic species. From a synthesis of existing knowledge, we develop a new conceptual understanding of how reducing glacier cover affects organisms spanning multiple trophic groups. Although the response of macroinvertebrates to glacier retreat has been well described, we show that there remains a relative paucity of information for biofilm, microinvertebrate, and vertebrate taxa. Enhanced understanding of whole river food webs will improve the prediction of river-ecosystem responses to deglaciation while offering the potential to identify and protect a wider range of sensitive and threatened species.
Woskie, S R; Smith, T J; Hammond, S K; Schenker, M B; Garshick, E; Speizer, F E
1988-01-01
The diesel exhaust exposures of railroad workers in thirteen job groups from four railroads in the United States were used to estimate U.S. national average exposures with a linear statistical model which accounts for the significant variability in exposure caused by climate, the differences among railroads and the uneven distribution of railroad workers across climatic regions. Personal measurements of respirable particulate matter, adjusted to remove the contribution of cigarette smoke particles, were used as a marker for diesel exhaust. The estimated national means of adjusted respirable particulate matter (ARP) averaged 10 micrograms/m3 lower than the simple means for each job group, reflecting the climatic differences between the northern railroads studied and the distribution of railroad workers nationally. Limited historical records, including some industrial hygiene data, were used to evaluate past diesel exhaust exposures, which were estimated to be approximately constant from the 1950's to 1983.
Gonçalves, Duarte Vasconcelos; Martínez-Freiría, Fernando; Crochet, Pierre-André; Geniez, Philippe; Carranza, Salvador; Brito, José Carlos
2018-01-01
Highlands, hydrographic systems and coastal areas have been hypothesised to form corridors across the hyperarid Sahara desert in North Africa, allowing dispersal and gene flow for non-xeric species. Here we aim to provide a genetic test for the trans-Saharan corridor model, and predict the location and stability of ecological-corridors, by combining phylogeography and palaeoclimatic modelling. The model was the Psammophis schokari (Schokari sand racer) group, fast-moving and widely distributed generalist colubrids occurring mostly in arid and semiarid scrublands. We combined dated phylogenies of mitochondrial and nuclear markers with palaeoclimatic modelling. For the phylogeographic analysis, we used 75 samples of P. schokari and P. aegyptius, and Bayesian and Maximum-Likelihood methods. For the ecological models, we used Maxent over the distribution of P. schokari and West African lineages. Models were projected to past conditions (mid Holocene, Last Glacial Maximum and Last Inter-Glacial) to infer climatic stable areas. Climatic stability was predicted to be mostly restricted to coastal areas and not spatially continuous. A putative temporary trans-Saharan corridor was identified in Eastern Sahara, with a more stable one along the Atlantic coast. Six parapatric lineages were identified within P. schokari, four occurring in North Africa. These likely diverged during the Pliocene. The Tamanraset River might have been a vicariant agent. African lineages may have experienced further subsequent diversification during the late Pleistocene. The main P. schokari refugia were probably located along the northern margins of the Sahara, allowing its North-to-South colonization. Trans-Saharan corridors seem to have played a role in P. schokari biogeography, allowing colonization of central Saharan mountains and Sahel. Some might have worked as refugia, and even the most stable corridors may have sections working as filters, depending on each climatic phase. We expect the use of trans-Saharan corridors to decrease for more mesic species or with less dispersal capabilities. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Technical Reports Server (NTRS)
Meeson, Blanche W.
2000-01-01
The research carried out in the Earth Sciences in NASA and at NASA's Goddard Space Flight Center will be the focus of the presentations. In addition, one research project that links sea surface temperature to epidemics in Africa will be highlighted. At GSFC research interests span the full breath of disciplines in Earth Science. Branches and research groups focus on areas as diverse as planetary geomagnetics and atmospheric chemistry. These organizations focus on atmospheric sciences (atmospheric chemistry, climate and radiation, regional processes, atmospheric modeling), hydrological sciences (snow, ice, oceans, and seasonal-to-interannual prediction), terrestrial physics (geology, terrestrial biology, land-atmosphere interactions, geophysics), climate modeling (global warming, greenhouse gases, climate change), on sensor development especially using lidar and microwave technologies, and on information technologies, that enable support of scientific and technical research.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maurakis, Eugene G
Objectives of the two-year study were to (1) establish baselines for fish and macroinvertebrate community structures in two mid-Atlantic lower Piedmont watersheds (Quantico Creek, a pristine forest watershed; and Cameron Run, an urban watershed, Virginia) that can be used to monitor changes relative to the impacts related to climate change in the future; (2) create mathematical expressions to model fish species richness and diversity, and macroinvertebrate taxa and macroinvertebrate functional feeding group taxa richness and diversity that can serve as a baseline for future comparisons in these and other watersheds in the mid-Atlantic region; and (3) heighten people’s awareness, knowledgemore » and understanding of climate change and impacts on watersheds in a laboratory experience and interactive exhibits, through internship opportunities for undergraduate and graduate students, a week-long teacher workshop, and a website about climate change and watersheds. Mathematical expressions modeled fish and macroinvertebrate richness and diversity accurately well during most of the six thermal seasons where sample sizes were robust. Additionally, hydrologic models provide the basis for estimating flows under varying meteorological conditions and landscape changes. Continuations of long-term studies are requisite for accurately teasing local human influences (e.g. urbanization and watershed alteration) from global anthropogenic impacts (e.g. climate change) on watersheds. Effective and skillful translations (e.g. annual potential exposure of 750,000 people to our inquiry-based laboratory activities and interactive exhibits in Virginia) of results of scientific investigations are valuable ways of communicating information to the general public to enhance their understanding of climate change and its effects in watersheds.« less
Özkan, Şeyda; Vitali, Andrea; Lacetera, Nicola; Amon, Barbara; Bannink, André; Bartley, Dave J; Blanco-Penedo, Isabel; de Haas, Yvette; Dufrasne, Isabelle; Elliott, John; Eory, Vera; Fox, Naomi J; Garnsworthy, Phil C; Gengler, Nicolas; Hammami, Hedi; Kyriazakis, Ilias; Leclère, David; Lessire, Françoise; Macleod, Michael; Robinson, Timothy P; Ruete, Alejandro; Sandars, Daniel L; Shrestha, Shailesh; Stott, Alistair W; Twardy, Stanislaw; Vanrobays, Marie-Laure; Ahmadi, Bouda Vosough; Weindl, Isabelle; Wheelhouse, Nick; Williams, Adrian G; Williams, Hefin W; Wilson, Anthony J; Østergaard, Søren; Kipling, Richard P
2016-11-01
Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. Copyright © 2016 Elsevier Inc. All rights reserved.
Simulating Effects of Forest Management Practices on Pesticide.
M.C. Smith; W.G. Knisel; J.L. Michael; D.G. Neary
1993-01-01
The GLEAMS model pesticide component was modified to simulate up to 245 pesticides simultaneously, and the revised model was used to pesticide pesticide application windows for forest site preparation and pine release. Five herbicides were made for soils representing four hydrologic soil groups in four climatic regions of the southeastern United States. Five herbicides...
2018-01-01
Like many other high elevation alpine tree species, Rocky Mountain bristlecone pine (Pinus aristata Engelm.) may be particularly vulnerable to climate change. To evaluate its potential vulnerability to shifts in climate, we defined the suitable climate space for each of four genetic lineages of bristlecone pine and for other subalpine tree species in close proximity to bristlecone pine forests. Measuring changes in the suitable climate space for lineage groups is an important step beyond models that assume species are genetically homogenous. The suitable climate space for bristlecone pine in the year 2090 is projected to decline by 74% and the proportional distribution of suitable climate space for genetic lineages shifts toward those associated with warmer and wetter conditions. The 2090 climate space for bristlecone pine exhibits a bimodal distribution along an elevation gradient, presumably due to the persistence of the climate space in the Southern Rocky Mountains and exclusion at mid-elevations by conditions that favor the climate space of other species. These shifts have implications for changes in fire regimes, vulnerability to pest and pathogens, and altered carbon dynamics across the southern Rockies, which may reduce the likelihood of bristlecone pine trees achieving exceptional longevity in the future. The persistence and expansion of climate space for southern bristlecone pine genetic lineage groups in 2090 suggests that these sources may be the least vulnerable in the future. While these lineages may be more likely to persist and therefore present opportunities for proactive management (e.g., assisted migration) to maintain subalpine forest ecosystem services in a warmer world, our findings also imply heighted conservation concern for vulnerable northern lineages facing range contractions. PMID:29554097
Wibeck, Victoria
2014-02-01
This paper explores social representations of climate change, investigating how climate change is discussed by Swedish laypeople interacting in focus group interviews. The analysis focuses on prototypical examples and metaphors, which were key devices for objectifying climate change representations. The paper analyzes how the interaction of focus group participants with other speakers, ideas, arguments, and broader social representations shaped their representations of climate change. Climate change was understood as a global but distant issue with severe consequences. There was a dynamic tension between representations of climate change as a gradual vs. unpredictable process. Implications for climate change communication are discussed.
Till, Charlotte; Haverkamp, Jamie; White, Devin; ...
2016-11-22
Climate change has the potential to displace large populations in many parts of the developed and developing world. Understanding why, how, and when environmental migrants decide to move is critical to successful strategic planning within organizations tasked with helping the affected groups, and mitigating their systemic impacts. One way to support planning is through the employment of computational modeling techniques. Models can provide a window into possible futures, allowing planners and decision makers to test different scenarios in order to understand what might happen. While modeling is a powerful tool, it presents both opportunities and challenges. This paper builds amore » foundation for the broader community of model consumers and developers by: providing an overview of pertinent climate-induced migration research, describing some different types of models and how to select the most relevant one(s), highlighting three perspectives on obtaining data to use in said model(s), and the consequences associated with each. It concludes with two case studies based on recent research that illustrate what can happen when ambitious modeling efforts are undertaken without sufficient planning, oversight, and interdisciplinary collaboration. Lastly, we hope that the broader community can learn from our experiences and apply this knowledge to their own modeling research efforts.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Till, Charlotte; Haverkamp, Jamie; White, Devin
Climate change has the potential to displace large populations in many parts of the developed and developing world. Understanding why, how, and when environmental migrants decide to move is critical to successful strategic planning within organizations tasked with helping the affected groups, and mitigating their systemic impacts. One way to support planning is through the employment of computational modeling techniques. Models can provide a window into possible futures, allowing planners and decision makers to test different scenarios in order to understand what might happen. While modeling is a powerful tool, it presents both opportunities and challenges. This paper builds amore » foundation for the broader community of model consumers and developers by: providing an overview of pertinent climate-induced migration research, describing some different types of models and how to select the most relevant one(s), highlighting three perspectives on obtaining data to use in said model(s), and the consequences associated with each. It concludes with two case studies based on recent research that illustrate what can happen when ambitious modeling efforts are undertaken without sufficient planning, oversight, and interdisciplinary collaboration. Lastly, we hope that the broader community can learn from our experiences and apply this knowledge to their own modeling research efforts.« less
A Simple Approach to Account for Climate Model Interdependence in Multi-Model Ensembles
NASA Astrophysics Data System (ADS)
Herger, N.; Abramowitz, G.; Angelil, O. M.; Knutti, R.; Sanderson, B.
2016-12-01
Multi-model ensembles are an indispensable tool for future climate projection and its uncertainty quantification. Ensembles containing multiple climate models generally have increased skill, consistency and reliability. Due to the lack of agreed-on alternatives, most scientists use the equally-weighted multi-model mean as they subscribe to model democracy ("one model, one vote").Different research groups are known to share sections of code, parameterizations in their model, literature, or even whole model components. Therefore, individual model runs do not represent truly independent estimates. Ignoring this dependence structure might lead to a false model consensus, wrong estimation of uncertainty and effective number of independent models.Here, we present a way to partially address this problem by selecting a subset of CMIP5 model runs so that its climatological mean minimizes the RMSE compared to a given observation product. Due to the cancelling out of errors, regional biases in the ensemble mean are reduced significantly.Using a model-as-truth experiment we demonstrate that those regional biases persist into the future and we are not fitting noise, thus providing improved observationally-constrained projections of the 21st century. The optimally selected ensemble shows significantly higher global mean surface temperature projections than the original ensemble, where all the model runs are considered. Moreover, the spread is decreased well beyond that expected from the decreased ensemble size.Several previous studies have recommended an ensemble selection approach based on performance ranking of the model runs. Here, we show that this approach can perform even worse than randomly selecting ensemble members and can thus be harmful. We suggest that accounting for interdependence in the ensemble selection process is a necessary step for robust projections for use in impact assessments, adaptation and mitigation of climate change.
Climatological Impact of Atmospheric River Based on NARCCAP and DRI-RCM Datasets
NASA Astrophysics Data System (ADS)
Mejia, J. F.; Perryman, N. M.
2012-12-01
This study evaluates spatial responses of extreme precipitation environments, typically associated with Atmospheric River events, using Regional Climate Model (RCM) output from NARCCAP dataset (50km grid size) and the Desert Research Institute-RCM simulations (36 and 12 km grid size). For this study, a pattern-detection algorithm was developed to characterize Atmospheric Rivers (ARs)-like features from climate models. Topological analysis of the enhanced elongated moisture flux (500-300hPa; daily means) cores is used to objectively characterize such AR features in two distinct groups: (i) zonal, north Pacific ARs, and (ii) subtropical ARs, also known as "Pineapple Express" events. We computed the climatological responses of the different RCMs upon these two AR groups, from which intricate differences among RCMs stand out. This study presents these climatological responses from historical and scenario driven simulations, as well as implications for precipitation extreme-value analyses.
NASA Astrophysics Data System (ADS)
Swart, R. J.; Pagé, C.
2010-12-01
Until recently, the policy applications of Earth System Models in general and climate models in particular were focusing mainly on the potential future changes in the global and regional climate and attribution of observed changes to anthropogenic activities. Is climate change real? And if so, why do we have to worry about it? Following the broad acceptance of the reality of the risks by the majority of governments, particularly after the publication of IPCC’s 4th Assessment Report and the increasing number of observations of changes in ecological and socio-economic systems that are consistent with the observed climatic changes, governments, companies and other societal groups have started to evaluate their own vulnerability in more detail and to develop adaptation and mitigation strategies. After an early focus on the most vulnerable developing countries, recently, an increasing number of industrialized countries have embarked on the design of adaptation and mitigation plans, or on studies to evaluate the level of climate resilience of their development plans and projects. Which climate data are actually required to effectively support these activities? This paper reports on the efforts of the IS-ENES project, the infrastructure project of the European Network for Earth System Modeling, to address this question. How do we define user needs and can the existing gap between the climate modeling and impact research communities be bridged in support of the ENES long-term strategy? In contrast from the climate modeling community, which has a relatively long history of collaboration facilitated by a relatively uniform subject matter, commonly agreed definitions of key terminology and some level of harmonization of methods, the climate change impacts research community is very diverse and fragmented, using a wide variety of data sources, methods and tools. An additional complicating factor is that researchers working on adaptation usually closely collaborate with non-scientific stakeholders in government, civil society and the private sector, in a context which is different in many European countries. In the IS-ENES effort, a dialogue is set up between the communities in Europe, building on various existing research networks in the area of climate change impacts, vulnerability and adaptation. Generally, the data needs have not been well articulated. If asked, people working on impacts and adaptation routinely seem to ask for data with the highest possible resolution. However, in reality for many impact and adaptation applications this is not needed, and the large resulting data sets may exceed the analytical capacity of the impact researchers. For impact analysis often various types of climate indices, derived from primary climate model output variables, are required, including indices for extremes and in probabilistic format. Rather than making output from climate modeling generically available, e.g. through a climate service e-portal, context-specific tailoring of information for specific applications is important for effective use. This may require some level of interaction between the users and the data providers, dependent on the specific questions to be addressed.
Multi-Decadal Oscillations of the Ocean Active Upper-Layer Heat Content
NASA Astrophysics Data System (ADS)
Byshev, Vladimir I.; Neiman, Victor G.; Anisimov, Mikhail V.; Gusev, Anatoly V.; Serykh, Ilya V.; Sidorova, Alexandra N.; Figurkin, Alexander L.; Anisimov, Ivan M.
2017-07-01
Spatial patterns in multi-decadal variability in upper ocean heat content for the last 60 years are examined using a numerical model developed at the Institute of Numerical Mathematics of Russia (INM Model) and sea water temperature-salinity data from the World Ocean Database (in: Levitus, NOAA Atlas NESDIS 66, U.S. Wash.: Gov. Printing Office, 2009). Both the model and the observational data show that the heat content of the Active Upper Layer (AUL) in particular regions of the Atlantic, Pacific and Southern oceans have experienced prominent simultaneous variations on multi-decadal (25-35 years) time scales. These variations are compared earlier revealed climatic alternations in the Northern Atlantic region during the last century (Byshev et al. in Doklady Earth Sci 438(2):887-892, 2011). We found that from the middle of 1970s to the end of 1990s the AUL heat content decreased in several oceanic regions, while the mean surface temperature increased on Northern Hemisphere continents according to IPCC (in: Stocker et al. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, Cambridge University Press, Cambridge, 2013). This means that the climate-forcing effect of the ocean-atmosphere interaction in certain energy-active areas determines not only local climatic processes, but also have an influence on global-scale climate phenomena. Here we show that specific regional features of the AUL thermal structure are in a good agreement with climatic conditions on the adjacent continents. Further, the ocean AUL in the five distinctive regions identified in our study have resumed warming in the first decade of this century. By analogy inference from previous climate scenarios, this may signal the onset of more continental climate over mainlands.
Bussi, Gianbattista; Whitehead, Paul G; Bowes, Michael J; Read, Daniel S; Prudhomme, Christel; Dadson, Simon J
2016-12-01
Potential increases of phytoplankton concentrations in river systems due to global warming and changing climate could pose a serious threat to the anthropogenic use of surface waters. Nevertheless, the extent of the effect of climatic alterations on phytoplankton concentrations in river systems has not yet been analysed in detail. In this study, we assess the impact of a change in precipitation and temperature on river phytoplankton concentration by means of a physically-based model. A scenario-neutral methodology has been employed to evaluate the effects of climate alterations on flow, phosphorus concentration and phytoplankton concentration of the River Thames (southern England). In particular, five groups of phytoplankton are considered, representing a range of size classes and pigment phenotypes, under three different land-use/land-management scenarios to assess their impact on phytoplankton population levels. The model results are evaluated within the framework of future climate projections, using the UK Climate Projections 09 (UKCP09) for the 2030s. The results of the model demonstrate that an increase in average phytoplankton concentration due to climate change is highly likely to occur, with the magnitude varying depending on the location along the River Thames. Cyanobacteria show significant increases under future climate change and land use change. An expansion of intensive agriculture accentuates the growth in phytoplankton, especially in the upper reaches of the River Thames. However, an optimal phosphorus removal mitigation strategy, which combines reduction of fertiliser application and phosphorus removal from wastewater, can help to reduce this increase in phytoplankton concentration, and in some cases, compensate for the effect of rising temperature. Copyright © 2016 Elsevier B.V. All rights reserved.
Special Issue ;Sediment cascades in cold climate geosystems;
NASA Astrophysics Data System (ADS)
Morche, David; Krautblatter, Michael; Beylich, Achim A.
2017-06-01
This Editorial introduces the Special Issue on sediment cascades in cold climate geosystems that evolved from the eighth I.A.G./A.I.G. SEDIBUD (Sediment Budgets in Cold Environments; http://www.geomorph.org/sedibud-working-group/) workshop. The workshop was held from 1st to 4th September 2014 at the Environmental Research Station ;Schneefernerhaus; (http://www.schneefernerhaus.de/en/home.html) located at Mt. Zugspitze, the highest peak of Germany, (2962 m asl). Paper and poster presentations focused on observations, measurements and modeling of geomorphological processes in sediment cascades in cold climate geosystems. This resulting Special Issue brings together ten selected contributions from arctic and alpine environments.
NASA Astrophysics Data System (ADS)
Sorokin, V. A.; Volkov, Yu V.; Sherstneva, A. I.; Botygin, I. A.
2016-11-01
This paper overviews a method of generating climate regions based on an analytic signal theory. When applied to atmospheric surface layer temperature data sets, the method allows forming climatic structures with the corresponding changes in the temperature to make conclusions on the uniformity of climate in an area and to trace the climate changes in time by analyzing the type group shifts. The algorithm is based on the fact that the frequency spectrum of the thermal oscillation process is narrow-banded and has only one mode for most weather stations. This allows using the analytic signal theory, causality conditions and introducing an oscillation phase. The annual component of the phase, being a linear function, was removed by the least squares method. The remaining phase fluctuations allow consistent studying of their coordinated behavior and timing, using the Pearson correlation coefficient for dependence evaluation. This study includes program experiments to evaluate the calculation efficiency in the phase grouping task. The paper also overviews some single-threaded and multi-threaded computing models. It is shown that the phase grouping algorithm for meteorological data can be parallelized and that a multi-threaded implementation leads to a 25-30% increase in the performance.
Tuning the climate sensitivity of a global model to match 20th Century warming
NASA Astrophysics Data System (ADS)
Mauritsen, T.; Roeckner, E.
2015-12-01
A climate models ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons historical warming cannot be considered a purely empirical result of the modelling efforts because the desired result is known in advance and so is a potential target of tuning. Here we explain how the latest edition of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) atmospheric model (ECHAM6.3) had its climate sensitivity systematically tuned to about 3 K; the MPI model to be used during CMIP6. This was deliberately done in order to improve the match to observed 20th Century warming over the previous model generation (MPI-ESM, ECHAM6.1) which warmed too much and had a sensitivity of 3.5 K. In the process we identified several controls on model cloud feedback that confirm recently proposed hypotheses concerning trade-wind cumulus and high-latitude mixed-phase clouds. We then evaluate the model fidelity with centennial global warming and discuss the relative importance of climate sensitivity, forcing and ocean heat uptake efficiency in determining the response as well as possible systematic biases. The activity of targeting historical warming during model development is polarizing the modeling community with 35 percent of modelers stating that 20th Century warming was rated very important to decisive, whereas 30 percent would not consider it at all. Likewise, opinions diverge as to which measures are legitimate means for improving the model match to observed warming. These results are from a survey conducted in conjunction with the first WCRP Workshop on Model Tuning in fall 2014 answered by 23 modelers. We argue that tuning or constructing models to match observed warming to some extent is practically unavoidable, and as such, in many cases might as well be done explicitly. For modeling groups that have the capability to tune both their aerosol forcing and climate sensitivity there is now a unique opportunity to explore the bounds of our understanding - a low sensitivity model could be sustained by weak aerosol forcing, and a highly sensitive model could potentially be constructed to match observed warming by strong compensating aerosol cooling. This next natural step could constitute a new paradigm in climate modeling.
An Earth Summit in a Large General Education Oceanography Class
NASA Astrophysics Data System (ADS)
Dodson, H.; Prothero, W. A.
2001-12-01
An Earth Summit approach in UCSB's undergraduate physical oceanography course has raised student interest level while it also supports the course goals of increased learner awareness of the process of science, and critical analysis of scientific claims. At the beginning of the quarter, each group of students chooses a country to represent in the Earth Summit. During the course of the quarter, these groups relate each of the class themes to their chosen country. Themes include 1) ocean basins and plate tectonics, 2) atmospheres, oceans and climate, and 3) fisheries. Students acquire and utilize Earth data to support their positions. Earth data sources include the "Our Dynamic Planet" CDROM (http://oceanography.geol.ucsb.edu/ODP_Advert/odp_onepage.htm), NOAA's ocean and climate database (http://ferret.wrc.noaa.gov/las/), WorldWatcher CD (http://www.worldwatcher.northwestern.edu/) and JPL's Seawinds web site (http://haifung.jpl.nasa.gov/index.html). During the atmospheres, oceans and climate theme, students choose from 12 mini-studies that use various kinds of on-line Earth data related to important global or regional phenomena relevant to the course. The Earth datasets that the students access for their analysis include: winds; atmospheric pressure; ocean chemistry; sea surface temperature; solar radiation; precipitation, etc. The first group of 6 mini-studies focus on atmosphere and ocean, and are: 1) global winds and surface currents, 2) atmosphere and ocean interactions, 3) stratospheric ozone depletion, 4) El Nino, 5) Indian monsoon, and 6) deep ocean circulation. The second group focus on the Earth's heat budget and climate and are: 1) influence of man's activities on the climate, 2) the greenhouse effect, 3) seasonal variation and the Earth's heat budget, 4) global warming, 5) paleoclimate, and 6) volcanoes and climate. The students use what they have learned in these mini-studies to address atmospheric and climatic issues pertinent to their specific Earth Summit countries. For example, students representing the country of Chile might model their investigations after a)winds and surface currents, b)atmosphere and ocean interactions, c) stratospheric ozone depletion, d)El Nino; and/or e)volcanoes and climate. Please join the "Oceanography" interest group of DLESE to discuss, develop, and access oceanography related mini-studies that use earth data (http://oceanography.geol.ucsb.edu/dlese/wg_oceanog/Index.html). >http://oceanography.geol.ucsb.edu/AWP/Class_Info/GS-4/Labs/Labs Index.html
Yang, Jixia; Mossholder, Kevin W; Peng, T K
2007-05-01
In this article, the authors extend research on the cross-level effects of procedural justice climate by theorizing and testing its interaction with group power distance. The results indicated that group power distance moderated the relationships between procedural justice climate and individual-level outcomes (organizational commitment and organization-directed citizenship behavior). More specifically, a larger group power distance was found to attenuate the positive cross-level effects of procedural justice climate. Implications for procedural justice climate research are discussed. 2007 APA, all rights reserved
NASA Astrophysics Data System (ADS)
Pytlak, E.
2014-12-01
This presentation will outline ongoing, multi-year hydroclimate change research between the Columbia River Management Joint Operating Committee (RMJOC), The University of Washington, Portland State University, and their many regional research partners and stakeholders. Climate change in the Columbia River Basin is of particular concern to the Bonneville Power Administration (BPA) and many Federal, Tribal and regional stakeholders. BPA, the U.S. Army Corp of Engineers, and U.S. Bureau of Reclamation, which comprise the RMJOC, conducted an extensive study in 2009-11 using climate change streamflows produced by the University of Washington Climate Impacts Group (CIG). The study reconfirmed that as more winter precipitation in the Columbia Basin falls as rain rather than snow by mid-century, particularly on the U.S. portion of the basin, increased winter runoff is likely, followed by an earlier spring snowmelt peak, followed by less summer flows as seasonal snowmelt diminished earlier in the water year. Since that initial effort, both global and regional climate change modeling has advanced. To take advantage of the new outputs from the Fifth Coupled Model Intercomparison Project (CMIP-5), the RMJOC, through BPA support, is sponsoring new hydroclimate research which considers not only the most recent information from the GCMs, but also the uncertainties introduced by the hydroclimate modeling process itself. Historical streamflows, which are used to calibrate hydrologic models and ascertain their reliability, are subject to both measurement and modeling uncertainties. Downscaling GCMs to a hydrologically useful spatial and temporal resolution introduces uncertainty, depending on the downscaling methods. Hydrologic modeling introduces uncertainties from calibration and geophysical states, some of which, like land surface characteristics, are likely to also change with time. In the upper Columbia Basin, glacier processes introduce yet another source of uncertainty. The latest joint effort attempts to ascertain the relative contributions of these uncertainties in comparison to the uncertainties brought by changing climate itself.
Using Models to Teach about Climate Change: A look at NGSS Expectations and Teacher Perceptions
NASA Astrophysics Data System (ADS)
Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.
2013-12-01
The Next Generation Science Standards have been updated from the previous version of the standards with some much needed emphasis on topics in climate and climate change. In particular, the standards have focused on K-12 students learning about science models, which is extremely important when discussing climate change. The NGSS suggest that students be able to 1) develop and use science models (not just use them to explain a concept) because this is how scientists actually use models during the scientific process; and 2) understand systems and system models across all science concepts and all age levels because it leads to further understanding about a more complex natural system (like climate change). To summarize, the NGSS expects that K-12 students should develop and use system models across disciplines and age groups in a way that is similar to how scientists use them in practice, which is to make predictions about unanswered questions. Research indicates that students who learn about science content using an approach that aligns more authentically with the way real science inquiry is done have a better understanding of the content, better understanding of the nature of science, improved critical thinking skills, and improved problem solving skills. Research also indicates that most teachers are aware of this method to teach science content, but sometimes have trouble implementing it into the classroom effectively for many reasons. If accepted, this presentation will share an approach to incorporate modeling into the classroom effectively as well as report the results from a study that qualitatively look at three teacher's perspectives on using models in the classroom while teaching units about climate change, in order to identify how/why teachers struggle to teach about models involved in content related to climate change. Preliminary results indicate that the teachers in this study view models as an effective way to explain a concept to their students, but none of them mention or discuss the predictive power of models. Although models are a useful way to explain a complex phenomenon concisely, arguably the most important role science models play in scientific inquiry is their ability to allow scientists to make prediction, especially when it comes to climate change. Since all three teachers overlooked the predictive power of models, it indicates that that they do not have a firm understanding of the role science models play in making scientific predictions. In conclusion, there is discrepancy between what the NGSS indicate students should be learning about modeling and what teachers are prepared to teach. In order to better prepare teachers to meet the demands required of them, they need to be better educated about models, what they are, what they do, and how scientists use them. By preparing teachers to teach K-12 students about the role models play in climate research, we can build a more knowledgeable society that is better prepared to make informed decisions on how to deal with issues in our changing climate.
Zohar, Dov; Lee, Jin
2016-10-01
The study was designed to test a multilevel path model whose variables exert opposing effects on school bus drivers' performance. Whereas departmental safety climate was expected to improve driving safety, the opposite was true for in-vehicle disruptive children behavior. The driving safety path in this model consists of increasing risk-taking practices starting with safety shortcuts leading to rule violations and to near-miss events. The study used a sample of 474 school bus drivers in rural areas, driving children to school and school-related activities. Newly developed scales for measuring predictor, mediator and outcome variables were validated with video data taken from inner and outer cameras, which were installed in 29 buses. Results partially supported the model by indicating that group-level safety climate and individual-level children distraction exerted opposite effects on the driving safety path. Furthermore, as hypothesized, children disruption moderated the strength of the safety rule violation-near miss relationship, resulting in greater strength under high disruptiveness. At the same time, the hypothesized interaction between the two predictor variables was not supported. Theoretical and practical implications for studying safety climate in general and distracted driving in particular for professional drivers are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Interannual Variation in Phytoplankton Class-specific Primary Production at a Global Scale
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile; Gregg, Watson
2014-01-01
Phytoplankton is responsible for over half of the net primary production on earth. The knowledge on the contribution of various phytoplankton groups to the total primary production is still poorly understood. Data from satellite observations suggest that for upwelling regions, photosynthetic rates by microplankton is higher than that of nanoplankton but that when the spatial extent is considered, the production by nanoplankton is comparable or even larger than microplankton. Here, we used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. Globally, diatoms were the group that contributed the most to the total phytoplankton production (approx. 50%) followed by coccolithophores and chlorophytes. Primary production by diatoms was highest in high latitude (>45 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nino Index, MEI) and 'regional' climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.
NASA Astrophysics Data System (ADS)
Medvigy, D.; Levy, J.; Xu, X.; Batterman, S. A.; Hedin, L.
2013-12-01
Ecosystems, by definition, involve a community of organisms. These communities generally exhibit heterogeneity in their structure and composition as a result of local variations in climate, soil, topography, disturbance history, and other factors. Climate-driven shifts in ecosystems will likely include an internal re-organization of community structure and composition and as well as the introduction of novel species. In terms of vegetation, this ecosystem heterogeneity can occur at relatively small scales, sometimes of the order of tens of meters or even less. Because this heterogeneous landscape generally has a variable and nonlinear response to environmental perturbations, it is necessary to carefully aggregate the local competitive dynamics between individual plants to the large scales of tens or hundreds of kilometers represented in climate models. Accomplishing this aggregation in a computationally efficient way has proven to be an extremely challenging task. To meet this challenge, the Ecosystem Demography 2 (ED2) model statistically characterizes a distribution of local resource environments, and then simulates the competition between individuals of different sizes and species (or functional groupings). Within this framework, it is possible to explicitly simulate the impacts of climate change on ecosystem structure and composition, including both internal re-organization and the introduction of novel species or functional groups. This presentation will include several illustrative applications of the evolution of ecosystem structure and composition under climate change. One application pertains to the role of nitrogen-fixing species in tropical forests. Will increasing CO2 concentrations increase the demand for nutrients and perhaps give a competitive edge to nitrogen-fixing species? Will potentially warmer and drier conditions make some tropical forests more water-limited, reducing the demand for nitrogen, thereby giving a competitive advantage to non-nitrogen-fixing species? Will the response of nitrogen-fixing species to climate change be sensitive to local disturbance histories?
Statistical downscaling of regional climate scenarios for the French Alps : Impacts on snow cover
NASA Astrophysics Data System (ADS)
Rousselot, M.; Durand, Y.; Giraud, G.; Mérindol, L.; Déqué, M.; Sanchez, E.; Pagé, C.; Hasan, A.
2010-12-01
Mountain areas are particularly vulnerable to climate change. Owing to the complexity of mountain terrain, climate research at scales relevant for impacts studies and decisive for stakeholders is challenging. A possible way to bridge the gap between these fine scales and those of the general circulation models (GCMs) consists of combining high-resolution simulations of Regional Climate Models (RCMs) to statistical downscaling methods. The present work is based on such an approach. It aims at investigating the impacts of climate change on snow cover in the French Alps for the periods 2021-2050 and 2071-2100 under several IPCC hypotheses. An analogue method based on high resolution atmospheric fields from various RCMs and climate reanalyses is used to simulate local climate scenarios. These scenarios, which provide meteorological parameters relevant for snowpack evolution, subsequently feed the CROCUS snow model. In these simulations, various sources of uncertainties are thus considered (several greenhouse gases emission scenarios and RCMs). Results are obtained for different regions of the French Alps at various altitudes. For all scenarios, temperature increase is relatively uniform over the Alps. This regional warming is larger than that generally modeled at the global scale (IPCC, 2007), and particularly strong in summer. Annual precipitation amounts seem to decrease, mainly as a result of decreasing precipitation trends in summer and fall. As a result of these climatic evolutions, there is a general decrease of the mean winter snow depth and seasonal snow duration for all massifs. Winter snow depths are particularly reduced in the Northern Alps. However, the impact on seasonal snow duration is more significant in the Southern and Extreme Southern Alps, since these regions are already characterized by small winter snow depths at low elevations. Reference : IPCC (2007a). Climate change 2007 : The physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. In : Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor, and H.L. Miller (eds.). Cambridge University Press, Cambridge, UK and New York, NY, USA. This work is performed in the framework of the SCAMPEI ANR (French research project).
NASA Technical Reports Server (NTRS)
1984-01-01
The Global Modeling and Simulation Branch (GMSB) of the Laboratory for Atmospheric Sciences (GLAS) is engaged in general circulation modeling studies related to global atmospheric and oceanographic research. The research activities discussed are organized into two disciplines: Global Weather/Observing Systems and Climate/Ocean-Air Interactions. The Global Weather activities are grouped in four areas: (1) Analysis and Forecast Studies, (2) Satellite Observing Systems, (3) Analysis and Model Development, (4) Atmospheric Dynamics and Diagnostic Studies. The GLAS Analysis/Forecast/Retrieval System was applied to both FGGE and post FGGE periods. The resulting analyses have already been used in a large number of theoretical studies of atmospheric dynamics, forecast impact studies and development of new or improved algorithms for the utilization of satellite data. Ocean studies have focused on the analysis of long-term global sea surface temperature data, for use in the study of the response of the atmosphere to sea surface temperature anomalies. Climate research has concentrated on the simulation of global cloudiness, and on the sensitivities of the climate to sea surface temperature and ground wetness anomalies.
The UPSCALE project: a large simulation campaign
NASA Astrophysics Data System (ADS)
Mizielinski, Matthew; Roberts, Malcolm; Vidale, Pier Luigi; Schiemann, Reinhard; Demory, Marie-Estelle; Strachan, Jane
2014-05-01
The development of a traceable hierarchy of HadGEM3 global climate models, based upon the Met Office Unified Model, at resolutions from 135 km to 25 km, now allows the impact of resolution on the mean state, variability and extremes of climate to be studied in a robust fashion. In 2011 we successfully obtained a single-year grant of 144 million core hours of supercomputing time from the PRACE organization to run ensembles of 27 year atmosphere-only (HadGEM3-A GA3.0) climate simulations at 25km resolution, as used in present global weather forecasting, on HERMIT at HLRS. Through 2012 the UPSCALE project (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) ran over 650 years of simulation at resolutions of 25 km (N512), 60 km (N216) and 135 km (N96) to look at the value of high resolution climate models in the study of both present climate and a potential future climate scenario based on RCP8.5. Over 400 TB of data was produced using HERMIT, with additional simulations run on HECToR (UK supercomputer) and MONSooN (Met Office NERC Supercomputing Node). The data generated was transferred to the JASMIN super-data cluster, hosted by STFC CEDA in the UK, where analysis facilities are allowing rapid scientific exploitation of the data set. Many groups across the UK and Europe are already taking advantage of these facilities and we welcome approaches from other interested scientists. This presentation will briefly cover the following points; Purpose and requirements of the UPSCALE project and facilities used. Technical implementation and hurdles (model porting and optimisation, automation, numerical failures, data transfer). Ensemble specification. Current analysis projects and access to the data set. A full description of UPSCALE and the data set generated has been submitted to Geoscientific Model development, with overview information available from http://proj.badc.rl.ac.uk/upscale .
A Dynamical Downscaling study over the Great Lakes Region Using WRF-Lake: Historical Simulation
NASA Astrophysics Data System (ADS)
Xiao, C.; Lofgren, B. M.
2014-12-01
As the largest group of fresh water bodies on Earth, the Laurentian Great Lakes have significant influence on local and regional weather and climate through their unique physical features compared with the surrounding land. Due to the limited spatial resolution and computational efficiency of general circulation models (GCMs), the Great Lakes are geometrically ignored or idealized into several grid cells in GCMs. Thus, the nested regional climate modeling (RCM) technique, known as dynamical downscaling, serves as a feasible solution to fill the gap. The latest Weather Research and Forecasting model (WRF) is employed to dynamically downscale the historical simulation produced by the Geophysical Fluid Dynamics Laboratory-Coupled Model (GFDL-CM3) from 1970-2005. An updated lake scheme originated from the Community Land Model is implemented in the latest WRF version 3.6. It is a one-dimensional mass and energy balance scheme with 20-25 model layers, including up to 5 snow layers on the lake ice, 10 water layers, and 10 soil layers on the lake bottom. The lake scheme is used with actual lake points and lake depth. The preliminary results show that WRF-Lake model, with a fine horizontal resolution and realistic lake representation, provides significantly improved hydroclimates, in terms of lake surface temperature, annual cycle of precipitation, ice content, and lake-effect snowfall. Those improvements suggest that better resolution of the lakes and the mesoscale process of lake-atmosphere interaction are crucial to understanding the climate and climate change in the Great Lakes region.
COSP: Satellite simulation software for model assessment
Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...
2011-08-01
Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boer, George J.; Smith, Douglas M.; Cassou, Christophe
The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less
NASA Astrophysics Data System (ADS)
Hurford, Anthony; Harou, Julien
2015-04-01
Climate change has challenged conventional methods of planning water resources infrastructure investment, relying on stationarity of time-series data. It is not clear how to best use projections of future climatic conditions. Many-objective simulation-optimisation and trade-off analysis using evolutionary algorithms has been proposed as an approach to addressing complex planning problems with multiple conflicting objectives. The search for promising assets and policies can be carried out across a range of climate projections, to identify the configurations of infrastructure investment shown by model simulation to be robust under diverse future conditions. Climate projections can be used in different ways within a simulation model to represent the range of possible future conditions and understand how optimal investments vary according to the different hydrological conditions. We compare two approaches, optimising over an ensemble of different 20-year flow and PET timeseries projections, and separately for individual future scenarios built synthetically from the original ensemble. Comparing trade-off curves and surfaces generated by the two approaches helps understand the limits and benefits of optimising under different sets of conditions. The comparison is made for the Tana Basin in Kenya, where climate change combined with multiple conflicting objectives of water management and infrastructure investment mean decision-making is particularly challenging.
Sustained Climate Assessments in California: Linkages with Local and National Efforts
NASA Astrophysics Data System (ADS)
Franco, G.; Bedsworth, L. W.
2016-12-01
This presentation will include discussions about the nature of the sustained Climate Assessments in California and their links to local, regional, and national efforts. The State of California has been supporting regional climate change science for more than two decades to complement federal and international research efforts. State sponsored research has been extremely useful to inform climate policy action and long-term planning in California. California has undertaken six climate assessments since 1998; the last three of these began in 2006 in response to an Executive Order from the Governor. California is now coordinating its next assessment (2018) not only with local/regional efforts (e.g., a group of studies focused on the San Francisco Bay region) but also with USGCRP and the next National Assessment. California is also already supporting foundation work for models and tools that would be used for the 2022 California Assessment.
Hydrological Climate Classification: Can We Improve on Köppen-Geiger?
NASA Astrophysics Data System (ADS)
Knoben, W.; Woods, R. A.; Freer, J. E.
2017-12-01
Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which can explain streamflow differences between geographically close locations. Summarizing, this work shows that hydrology needs its own way to structure climate forcing, acknowledging that climates vary gradually on a global scale and explicitly including those climate aspects that drive seasonal changes in hydrologic regimes.
NASA Astrophysics Data System (ADS)
Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro
2016-04-01
The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.
Introduction of Energy and Climate Mitigation Policy Issues in Energy - Environment Model of Latvia
NASA Astrophysics Data System (ADS)
Klavs, G.; Rekis, J.
2016-12-01
The present research is aimed at contributing to the Latvian national climate policy development by projecting total GHG emissions up to 2030, by evaluating the GHG emission reduction path in the non-ETS sector at different targets set for emissions reduction and by evaluating the obtained results within the context of the obligations defined by the EU 2030 policy framework for climate and energy. The method used in the research was bottom-up, linear programming optimisation model MARKAL code adapted as the MARKAL-Latvia model with improvements for perfecting the integrated assessment of climate policy. The modelling results in the baseline scenario, reflecting national economic development forecasts and comprising the existing GHG emissions reduction policies and measures, show that in 2030 emissions will increase by 19.1 % compared to 2005. GHG emissions stabilisation and reduction in 2030, compared to 2005, were researched in respective alternative scenarios. Detailed modelling and analysis of the Latvian situation according to the scenario of non-ETS sector GHG emissions stabilisation and reduction in 2030 compared to 2005 have revealed that to implement a cost effective strategy of GHG emissions reduction first of all a policy should be developed that ensures effective absorption of the available energy efficiency potential in all consumer sectors. The next group of emissions reduction measures includes all non-ETS sectors (industry, services, agriculture, transport, and waste management).
NASA Astrophysics Data System (ADS)
de Noblet, N.; Pitman, A.; Participants, Lucid
2009-04-01
The project "Land-Use and Climate, IDentification of robust impacts" (LUCID) was conceived under the auspices of IGBP-iLEAPS and GEWEX-GLASS, to address the robustness of 'local' and possible remote impacts of land-use induced land-cover changes (LCC). LUCID explores, using methodologies that major climate modelling groups recognise, those impacts of LCC that are robust - that is, above the noise generated by model variability and consistent across a suite of climate models. To start with, seven climate models were run, in ensemble mode (5 realisations per 31-years long experiment), with prescribed observed sea-surface temperatures (SSTs) and sea ice extent (SIc). Pre-industrial and present-day simulations were used to explore the impacts of biogeophysical impacts of human-induced land cover change. The imposed LCC perturbation led to statistically significant changes in latent heat flux and near-surface temperature over the regions of land cover change, but few significant changes in precipitation. Our results show no common remote impacts of land cover change. They also highlight a dilemma for both historical hind-casts and future projections; land cover change is regionally important, but it is not feasible within the time frame of the next IPCC (AR5) assessment to implement this change commonly across multiple models. Further analysis are in progress and will be presented to identify the continental regions where changes in LCC may have been more important than the combined changes in SSTs, SIc and CO2 between the pre-industrial times and nowadays.
NASA Astrophysics Data System (ADS)
Feng, X.; Shen, S.
2014-12-01
The US coastline, over the past few years, has been overwhelmed by major storms including Hurricane Katrina (2005), Ike (2008), Irene (2011), and Sandy (2012). Supported by a growing and extensive body of evidence, a majority of research agrees hurricane activities have been enhanced due to climate change. However, the precise prediction of hurricane induced inundation remains a challenge. This study proposed a probabilistic inundation map based on a Statistically Modeled Storm Database (SMSD) to assess the probabilistic coastal inundation risk of Southwest Florida for near-future (20 years) scenario considering climate change. This map was processed through a Joint Probability Method with Optimal-Sampling (JPM-OS), developed by Condon and Sheng in 2012, and accompanied by a high resolution storm surge modeling system CH3D-SSMS. The probabilistic inundation map shows a 25.5-31.2% increase in spatially averaged inundation height compared to an inundation map of present-day scenario. To estimate climate change impacts on coastal communities, socioeconomic analyses were conducted using both the SMSD based probabilistic inundation map and the present-day inundation map. Combined with 2010 census data and 2012 parcel data from Florida Geographic Data Library, the differences of economic loss between the near-future and present day scenarios were used to generate an economic exposure map at census block group level to reflect coastal communities' exposure to climate change. The results show that climate change induced inundation increase has significant economic impacts. Moreover, the impacts are not equally distributed among different social groups considering their social vulnerability to hazards. Social vulnerability index at census block group level were obtained from Hazards and Vulnerability Research Institute. The demographic and economic variables in the index represent a community's adaptability to hazards. Local Moran's I was calculated to identify the clusters of highly exposed and vulnerable communities. The economic-exposure cluster map was overlapped with social-vulnerability cluster map to identify communities with low adaptive capability but high exposure. The result provides decision makers an intuitive tool to identify most susceptible communities for adaptation.
An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate
Weijerman, Mariska; Fulton, Elizabeth A.; Kaplan, Isaac C.; Gorton, Rebecca; Leemans, Rik; Mooij, Wolf M.; Brainard, Russell E.
2015-01-01
Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5–8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors. PMID:26672983
An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate.
Weijerman, Mariska; Fulton, Elizabeth A; Kaplan, Isaac C; Gorton, Rebecca; Leemans, Rik; Mooij, Wolf M; Brainard, Russell E
2015-01-01
Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5-8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors.
Moragrega, Concepció; Puig, Mireia; Ruz, Lídia; Montesinos, Emilio; Llorente, Isidre
2018-02-01
Brown spot of pear, caused by the fungus Stemphylium vesicarium, is an emerging disease of economic importance in several pear-growing areas in Europe. In recent years, new control strategies combining sanitation practices and fungicide applications according to developed forecasting models have been introduced to manage the disease. However, the pathogenic and saprophytic behavior of this pathogen makes it difficult to manage the disease. In addition, climate change can also result in variations in the severity and geographical distribution of the disease. In this study, ecological and epidemiological aspects of brown spot of pear disease related to inoculum characterization and climate change impact were elucidated. The pathogenic variation in S. vesicarium populations from pear orchards and its relationship to inoculum sources (air samples, leaf debris, and infected host and nonhost tissues) was determined using multivariate analysis. In total, six variables related to infection and disease development on cultivar Conference pear detached leaves of 110 S. vesicarium isolates were analyzed. A high proportion of isolates (42%) were nonpathogenic to pear; 85% of these nonpathogenic isolates were recovered from air samples. Most isolates recovered from lesions (93%) and pseudothecia (83%) were pathogenic to pear. A group of pathogenic isolates rapidly infected cultivar Conference pear leaves resulted in disease increase that followed a monomolecular model, whereas some S. vesicarium isolates required a period of time after inoculation to initiate infection and resulted in disease increase that followed a logistic model. The latter group was mainly composed of isolates recovered from pseudothecia on leaf debris, whereas the former group was mainly composed of isolates recovered from lesions on pear fruit and leaves. The relationship between the source of inoculum and pathogenic/aggressiveness profile was confirmed by principal component analysis. The effect of climate change on disease risk was analyzed in two pear-growing areas of Spain under two scenarios (A2 and B1) and for three periods (2005 to 2009, 2041 to 2060, and 2081 to 2100). Simulations showed that the level of risk predicted by BSPcast model increased to high or very high under the two scenarios and was differentially distributed in the two regions. This study is an example of how epidemiological models can be used to predict not only the onset of infections but also how climate change could affect brown spot of pear. [Formula: see text] Copyright © 2018 The Author(s). This is an open-access article distributed under the CC BY-NC-ND 4.0 International license .
Use of Giovanni System in Public Health Application
NASA Technical Reports Server (NTRS)
Soebiyanto, Radina; Kiang, Richard K.
2012-01-01
The role of environment and climate in propagating infectious disease has long been recognized since the 5th century. The effect is particularly evident in vector-borne diseases such as malaria where temperature, precipitation and humidity influence the lifecycle of the pathogens and mosquitoes. Likewise, the transmission of respiratory diseases is also often associated with climatic factors. For example, a recent study showed that low humidity and temperature provides efficient condition for seasonal influenza transmission. Understanding of how environment and climate affect infectious diseases would essentially provide guides to prevent and control the spread of disease. Toward this end, our group has developed models for infectious disease risk such as for malaria, dengue and influenza that are driven by climatic and environmental inputs. Results will be presented, especially those that used TRMM data from GIOVANNI.
NASA Astrophysics Data System (ADS)
Mangosing, D. C.; Chen, G.; Kusterer, J.; Rinsland, P.; Perez, J.; Sorlie, S.; Parker, L.
2011-12-01
One of the objectives of the NASA Langley Research Center's MEaSURES project, "Creating a Unified Airborne Database for Model Assessment", is the development of airborne Earth System Data Records (ESDR) for the regional and global model assessment and validation activities performed by the tropospheric chemistry and climate modeling communities. The ongoing development of ADAM, a web site designed to access a unified, standardized and relational ESDR database, meets this objective. The ESDR database is derived from publically available data sets, from NASA airborne field studies to airborne and in-situ studies sponsored by NOAA, NSF, and numerous international partners. The ADAM web development activities provide an opportunity to highlight a growing synergy between the Airborne Science Data for Atmospheric Composition (ASD-AC) group at NASA Langley and the NASA Langley's Atmospheric Sciences Data Center (ASDC). These teams will collaborate on the ADAM web application by leveraging the state-of-the-art service and message-oriented data distribution architecture developed and implemented by ASDC and using a web-based tool provided by the ASD-AC group whose user interface accommodates the nuanced perspective of science users in the atmospheric chemistry and composition and climate modeling communities.
ERIC Educational Resources Information Center
Johnson, Joseph Hamilton
2012-01-01
The Full Service Schools (FSS) reform model is an inter-agency collaboration between the District of Columbia Public Schools (DCPS), Choices, Inc., Insights Education Group and the DC Department of Mental Health. This comprehensive school reform model is based in the Response to Intervention paradigm and is designed to mitigate student academic…
Eyring, Veronika; Bony, Sandrine; Meehl, Gerald A.; ...
2016-05-26
By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) andmore » CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.« less
Local climatic adaptation in a widespread microorganism.
Leducq, Jean-Baptiste; Charron, Guillaume; Samani, Pedram; Dubé, Alexandre K; Sylvester, Kayla; James, Brielle; Almeida, Pedro; Sampaio, José Paulo; Hittinger, Chris Todd; Bell, Graham; Landry, Christian R
2014-02-22
Exploring the ability of organisms to locally adapt is critical for determining the outcome of rapid climate changes, yet few studies have addressed this question in microorganisms. We investigated the role of a heterogeneous climate on adaptation of North American populations of the wild yeast Saccharomyces paradoxus. We found abundant among-strain variation for fitness components across a range of temperatures, but this variation was only partially explained by climatic variation in the distribution area. Most of fitness variation was explained by the divergence of genetically distinct groups, distributed along a north-south cline, suggesting that these groups have adapted to distinct climatic conditions. Within-group fitness components were correlated with climatic conditions, illustrating that even ubiquitous microorganisms locally adapt and harbour standing genetic variation for climate-related traits. Our results suggest that global climatic changes could lead to adaptation to new conditions within groups, or changes in their geographical distributions.
Measuring Student Improvement in Lower- and Upper-Level University Climate Science Courses
NASA Astrophysics Data System (ADS)
Harris, S. E.; Taylor, S. V.; Schoonmaker, J. E.; Lane, E.; Francois, R. H.; Austin, P.
2011-12-01
What do university students know about climate? What do they learn in a climate course? On the second-to-last day of a course about global climate change, only 48% of our upper-level science students correctly answered a multiple-choice question about the greenhouse effect. The good news: improvement. Only 16% had answered correctly on the first day of class. The bad news: the learning opportunities we've provided appear to have missed more than half the class on a fundamental climate concept. To evaluate the effectiveness of instruction on student learning about climate, we have developed a prototype assessment tool, designed to be deployed as a low-stakes pre-post test. The items included were validated through student interviews to ensure that students interpret the wording and answer choices in the way we intend. This type of validated assessment, administered both at the beginning and end of term, with matched individuals, provides insight regarding the baseline knowledge with which our students enter a course, and the impact of that course on their learning. We administered test items to students in (1) an upper-level climate course for science majors and (2) a lower-level climate course open to all students. Some items were given to both groups, others to only one of the groups. Both courses use evidence-based pedagogy with active student engagement (clickers, small group activities, regular pre-class preparation). Our results with upper-level students show strong gains in student thinking (>70% of students who missed a question on the pre-test answered correctly on the post-test) about stock-and-flow (box model) problems, annual cycles in the Keeling curve, ice-albedo feedbacks, and isotopic fractionation. On different questions, lower-level students showed strong gains regarding albedo and blackbody emission spectra. Both groups show similar baseline knowledge and lower-than-expected gains on greenhouse effect fundamentals, and zero gain regarding the relative importance of different greenhouse gases. A larger percentage of upper-level students (compared to lower-level students) arrive with correct knowledge comparing different greenhouse gases, and explanations of annual cycles in the Keeling curve, but both groups show similar gains with instruction. Instructors can use feedback from these pre-post assessment results to iteratively modify and test the learning opportunities they provide. We aim to continue development and further validation of this tool such that it can be used in many university-level climate courses.
Assessing the Vulnerability of Agriculture to Climate Change in Jordan
NASA Astrophysics Data System (ADS)
Khresat, Sa'eb; Shraidaeh, Fadi; Maddat, Amer
2015-04-01
Climate change represents one of the greatest environmental, social and economic threats facing Jordan. In particular, the combined effects of climate change and water scarcity threaten to affect food and water resources that are critical for livelihoods in Jordan. This is especially true for those communities who live in the dryland area in the country and who rely wholly on rain-fed agriculture. The exact nature and extent of the impact of climate change on temperature and precipitation distribution pattern remain uncertain and it is the poor and vulnerable who will be the most susceptible to climate change adverse effects. A vulnerability assessment of rain fed agriculture to climate change and variability in semi-arid parts of Jordan was conducted in 2014. The purpose of this study is to assess the vulnerability and resilience of the most vulnerable groups where rainfed and irrigated agriculture is practiced. Also, the study focused on quantifying the impacts on agricultural productivity in response to climate change. This will help policymakers and researchers better understand and anticipate the likely impacts of climate change on agriculture and on vulnerable communities in Jordan. Also, it will provide them with tools to identify and implement appropriate adaptation strategies. The data used includes; Representative Concentration Pathways (RCPs), RCP 4.5 and RCP 8.5 adopted by the IPCC for its fifth Assessment Report (AR5). Those pathways were used for climate modeling. A decision support system (DSSAT) for agricultural production was used to assess the impact of climate changes on agricultural production. This approach was used for the Identification of climate change risk and their impacts on Agriculture. Outputs from models are used to assess the vulnerability of farmers and crops to climate and socio-economic change by estimating their sensitivity and capacity to adapt to external factors as a means of identifying what causes the differences in their vulnerability. Based on the projection models for the area, average temperature in Jordan is projected to increase between 1.2 and 1.6°C by 2050. These upward temperature trends are projected to continue beyond 2050. Projections for precipitation trends are projected to decrease by 16% by the year 2050. Evaporation is likely to increase due to higher temperatures. This is likely to increase the incidence of drought potential since precipitation is projected to decrease. It is concluded that the Overall vulnerability of agriculture to climate change in Jordan is high, where impacts such as drought and increased temperatures and decreased precipitation will be more pronounced. Major implications on rain fed agriculture are possible shorter growing season, increasing moisture and heat stress to field and horticultural crops and eventually low income and food insecurity. There were different impacts among studied communities, which is related to the: economic capability, local knowledge, physical infrastructure, institutional capacity, modern technology used, age group of farmers and diversification of their income.
ERIC Educational Resources Information Center
Hester, Paul H.
This study sought to demonstrate how an interactive model can be used as a "semiotic" tool to reconcile contrasting views of the role of the college professor. The study used concepts of group dynamics to study classroom leadership, climate, and expectations and a social-psychological perspective was used to analyze group interaction patterns as…
Improving Teacher Content Knowledge about the Physical Basis of Climate Change
NASA Astrophysics Data System (ADS)
Gaboardi, M.
2009-12-01
In order for teachers to guide students to a deeper understanding of climate change science, teachers themselves must have a firm comprehension of: - the climate system, - how changes in climate can be measured over time, - how past changes are investigated. Improving teacher content knowledge about the physical basis of climate change, and the sources of paleoclimate data, was the primary focus of the 2009 Florida PROMiSE (Partnership to Rejuvenate and Optimize Mathematics and Science Education in Florida) Climate Change Institute. Our team of four, including two scientists, a district resource teacher, and a practicing classroom teacher, collaborated to create and implement 60 hours of professional development for teachers of grades 4-9. First we determined what primary learning outcome we expected: teachers should be able to unravel a basic multi-proxy paleoclimate record (ice core) and convey that in formation in terms of climate change on earth. We then constructed a concept map containing major concepts teachers would need to interpret their records. During the first week, each day was devoted to a major concept, and included: - stations, at which each group of four teachers openly explored components or misconceptions central to that concept; - a station debrief, during which all groups shared findings and were guided to understand the links between the different stations; - a whole group structured discussion, which helped to crystallize the main concept; - time for teachers to reflect on their own learning. Our district resource teacher and our classroom teacher led the development and instruction of stations; our scientists mainly led structured discussions, though all facilitators participated in all levels of development and implementation. The second week included less structure. Learners worked in groups of of four and were able to handle more complex inquiry. The week culminated in the day-long dissection of model ice cores, presentation of each group’s climate change findings, relation of their discoveries to actual findings from ice core data, and placement of that information within the context of climate change over a variety of time scales. Both formal and informal assessment demonstrate that: - teacher content knowledge increased substantially, - teachers report that the various levels of guided inquiry employed during instruction were helpful for their own learning, - teachers communicate that the content and pedagogical knowledge gained during the institute would be useful to them in their classrooms.
Plant community dynamics and restoring Louisiana's wetland ecosystems
NASA Astrophysics Data System (ADS)
Duke-Sylvester, S. M.; Visser, J.
2017-12-01
We have developed a computational model of plant community dynamics. Our model is designed to evaluate the effects of management actions on the structure and health of Louisiana's coastal wetland plant communities. A number of projects have been initiated or proposed to preserve and restore this ecosystem while still allowing the area to support Louisiana's economy. These projects involve both modification of the flow of freshwater as well as restoring natural wetlands. Evaluating the long term effects of these projects is complex and involves numerous moving pieces operating over an extensive and diverse landscape. The situation is further complicated by in sea level rise and climate change associated with global warming. The vegetation model is part of a larger set of linked models that include hydrology and soil morphology. Using hydrological conditions projected by the linked hydrology models, we are able to evaluate the effects of anthropogenic and climatic changes on Louisiana's wetland plant communities. Unique features of our model include replacing the division of wetlands into coarse groups defined by salinity conditions with species level responses to environmental conditions and extending the spatial scale of modeling to encompass the entirety of Louisiana's Gulf coast. Model results showing the potential impact of alternative management and climate change scenarios are presented.
NASA Astrophysics Data System (ADS)
Foster, J. R.; D'Amato, A. W.; Itter, M.; Reinikainen, M.; Curzon, M.
2017-12-01
The terrestrial carbon cycle is perturbed when disturbances remove leaf biomass from the forest canopy during the growing season. Changes in foliar biomass arise from defoliation caused by insects, disease, drought, frost or human management. As ephemeral disturbances, these often go undetected and their significance to models that predict forest growth from climatic drivers remains unknown. Here, we seek to distinguish the roles of weather vs. canopy disturbance on forest growth by using dense Landsat time-series to quantify departures in mean phenology that in turn predict changes in leaf biomass. We estimated a foliar biomass index (FBMI) from 1984-2016, and predict plot-level wood growth over 28 years on 156 tree-ring monitoring plots in Minnesota, USA. We accessed the entire Landsat archive (sensors 4, 5 & 7) to compute FBMI using Google Earth Engine's cloud computing platform (GEE). GEE allows this pixel-level approach to be applied at any location; a feature we demonstrate with published wood-growth data from flux tower sites. Our Bayesian models predicted biomass changes from tree-ring plots as a function of Landsat FBMI and annual climate data. We expected model parameters to vary by tree functional groups defined by differences in xylem anatomy and leaf longevity, two traits with linkages to phenology, as reported in a recent review. We found that Landsat FBMI was a surprisingly strong predictor of aggregate wood-growth, explaining up to 80% of annual growth variation for some deciduous plots. Growth responses to canopy disturbance varied among tree functional groups, and the importance of some seasonal climate metrics diminished or changed sign when FBMI was included (e.g. fall and spring climatic water deficit), while others remained unchanged (current and lagged summer deficit). Insights emerging from these models can clear up sources of persistent uncertainty and open a new frontier for models of forest productivity.
NASA Astrophysics Data System (ADS)
Rodysill, J. R.
2017-12-01
Proxy-based reconstructions provide vital information for developing histories of environmental and climate changes. Networks of spatiotemporal paleoclimate information are powerful tools for understanding dynamical processes within the global climate system and improving model-based predictions of the patterns and magnitudes of climate changes at local- to global-scales. Compiling individual paleoclimate records and integrating reconstructed climate information in the context of an ensemble of multi-proxy records, which are fundamental for developing a spatiotemporal climate data network, are hindered by challenges related to data and information accessibility, chronological uncertainty, sampling resolution, climate proxy type, and differences between depositional environments. The U.S. Geological Survey (USGS) North American Holocene Climate Synthesis Working Group has been compiling and integrating multi-proxy paleoclimate data as part of an ongoing effort to synthesize Holocene climate records from North America. The USGS North American Holocene Climate Synthesis Working Group recently completed a late Holocene hydroclimate synthesis for the North American continent using several proxy types from a range of depositional environments, including lakes, wetlands, coastal marine, and cave speleothems. Using new age-depth relationships derived from the Bacon software package, we identified century-scale patterns of wetness and dryness for the past 2000 years with an age uncertainty-based confidence rating for each proxy record. Additionally, for highly-resolved North American lake sediment records, we computed average late Holocene sediment deposition rates and identified temporal trends in age uncertainty that are common to multiple lakes. This presentation addresses strengths and challenges of compiling and integrating data from different paleoclimate archives, with a particular focus on lake sediments, which may inform and guide future paleolimnological studies.
Validation of the group nuclear safety climate questionnaire.
Navarro, M Felisa Latorre; Gracia Lerín, Francisco J; Tomás, Inés; Peiró Silla, José María
2013-09-01
Group safety climate is a leading indicator of safety performance in high reliability organizations. Zohar and Luria (2005) developed a Group Safety Climate scale (ZGSC) and found it to have a single factor. The ZGSC scale was used as a basis in this study with the researchers rewording almost half of the items on this scale, changing the referents from the leader to the group, and trying to validate a two-factor scale. The sample was composed of 566 employees in 50 groups from a Spanish nuclear power plant. Item analysis, reliability, correlations, aggregation indexes and CFA were performed. Results revealed that the construct was shared by each unit, and our reworded Group Safety Climate (GSC) scale showed a one-factor structure and correlated to organizational safety climate, formalized procedures, safety behavior, and time pressure. This validation of the one-factor structure of the Zohar and Luria (2005) scale could strengthen and spread this scale and measure group safety climate more effectively. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.
Model dependence and its effect on ensemble projections in CMIP5
NASA Astrophysics Data System (ADS)
Abramowitz, G.; Bishop, C.
2013-12-01
Conceptually, the notion of model dependence within climate model ensembles is relatively simple - modelling groups share a literature base, parametrisations, data sets and even model code - the potential for dependence in sampling different climate futures is clear. How though can this conceptual problem inform a practical solution that demonstrably improves the ensemble mean and ensemble variance as an estimate of system uncertainty? While some research has already focused on error correlation or error covariance as a candidate to improve ensemble mean estimates, a complete definition of independence must at least implicitly subscribe to an ensemble interpretation paradigm, such as the 'truth-plus-error', 'indistinguishable', or more recently 'replicate Earth' paradigm. Using a definition of model dependence based on error covariance within the replicate Earth paradigm, this presentation will show that accounting for dependence in surface air temperature gives cooler projections in CMIP5 - by as much as 20% globally in some RCPs - although results differ significantly for each RCP, especially regionally. The fact that the change afforded by accounting for dependence across different RCPs is different is not an inconsistent result. Different numbers of submissions to each RCP by different modelling groups mean that differences in projections from different RCPs are not entirely about RCP forcing conditions - they also reflect different sampling strategies.
Is temperature the main cause of dengue rise in non-endemic countries? The case of Argentina
2012-01-01
Background Dengue cases have increased during the last decades, particularly in non-endemic areas, and Argentina was no exception in the southern transmission fringe. Although temperature rise has been blamed for this, human population growth, increased travel and inefficient vector control may also be implicated. The relative contribution of geographic, demographic and climatic of variables on the occurrence of dengue cases was evaluated. Methods According to dengue history in the country, the study was divided in two decades, a first decade corresponding to the reemergence of the disease and the second including several epidemics. Annual dengue risk was modeled by a temperature-based mechanistic model as annual days of possible transmission. The spatial distribution of dengue occurrence was modeled as a function of the output of the mechanistic model, climatic, geographic and demographic variables for both decades. Results According to the temperature-based model dengue risk increased between the two decades, and epidemics of the last decade coincided with high annual risk. Dengue spatial occurrence was best modeled by a combination of climatic, demographic and geographic variables and province as a grouping factor. It was positively associated with days of possible transmission, human population number, population fall and distance to water bodies. When considered separately, the classification performance of demographic variables was higher than that of climatic and geographic variables. Conclusions Temperature, though useful to estimate annual transmission risk, does not fully describe the distribution of dengue occurrence at the country scale. Indeed, when taken separately, climatic variables performed worse than geographic or demographic variables. A combination of the three types was best for this task. PMID:22768874
NASA Astrophysics Data System (ADS)
Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald
2014-05-01
Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are accompanied by the WASCAL Graduate Research Program on the West African Climate System. The GRP-WACS provides ten scholarships per year for West African PhD students with a duration of three years. Present and future WASCAL PhD students will constitute one important user group of the Linux cluster that will be installed at the Competence Center in Ouagadougou, Burkina Faso. Regional Land-Atmosphere Simulations A key research activity of the WASCAL Core Research Program is the analysis of interactions between the land surface and the atmosphere to investigate how land surface changes affect hydro-meteorological surface fluxes such as evapotranspiration. Since current land surface models of global and regional climate models neglect dominant lateral hydrological processes such as surface runoff, a novel land surface model is used, the NCAR Distributed Hydrological Modeling System (NDHMS). This model can be coupled to WRF (WRF-Hydro) to perform two-way coupled atmospheric-hydrological simulations for the watershed of interest. Hardware and network prerequisites include a HPC cluster, network switches, internal storage media, Internet connectivity of sufficient bandwidth. Competences needed are HPC, storage, and visualization systems optimized for climate research, parallelization and optimization of climate models and workflows, efficient management of highest data volumes.
Profiles of perfectionism, parental climate, and burnout among competitive junior athletes.
Gustafsson, H; Hill, A P; Stenling, A; Wagnsson, S
2016-10-01
Recent research suggests that groups of athletes which differ in terms of perfectionism and perceptions of achievement climate can be identified. Moreover, these groups also differ in terms of burnout symptoms. The purpose of the current study was to extend this research by examining whether discernible groups can be identified based on scores of perfectionism and perceptions of parent-initiated climate and, then, whether these groups differ in terms of burnout. Two-hundred and thirty-seven Swedish junior athletes (124 males and 113 females aged 16-19) from a variety of sports completed measures of athlete burnout, multidimensional perfectionism, and parent-initiated motivational climate. Latent profile analysis identified four groups: non-perfectionistic athletes in a task-involving climate, moderately perfectionistic athletes in a task-involving climate, highly perfectionistic athletes in a task-involving climate, and highly perfectionistic athletes in a mixed climate. The latter two groups reported higher levels of burnout in comparison to other groups. The findings suggest that junior athletes high in perfectionism may be at comparatively greater risk to burnout and that this may especially be the case when they perceive their parents to emphasize concerns about failure and winning without trying one's best. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Climate scenarios for the Truckee-Carson River system
Dettinger, Michael; Sterle, Kelley; Simpson, Karen; Singletary, Loretta; Fitzgerald, Kelsey; McCarthy, Maureen
2017-01-01
In this study, the scenarios ultimately take the form of gridded, daily (maximum and minimum) temperatures and precipitation totals spanning the entire Truckee-Carson River System, from which meteorological inputs to various hydrologic, water-balance and watermanagement models can be extracted by other parts of the Water for the Seasons project and by other studies and stakeholders. Climate scenarios are constructed using: 1) survey data from interviews with 66 Truckee-Carson River System water-management and water-interest organizations to identify plausible drought and high-flow events that could stress the system irreparably; 2) input from the Stakeholder Affiliate Group and other modelers on the Water for the Seasons team to gain additional key stakeholder input with regard to organizational survey results and to identify the most pressing water-management issues being faced in the system; and 3) historical climate datasets used to simulate possible future conditions.
Shestakova, Tatiana A; Aguilera, Mònica; Ferrio, Juan Pedro; Gutiérrez, Emilia; Voltas, Jordi
2014-08-01
Identifying how physiological responses are structured across environmental gradients is critical to understanding in what manner ecological factors determine tree performance. Here, we investigated the spatiotemporal patterns of signal strength of carbon isotope discrimination (Δ(13)C) and oxygen isotope composition (δ(18)O) for three deciduous oaks (Quercus faginea (Lam.), Q. humilis Mill. and Q. petraea (Matt.) Liebl.) and one evergreen oak (Q. ilex L.) co-occurring in Mediterranean forests along an aridity gradient. We hypothesized that contrasting strategies in response to drought would lead to differential climate sensitivities between functional groups. Such differential sensitivities could result in a contrasting imprint on stable isotopes, depending on whether the spatial or temporal organization of tree-ring signals was analysed. To test these hypotheses, we proposed a mixed modelling framework to group isotopic records into potentially homogeneous subsets according to taxonomic or geographical criteria. To this end, carbon and oxygen isotopes were modelled through different variance-covariance structures for the variability among years (at the temporal level) or sites (at the spatial level). Signal-strength parameters were estimated from the outcome of selected models. We found striking differences between deciduous and evergreen oaks in the organization of their temporal and spatial signals. Therefore, the relationships with climate were examined independently for each functional group. While Q. ilex exhibited a large spatial dependence of isotopic signals on the temperature regime, deciduous oaks showed a greater dependence on precipitation, confirming their higher susceptibility to drought. Such contrasting responses to drought among oak types were also observed at the temporal level (interannual variability), with stronger associations with growing-season water availability in deciduous oaks. Thus, our results indicate that Mediterranean deciduous and evergreen oaks constitute two clearly differentiated functional groups in terms of their carbon and water economies, despite co-existing in a wide range of environments. In contrast, deciduous oaks form a rather homogeneous group in terms of climate sensitivity. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Lantuit, Hugues; Boike, Julia; Dahms, Melanie; Hubberten, Hans-Wolfgang
2013-04-01
The northern permafrost region contains approximately 50% of the estimated global below-ground organic carbon pool and more than twice as much as is contained in the current atmos-pheric carbon pool. The sheer size of this carbon pool, together with the large amplitude of predicted arctic climate change im-plies that there is a high potential for global-scale feedbacks from arctic climate change if these carbon reservoirs are desta-bilized. Nonetheless, significant gaps exist in our current state of knowledge that prevent us from producing accurate assess-ments of the vulnerability of the arctic permafrost to climate change, or of the implications of future climate change for global greenhouse gas (GHG) emissions. Specifically: • Our understanding of the physical and biogeochemical processes at play in permafrost areas is still insuffi-cient in some key aspects • Size estimates for the high latitude continental carbon and nitrogen stocks vary widely between regions and research groups. • The representation of permafrost-related processes in global climate models still tends to be rudimentary, and is one reason for the frequently poor perform-ances of climate models at high latitudes. The key objectives of PAGE21 are: • to improve our understanding of the processes affect-ing the size of the arctic permafrost carbon and nitro-gen pools through detailed field studies and monitor-ing, in order to quantify their size and their vulnerability to climate change, • to produce, assemble and assess high-quality datasets in order to develop and evaluate representations of permafrost and related processes in global models, • to improve these models accordingly, • to use these models to reduce the uncertainties in feed-backs from arctic permafrost to global change, thereby providing the means to assess the feasibility of stabili-zation scenarios, and • to ensure widespread dissemination of our results in order to provide direct input into the ongoing debate on climate-change mitigation. The concept of PAGE21 is to directly address these questions through a close interaction between monitoring activities, proc-ess studies and modeling on the pertinent temporal and spatial scales. Field sites have been selected to cover a wide range of environmental conditions for the validation of large scale mod-els, the development of permafrost monitoring capabilities, the study of permafrost processes, and for overlap with existing monitoring programs. PAGE21 will contribute to upgrading the project sites with the objective of providing a measurement baseline, both for process studies and for modeling programs. PAGE21 is determined to break down the traditional barriers in permafrost sciences between observational and model-supported site studies and large-scale climate modeling. Our concept for the interaction between site-scale studies and large-scale modeling is to establish and maintain a direct link be-tween these two areas for developing and evaluating, on all spatial scales, the land-surface modules of leading European global climate models taking part in the Coupled Model Inter-comparison Project Phase 5 (CMIP5), designed to inform the IPCC process. The timing of this project is such that the main scientific results from PAGE21, and in particular the model-based assessments will build entirely on new outputs and results from the CMIP5 Climate Model Intercomparison Project designed to inform the IPCC Fifth Assessment Report. However, PAGE21 is designed to leave a legacy that will en-dure beyond the lifetime of the projections that it produces. This legacy will comprise • an improved understanding of the key processes and parameters that determine the vulnerability of arctic permafrost to climate change, • the production of a suite of major European coupled climate models including detailed and validated repre-sentations of permafrost-related processes, that will reduce uncertainties in future climate projections pro-duced well beyond the lifetime of PAGE21, and • the training of a new generation of permafrost scien-tists who will bridge the long-standing gap between permafrost field science and global climate modeling, for the long-term benefit of science and society.
van der Fels-Klerx, H J; Olesen, J E; Naustvoll, L-J; Friocourt, Y; Mengelers, M J B; Christensen, J H
2012-01-01
Climate change is expected to affect food and feed safety, including the occurrence of natural toxins in primary crop and seafood production; however, to date, quantitative estimates are scarce. This study aimed to estimate the impact of climate change effects on mycotoxin contamination of cereal grains cultivated in the terrestrial area of north west Europe, and on the frequency of harmful algal blooms and contamination of shellfish with marine biotoxins in the North Sea coastal zone. The study focused on contamination of wheat with deoxynivalenol, and on abundance of Dinophysis spp. and the possible relationship with diarrhetic shellfish toxins. The study used currently available data and models. Global and regional climate models were combined with models of crop phenology, mycotoxin prediction models, hydrodynamic models and ecological models, with the output of one model being used as input for the other. In addition, statistical data analyses using existing national datasets from the study area were performed to obtain information on the relationships between Dinophysis spp. cell counts and contamination of shellfish with diarrhetic shellfish toxins as well as on frequency of cereal cropping. In this paper, a summary of the study is presented, and overall conclusions and recommendations are given. Climate change projections for the years 2031-2050 were used as the starting point of the analyses relative to a preceding 20-year baseline period from which the climate change signal was calculated. Results showed that, in general, climate change effects lead to advanced flowering and harvest of wheat, and increased risk of contamination of wheat with deoxynivalenol. Blooms of dinoflagellates were estimated to occur more often. If the group of Dinophysis spp. behaves similarly to other flagellates in the future then frequency of harmful algal blooms of Dinophysis spp. may also increase, but consequences for contamination of shellfish with diarrhetic shellfish toxins are uncertain. Climate change will also have indirect effects on toxin contamination, which may be equally important. For example, the frequency of cropping of wheat and maize in north Europe was projected to increase under climate change, which will also increase the risk of contamination of the grains with deoxynivalenol. Risk managers are encouraged to consider the entire range of the predictions of climate change effects on food safety hazards, rather than median or average values only. Furthermore, it is recommended to closely monitor levels of mycotoxins and marine biotoxins in the future, in particular related to risky situations associated with favourable climatic conditions for toxin producing organisms. In particular, it is important to pay attention to the continuity of collecting the right data, and the availability and accessibility of databases. On a European level, it is important to stress the need for harmonisation of terminology and data collection.
Big emitting nations and the 2°C target:beyond integrated assessment
NASA Astrophysics Data System (ADS)
Bows-Larkin, Alice; Sharmina, Maria; Kuriakose, Jaise; Anderson, Kevin
2015-04-01
This year, the United Nations Conference of the Parties in Paris is tasked with delivering a land-mark agreement on avoiding the 2°C warming associated with 'dangerous interference with the climate system'. If this happens, it will re-invigorate analyses of how global and national energy systems can deliver the rates of mitigation accompanying the 2°C threshold. Commonly such studies rely on detailed integrated assessment models combining economic and physical relationships to describe climate and energy systems. These allow the user to develop 'feasible' scenarios in terms of technology, infrastructure and efficiency change. This paper reflects upon the reliance of decision makers on the outcomes of these models, and their suitability for producing plausible outcomes. One criticism is how they can explore future societies under the pressures of climate change mitigation and adaptation given that their economic parameterisations are underpinned by historical relationships fit for a world unperturbed by climate change. A second relates to their theoretical basis being appropriate for articulating the outcome of marginal change, when the very futures they are set up to explore involve non-marginal adjustments - very radical cuts in CO2, or severe climate change impacts. Quantifying societal responses within such models is a particular challenge. Finally, these models downplay risks through disregarding low-probability, high-impact events and their consequences, including wars and migration. It is argued here that as currently formulated these tools are unsuitable for modelling the revolutionary transformations necessary to stay within 2°C carbon budgets, or similarly, futures with higher levels of warming and subsequent impacts. To address this deficiency, this paper takes a complementary approach to contextually explore the 'possibility space' appropriate for avoiding 2°C. In contrast to exercises that build future scenarios using 'immutable' relationships within and between the energy and climate systems, a more transparent and dynamic framing based on highly constrained cumulative carbon budgets is proposed. Building on previous assessments that use a similar approach by authors Anderson and Bows, this analysis looks beyond the contested 'Annex 1' and 'non-Annex 1' division to backcast what the remaining CO2 budget implies for the world's top emitting nations. The analysis takes the top 25 nations, responsible for 85% of global CO2, and groups these nations on the basis of similarities within their energy systems. Using a range of explicit variables a suite of scenarios for these groups, as well as the 'rest of the world', 'deforestation' and 'bunker fuel CO2' are then developed, all constrained within a range of 2°C carbon budgets. By varying the levels of near-term emissions from each group's energy system, under a highly constrained CO2 budget, important sensitivities are revealed. Results demonstrate the significance of the coming 1-5 years' levels of emissions of the highest emitting groups and the importance of bunker-fuel emissions in shaping our collective futures. They also illustrate that only non-marginal futures with radical transitions across all energy systems can now be reconciled with the 2°C policy objective.
Maldonado-Sánchez, Denisse; Gutiérrez-Rodríguez, Carla; Ornelas, Juan Francisco
2016-06-01
By integrating mitochondrial DNA (mtDNA), microsatellites and ecological niche modelling (ENM), we investigated the phylogeography of Mexican populations of the common bush-tanager Chlorospingus ophthalmicus to examine the relative role of geographical and ecological features, as well as Pleistocene climatic oscillations in driving the diversification. We sequenced mtDNA of individuals collected throughout the species range in Mexico and genotyped them at seven microsatellite loci. Phylogeographic, population genetics and coalescent methods were used to assess patterns of genetic structure, gene flow and demographic history. ENM was used to infer contractions and expansions at different time periods as well as differences in climatic conditions among lineages. The retrieved mitochondrial and microsatellite groups correspond with the fragmented cloud forest distribution in mountain ranges and morphotectonic provinces. Differing climatic conditions between mountain ranges were detected, and palaeodistribution modelling as well as demographic history analyses, indicated recent population expansions throughout the Sierra Madre Oriental (SMO). The marked genetic structure of C. ophthalmicus was promoted by the presence of ecological and geographical barriers that restricted the movement of individuals among mountain ranges. The SMO was mainly affected by Pleistocene climatic oscillations, with the moist forests model best fitting the displayed genetic patterns of populations in this mountain range. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Vano, J. A.
2013-12-01
By 2007, motivated by the ongoing drought and release of new climate model projections associated with the IPCC AR4 report, multiple independent studies had made estimates of future Colorado River streamflow. Each study had a unique approach, and unique estimate for the magnitude for mid-21st century streamflow change ranging from declines of only 6% to declines of as much as 45%. The differences among studies provided for interesting scientific debates, but to many practitioners this appeared to be just a tangle of conflicting predictions, leading to the question 'why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted?' In response, a group of scientists from academic and federal agencies, brought together through a NOAA cross-RISA project, set forth to identify the major sources of disparities and provide actionable science and guidance for water managers and decision makers. Through this project, four major sources of disparities among modeling studies were identified that arise from both methodological and model differences. These differences, in order of importance, are: (1) the Global Climate Models (GCMs) and emission scenarios used; (2) the ability of land surface hydrology and atmospheric models to simulate properly the high elevation runoff source areas; (3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and (4) the methods used to statistically downscale GCM scenarios. Additionally, reconstructions of pre-instrumental streamflows provided further insights about the greatest risk to Colorado River streamflow of a multi-decadal drought, like those observed in paleo reconstructions, exacerbated by a steady reduction in flows due to climate change. Within this talk I will provide an overview of these findings and insights into the opportunities and challenges encountered in the process of striving to make climate change projections more useful to water managers and decision makers.
Climate Variability and Phytoplankton in the Pacific Ocean
NASA Technical Reports Server (NTRS)
Rousseaux, Cecile
2012-01-01
The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (p<0.01) with the Multivariate El Nino Southern Oscillation Index (MEI). In the North Central Pacific, MEI and chlorophyll were significantly (p<0.01) correlated along with two of the phytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Nina events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.
Academic climate, well-being and academic performance in a university degree course.
Rania, Nadia; Siri, Anna; Bagnasco, Annamaria; Aleo, Giuseppe; Sasso, Loredana
2014-09-01
The psychological climate within organisations affects not only the behaviour and the attitude of group members, but also the performance of the group itself. According to the ecological model, this research examines how learning in different classroom contexts of the same nursing degree programme can affect academic performance, well-being, self-esteem and perceived climate. Four scales were used to assess students' perceptions by collecting primary data while academic performance was measured by obtaining students' academic records. A questionnaire completed by 391 first-year nursing students was administered. Differences were observed in the perceptions of climate and academic performance in different classroom contexts with trends, which did not always overlap; however, strong correlations were observed among self-esteem, well-being and climate, and schoolmate relationships. Universities should not merely train competent professionals but also build learning communities that support the well-being of relationships and the development of well-being contexts. The findings support the need for an educational intervention for improving the quality of life and well-being of the community and individual students. This type of intervention requires a 'compliant' organisational environment that puts studetns, teachers and professionals in the condition to practice their professional skills. © 2013 John Wiley & Sons Ltd.
The impacts of climate change on crops in China: A Ricardian analysis
NASA Astrophysics Data System (ADS)
Chen, Yongfu; Wu, Zhigang; Okamoto, Katsuo; Han, Xinru; Ma, Guoying; Chien, Hsiaoping; Zhao, Jing
2013-05-01
This paper assesses the impact of climate change on China's agricultural production at a cross-provincial level using the Ricardian approach, incorporating a multilevel model with farm-level group data. The farm-level group data includes 13,379 farm households, across 316 villages, distributed in 31 provinces. The empirical results show that, firstly, the marginal effects and elasticities of net crop revenue per hectare with respect to climate factors indicated that the annual impact of temperature on net crop revenue per hectare was positive, and the effect of increased precipitation was negative when looking at the national totals; secondly, the total impact of simulated climate change scenarios on net crop revenues per hectare at a Chinese national total level, was an increase of between 79 USD per hectare and 207 USD per hectare for the 2050s, and an increase from 140 USD per hectare to 355 USD per hectare for the 2080s. As a result, climate change may create a potential advantage for the development of Chinese agriculture, rather than a risk, especially for agriculture in the provinces of the Northeast, Northwest and North regions. However, the increased precipitation can lead to a loss of net crop revenue per hectare, especially for the provinces of the Southwest, Northwest, North and Northeast regions.
Bode, Antonio; Estévez, M Graciela; Varela, Manuel; Vilar, José A
2015-09-01
Phytoplankton is a sentinel of marine ecosystem change. Composed by many species with different life-history strategies, it rapidly responds to environment changes. An analysis of the abundance of 54 phytoplankton species in Galicia (NW Spain) between 1989 and 2008 to determine the main components of temporal variability in relation to climate and upwelling showed that most of this variability was stochastic, as seasonality and long term trends contributed to relatively small fractions of the series. In general, trends appeared as non linear, and species clustered in 4 groups according to the trend pattern but there was no defined pattern for diatoms, dinoflagellates or other groups. While, in general, total abundance increased, no clear trend was found for 23 species, 14 species decreased, 4 species increased during the early 1990s, and only 13 species showed a general increase through the series. In contrast, series of local environmental conditions (temperature, stratification, nutrients) and climate-related variables (atmospheric pressure indices, upwelling winds) showed a high fraction of their variability in deterministic seasonality and trends. As a result, each species responded independently to environmental and climate variability, measured by generalized additive models. Most species showed a positive relationship with nutrient concentrations but only a few showed a direct relationship with stratification and upwelling. Climate variables had only measurable effects on some species but no common response emerged. Because its adaptation to frequent disturbances, phytoplankton communities in upwelling ecosystems appear less sensitive to changes in regional climate than other communities characterized by short and well defined productive periods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eyring, Veronika; Bony, Sandrine; Meehl, Gerald A.
By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) andmore » CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.« less
NASA Astrophysics Data System (ADS)
Stanier, C. O.; Spak, S.; Neal, T. A.; Herder, S.; Malek, A.; Miller, Z.
2017-12-01
The Iowa Board of Education voted unanimously in 2015 to adopt NGSS performance standards. The CGRER - College of Education Iowa K-12 Climate Science Education Initiative was established in 2016 to work directly with Iowa inservice teachers to provide what teachers need most to teach climate literacy and climate science content through investigational learning aligned with NGSS. Here we present teachers' requests for teaching climate with NGSS, and an approach to provide resources for place-based authentic inquiry on climate, developed, tested, and refined in partnership with inservice and preservice teachers. A survey of inservice middle school and high school science teachers was conducted at the 2016 Iowa Council of Teachers of Mathematics/Iowa Academy of Sciences - Iowa Science Teaching Section Fall Conference and online in fall 2016. Participants (n=383) were asked about their prior experience and education, the resources they use and need, their level of comfort in teaching climate science, perceived barriers, and how they address potential controversy. Teachers indicated preference for professional development on climate content and complete curricula packaged with lessons and interactive models aligned to Iowa standards, as well as training on instructional strategies to enhance students' ability to interpret scientific evidence. We identify trends in responses by teaching experience, climate content knowledge and its source, grade level, and urban and rural districts. Less than 20% of respondents reported controversy or negativity in teaching climate to date, and a majority were comfortable teaching climate science and climate change, with equal confidence in teaching climate and other STEM content through investigational activities. We present an approach and materials to meet these stated needs, created and tested in collaboration with Iowa teachers. We combine professional development and modular curricula with bundled standards, concepts, models, data, field activities, and sequences of individual and group investigational and student-driven inquiry prompts on climate science, climate change, and climate impacts. We identify key resource availability needed to teach place-based climate literacy aligned with NGSS as a standalone curriculum and through local impacts.
The public's belief in climate change and its human cause are increasing over time.
Milfont, Taciano L; Wilson, Marc S; Sibley, Chris G
2017-01-01
Polls examining public opinion on the subject of climate change are now commonplace, and one-off public opinion polls provide a snapshot of citizen's opinions that can inform policy and communication strategies. However, cross-sectional polls do not track opinions over time, thus making it impossible to ascertain whether key climate change beliefs held by the same group of individuals are changing or not. Here we examine the extent to which individual's level of agreement with two key beliefs ("climate change is real" and "climate change is caused by humans") remain stable or increase/decrease over a six-year period in New Zealand using latent growth curve modelling (n = 10,436). Data were drawn from the New Zealand Attitudes and Values Study, a probabilistic national panel study, and indicated that levels of agreement to both beliefs have steadily increased over the 2009-2015 period. Given that climate change beliefs and concerns are key predictors of climate change action, our findings suggest that a combination of targeted endeavors, as well as serendipitous events, may successfully convey the emergency of the issue.
Evolving Views on a Dynamic Greenhouse Earth
NASA Astrophysics Data System (ADS)
Hollis, Chris; Huber, Matthew
2009-06-01
Climatic and Biotic Events of the Paleogene (CBEP 2009) Conference; Wellington, New Zealand, 12-15 January 2009; The Paleogene (65-24 million years ago) was a dynamic period in Earth's history in which major mammal groups became established and diversified, rapid and repeated extreme global warming events occurred, and climate began its stuttering progression from a greenhouse to an icehouse climate state. With atmospheric carbon dioxide concentrations in the range projected to occur over the next several centuries (>1000 parts per million), the Paleogene is also a window into our future (see J. C. Zachos et al., Nature, 451, 279-283, 2008). Long-standing interest in understanding the causes and consequences of global change in the Paleogene and the current timeliness of greenhouse climate research explain why conferences are periodically devoted to the climatic and biotic events of the Paleogene. The 2009 conference, held in New Zealand, attracted 130 participants from 20 countries. Presentations demonstrated substantial progress in new climate proxy development, new multiproxy approaches, and closer integration of paleoclimate records with climate models, consolidating around three main issues.
Baca, María; Läderach, Peter; Haggar, Jeremy; Schroth, Götz; Ovalle, Oriana
2014-01-01
The Mesoamerican region is considered to be one of the areas in the world most vulnerable to climate change. We developed a framework for quantifying the vulnerability of the livelihoods of coffee growers in Mesoamerica at regional and local levels and identify adaptation strategies. Following the Intergovernmental Panel on Climate Change (IPCC) concepts, vulnerability was defined as the combination of exposure, sensitivity and adaptive capacity. To quantify exposure, changes in the climatic suitability for coffee and other crops were predicted through niche modelling based on historical climate data and locations of coffee growing areas from Mexico, Guatemala, El Salvador and Nicaragua. Future climate projections were generated from 19 Global Circulation Models. Focus groups were used to identify nine indicators of sensitivity and eleven indicators of adaptive capacity, which were evaluated through semi-structured interviews with 558 coffee producers. Exposure, sensitivity and adaptive capacity were then condensed into an index of vulnerability, and adaptation strategies were identified in participatory workshops. Models predict that all target countries will experience a decrease in climatic suitability for growing Arabica coffee, with highest suitability loss for El Salvador and lowest loss for Mexico. High vulnerability resulted from loss in climatic suitability for coffee production and high sensitivity through variability of yields and out-migration of the work force. This was combined with low adaptation capacity as evidenced by poor post harvest infrastructure and in some cases poor access to credit and low levels of social organization. Nevertheless, the specific contributors to vulnerability varied strongly among countries, municipalities and families making general trends difficult to identify. Flexible strategies for adaption are therefore needed. Families need the support of government and institutions specialized in impacts of climate change and strengthening of farmer organizations to enable the adjustment of adaptation strategies to local needs and conditions.
NASA Technical Reports Server (NTRS)
Kihara, Job; MacCarthy, Dilys S.; Bationo, Andre; Koala, Saidou; Hickman, Jonathon; Koo, Jawoo; Vanya, Charles; Adiku, Samuel; Beletse, Yacob; Masikate, Patricia;
2012-01-01
Agriculture in Sub-Saharan Africa (SSA) is experiencing climate change-related effects that call for integrated regional assessments, yet capacity for these assessments has been low. The Agricultural Model Intercomparison and Improvement Project (AgMIP) is advancing research on integrated regional assessments of climate change that include climate, crop, and economic modeling and analysis. Through AgMIP, regional integrated assessments are increasingly gaining momentum in SSA, and multi-institutional regional research teams (RRTs) centered in East, West, and Southern· Africa are generating new information on climate change impacts and adaptation in selected agricultural systems. The research in Africa is organized into four RRTs and a coordination team. Each of the RRTs in SSA is composed of scientists from the Consultative Group of International Agricultural Research (CGIAR) institutions, National Agriculture Research institutes (NARs), and universities consisting of experts in crop and economic modeling, climate, and information technology. Stakeholder involvement to inform specific agricultural systems to be evaluated, key outputs, and the representative agricultural pathways (RAPs), is undertaken at two levels: regional and national, in order to contribute to decision making at these levels. Capacity building for integrated assessment (lA) is a key component that is undertaken continuously through interaction with experts in regional and SSA-wide workshops, and through joint creation of tools. Many students and research affiliates have been identified and entrained as part of capacity building in IA. Bi-monthly updates on scholarly publications in climate change in Africa also serve as a vehicle for knowledge-sharing. With 60 scientists already trained and actively engaged in IA and over 80 getting monthly briefs on the latest information on climate change, a climate-informed community of experts is gradually taking shape in SSA. (See Part 2, Appendices 3-5 in this volume for AgMIP Regional Workshop reports.)
Baca, María; Läderach, Peter; Haggar, Jeremy; Schroth, Götz; Ovalle, Oriana
2014-01-01
The Mesoamerican region is considered to be one of the areas in the world most vulnerable to climate change. We developed a framework for quantifying the vulnerability of the livelihoods of coffee growers in Mesoamerica at regional and local levels and identify adaptation strategies. Following the Intergovernmental Panel on Climate Change (IPCC) concepts, vulnerability was defined as the combination of exposure, sensitivity and adaptive capacity. To quantify exposure, changes in the climatic suitability for coffee and other crops were predicted through niche modelling based on historical climate data and locations of coffee growing areas from Mexico, Guatemala, El Salvador and Nicaragua. Future climate projections were generated from 19 Global Circulation Models. Focus groups were used to identify nine indicators of sensitivity and eleven indicators of adaptive capacity, which were evaluated through semi-structured interviews with 558 coffee producers. Exposure, sensitivity and adaptive capacity were then condensed into an index of vulnerability, and adaptation strategies were identified in participatory workshops. Models predict that all target countries will experience a decrease in climatic suitability for growing Arabica coffee, with highest suitability loss for El Salvador and lowest loss for Mexico. High vulnerability resulted from loss in climatic suitability for coffee production and high sensitivity through variability of yields and out-migration of the work force. This was combined with low adaptation capacity as evidenced by poor post harvest infrastructure and in some cases poor access to credit and low levels of social organization. Nevertheless, the specific contributors to vulnerability varied strongly among countries, municipalities and families making general trends difficult to identify. Flexible strategies for adaption are therefore needed. Families need the support of government and institutions specialized in impacts of climate change and strengthening of farmer organizations to enable the adjustment of adaptation strategies to local needs and conditions. PMID:24586328
NASA Astrophysics Data System (ADS)
Cohen, Edward Charles
Design based research was utilized to investigate how students use a greenhouse effect simulation in order to derive best learning practices. During this process, students recognized the authentic scientific process involving computer simulations. The simulation used is embedded within an inquiry-based technology-mediated science curriculum known as Web-based Inquiry Science Environment (WISE). For this research, students from a suburban, diverse, middle school setting use the simulations as part of a two week-long class unit on climate change. A pilot study was conducted during phase one of the research that informed phase two, which encompasses the dissertation. During the pilot study, as students worked through the simulation, evidence of shifts in student motivation, understanding of science content, and ideas about the nature of science became present using a combination of student interviews, focus groups, and students' conversations. Outcomes of the pilot study included improvements to the pedagogical approach. Allowing students to do "Extreme Testing" (e.g., making the world as hot or cold as possible) and increasing the time for free exploration of the simulation are improvements made as a result of the findings of the pilot study. In the dissertation (phase two of the research design) these findings were implemented in a new curriculum scaled for 85 new students from the same school during the next school year. The modifications included new components implementing simulations as an assessment tool for all students and embedded modeling tools. All students were asked to build pre and post models, however due to technological constraints these were not an effective tool. A non-video group of 44 students was established and another group of 41 video students had a WISE curriculum which included twelve minutes of scientists' conversational videos referencing explicit aspects on the nature of science, specifically the use of models and simulations in science. The students in the video group had marked improvement compared to the non-video group on questions regarding modeling as a tool for representing objects and processes of science modeling aspects as evident by multiple data sources. The findings from the dissertation have potential impacts on improving Nature of Science (NOS) concepts around modeling by efficiently embedding short authentic scientific videos that can be easily used by many educators. Compared to published assessments by the American Association for the Advancement of Science (AAAS), due to the curriculum interventions both groups scored higher than the average United States middle school student on many NOS and climate content constructs.
NASA Astrophysics Data System (ADS)
Cohen, E.
2013-12-01
Design based research was utilized to investigate how students use a greenhouse effect simulation in order to derive best learning practices. During this process, students recognized the authentic scientific process involving computer simulations. The simulation used is embedded within an inquiry-based technology-mediated science curriculum known as Web-based Inquiry Science Environment (WISE). For this research, students from a suburban, diverse, middle school setting use the simulations as part of a two week-long class unit on climate change. A pilot study was conducted during phase one of the research that informed phase two, which encompasses the dissertation. During the pilot study, as students worked through the simulation, evidence of shifts in student motivation, understanding of science content, and ideas about the nature of science became present using a combination of student interviews, focus groups, and students' conversations. Outcomes of the pilot study included improvements to the pedagogical approach. Allowing students to do 'Extreme Testing' (e.g., making the world as hot or cold as possible) and increasing the time for free exploration of the simulation are improvements made as a result of the findings of the pilot study. In the dissertation (phase two of the research design) these findings were implemented in a new curriculum scaled for 85 new students from the same school during the next school year. The modifications included new components implementing simulations as an assessment tool for all students and embedded modeling tools. All students were asked to build pre and post models, however due to technological constraints these were not an effective tool. A non-video group of 44 students was established and another group of 41 video students had a WISE curriculum which included twelve minutes of scientists' conversational videos referencing explicit aspects on the nature of science, specifically the use of models and simulations in science. The students in the video group had marked improvement compared to the non-video group on questions regarding modeling as a tool for representing objects and processes of science modeling aspects as evident by multiple data sources. The findings from the dissertation have potential impacts on improving Nature of Science (NOS) concepts around modeling by efficiently embedding short authentic scientific videos that can be easily used by many educators. Compared to published assessments by the American Association for the Advancement of Science (AAAS), due to the curriculum interventions both groups scored higher than the average United States middle school student on many NOS and climate content constructs.
Villeneuve, Isabelle; Lamhamedi, Mohammed S.; Benomar, Lahcen; Rainville, André; DeBlois, Josianne; Beaulieu, Jean; Bousquet, Jean; Lambert, Marie-Claude; Margolis, Hank
2016-01-01
Because of changes in climatic conditions, tree seeds originating from breeding programs may no longer be suited to sites where they are currently sent. As a consequence, new seed zones may have to be delineated. Assisted migration consists of transferring seed sources that match the future climatic conditions to which they are currently adapted. It represents a strategy that could be used to mitigate the potential negative consequences of climate change on forest productivity. Decisions with regard to the choice of the most appropriate seed sources have to rely on appropriate knowledge of morpho-physiological responses of trees. To meet this goal, white spruce (Picea glauca [Moench] Voss) seedlings from eight seed orchards were evaluated during two years in a forest nursery, and at the end of the first growing season on three plantation sites located in different bioclimatic domains in Quebec. The morpho-physiological responses obtained at the end of the second growing season (2+0) in the nursery made it possible to cluster the orchards into three distinct groups. Modeling growth curves of these different groups showed that the height growth of seedlings from the second-generation and southern first-generation seed orchards was significantly higher than that of those from other orchards, by at least 6%. A multiple regression model with three climatic variables (average growing season temperature, average July temperature, length of the growing season) showed that the final height of seedlings (2+0) from the first-generation seed orchards was significantly related to the local climatic conditions at the orchard sites of origin where parental trees from surrounding natural populations were sampled to provide grafts for orchard establishment. Seedling height growth was significantly affected by both seed source origins and planting sites, but the relative ranking of the different seed sources was maintained regardless of reforestation site. This knowledge could be used, in conjunction with transfer models, to refine operational seed transfer rules and select the most suitable sites in an assisted migration strategy. PMID:27746795
Avoiding drift related to linear analysis update with Lagrangian coordinate models
NASA Astrophysics Data System (ADS)
Wang, Yiguo; Counillon, Francois; Bertino, Laurent
2015-04-01
When applying data assimilation to Lagrangian coordinate models, it is profitable to correct its grid (position, volume). In isopycnal ocean coordinate model, such information is provided by the layer thickness that can be massless but must remains positive (truncated Gaussian distribution). A linear gaussian analysis does not ensure positivity for such variable. Existing methods have been proposed to handle this issue - e.g. post processing, anamorphosis or resampling - but none ensures conservation of the mean, which is imperative in climate application. Here, a framework is introduced to test a new method, which proceed as following. First, layers for which analysis yields negative values are iteratively grouped with neighboring layers, resulting in a probability density function with a larger mean and smaller standard deviation that prevent appearance of negative values. Second, analysis increments of the grouped layer are uniformly distributed, which prevent massless layers to become filled and vice-versa. The new method is proved fully conservative with e.g. OI or 3DVAR but a small drift remains with ensemble-based methods (e.g. EnKF, DEnKF, …) during the update of the ensemble anomaly. However, the resulting drift with the latter is small (an order of magnitude smaller than with post-processing) and the increase of the computational cost moderate. The new method is demonstrated with a realistic application in the Norwegian Climate Prediction Model (NorCPM) that provides climate prediction by assimilating sea surface temperature with the Ensemble Kalman Filter in a fully coupled Earth System model (NorESM) with an isopycnal ocean model (MICOM). Over 25-year analysis period, the new method does not impair the predictive skill of the system but corrects the artificial steric drift introduced by data assimilation, and provide estimate in good agreement with IPCC AR5.
Impact of the climate change to shallow groundwater in Baltic artesian basin
NASA Astrophysics Data System (ADS)
Lauva, D.; Bethers, P.; Timuhins, A.; Sennikovs, J.
2012-04-01
The purpose of our work was to find the long term pattern of annual shallow ground water changes in region of Latvia, ground water level modelling for the contemporary climate and future climate scenarios and the model generalization to the Baltic artesian basin (BAB) region. Latvia is located in the middle part of BAB. It occupies about 65'000 square kilometers. BAB territory (480'000 square kilometres) also includes Lithuania, Estonia as well as parts of Poland, Russia, Belarus and the Baltic Sea. Territory of BAB is more than seven times bigger than Latvia. Precipitation and spring snow melt are the main sources of the ground water recharge in BAB territory. The long term pattern of annual shallow ground water changes was extracted from the data of 25 monitoring wells in the territory of Latvia. The main Latvian groundwater level fluctuation regime can be described as a function with two maximums (in spring and late autumn) and two minimums (in winter and late summer). The mathematical model METUL (developed by Latvian University of Agriculture) was chosen for the ground water modelling. It was calibrated on the observations in 25 gauging wells around Latvia. After the calibration we made calculations using data provided by an ensemble of regional climate models, yielding a continuous groundwater table time-series from 1961 to 2100, which were analysed and split into 3 time windows for further analysis: contemporary climate (1961-1990), near future (2021-2050) and far future (2071-2100). The daily average temperature, precipitation and humidity time series were used as METUL forcing parameters. The statistical downscaling method (Sennikovs and Bethers, 2009) was applied for the bias correction of RCM calculated and measured variables. The qualitative differences in future and contemporary annual groundwater regime are expected. The future Latvian annual groundwater cycle according to the RCM climate projection changes to curve with one peak and one drought point. Acknowledgements. This research was supported by the European Social Fund project "Establishment of interdisciplinary scientist group and modelling system for groundwater research" (Project Nr. 2009/0212/1DP/1.1.1.2.0/09/APIA/VIAA/060). Regional climate model data was provided through the ENSEMBLES data archive, funded by the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Reference: Sennikovs, J., Bethers, U. 2009. Statistical downscaling method of regional climate model results for hydrological modelling. In: Proceedings of 18th World IMACS / MODSIM Congress.
Fortini, Lucas B.; Vorsino, Adam E.; Amidon, Fred A.; Paxton, Eben H.; Jacobi, James D.
2015-01-01
Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria's life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations.
Gao, Ran; Chan, Albert P.C.; Utama, Wahyudi P.; Zahoor, Hafiz
2016-01-01
The character of construction projects exposes front-line workers to dangers and accidents. Safety climate has been confirmed to be a predictor of safety performance in the construction industry. This study aims to explore the underlying mechanisms of the relationship between multilevel safety climate and safety performance. An integrated model was developed to study how particular safety climate factors of one level affect those of other levels, and then affect safety performance from the top down. A questionnaire survey was administered on six construction sites in Vietnam. A total of 1030 valid questionnaires were collected from this survey. Approximately half of the data were used to conduct exploratory factor analysis (EFA) and the remaining data were submitted to structural equation modeling (SEM). Top management commitment (TMC) and supervisors’ expectation (SE) were identified as factors to represent organizational safety climate (OSC) and supervisor safety climate (SSC), respectively, and coworkers’ caring and communication (CCC) and coworkers’ role models (CRM) were identified as factors to denote coworker safety climate (CSC). SEM results show that OSC factor is positively related to SSC factor and CSC factors significantly. SSC factor could partially mediate the relationship between OSC factor and CSC factors, as well as the relationship between OSC factor and safety performance. CSC factors partially mediate the relationship between OSC factor and safety performance, and the relationship between SSC factor and safety performance. The findings imply that a positive safety culture should be established both at the organizational level and the group level. Efforts from all top management, supervisors, and coworkers should be provided to improve safety performance in the construction industry. PMID:27834823
Fortini, Lucas B; Vorsino, Adam E; Amidon, Fred A; Paxton, Eben H; Jacobi, James D
2015-01-01
Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria's life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations.
Fortini, Lucas B.; Vorsino, Adam E.; Amidon, Fred A.; Paxton, Eben H.; Jacobi, James D.
2015-01-01
Hawaiian forest birds serve as an ideal group to explore the extent of climate change impacts on at-risk species. Avian malaria constrains many remaining Hawaiian forest bird species to high elevations where temperatures are too cool for malaria’s life cycle and its principal mosquito vector. The impact of climate change on Hawaiian forest birds has been a recent focus of Hawaiian conservation biology, and has centered on the links between climate and avian malaria. To elucidate the differential impacts of projected climate shifts on species with known varying niches, disease resistance and tolerance, we use a comprehensive database of species sightings, regional climate projections and ensemble distribution models to project distribution shifts for all Hawaiian forest bird species. We illustrate that, under a likely scenario of continued disease-driven distribution limitation, all 10 species with highly reliable models (mostly narrow-ranged, single-island endemics) are expected to lose >50% of their range by 2100. Of those, three are expected to lose all range and three others are expected to lose >90% of their range. Projected range loss was smaller for several of the more widespread species; however improved data and models are necessary to refine future projections. Like other at-risk species, Hawaiian forest birds have specific habitat requirements that limit the possibility of range expansion for most species, as projected expansion is frequently in areas where forest habitat is presently not available (such as recent lava flows). Given the large projected range losses for all species, protecting high elevation forest alone is not an adequate long-term strategy for many species under climate change. We describe the types of additional conservation actions practitioners will likely need to consider, while providing results to help with such considerations. PMID:26509270
Gao, Ran; Chan, Albert P C; Utama, Wahyudi P; Zahoor, Hafiz
2016-11-08
The character of construction projects exposes front-line workers to dangers and accidents. Safety climate has been confirmed to be a predictor of safety performance in the construction industry. This study aims to explore the underlying mechanisms of the relationship between multilevel safety climate and safety performance. An integrated model was developed to study how particular safety climate factors of one level affect those of other levels, and then affect safety performance from the top down. A questionnaire survey was administered on six construction sites in Vietnam. A total of 1030 valid questionnaires were collected from this survey. Approximately half of the data were used to conduct exploratory factor analysis (EFA) and the remaining data were submitted to structural equation modeling (SEM). Top management commitment (TMC) and supervisors' expectation (SE) were identified as factors to represent organizational safety climate (OSC) and supervisor safety climate (SSC), respectively, and coworkers' caring and communication (CCC) and coworkers' role models (CRM) were identified as factors to denote coworker safety climate (CSC). SEM results show that OSC factor is positively related to SSC factor and CSC factors significantly. SSC factor could partially mediate the relationship between OSC factor and CSC factors, as well as the relationship between OSC factor and safety performance. CSC factors partially mediate the relationship between OSC factor and safety performance, and the relationship between SSC factor and safety performance. The findings imply that a positive safety culture should be established both at the organizational level and the group level. Efforts from all top management, supervisors, and coworkers should be provided to improve safety performance in the construction industry.
Road building, land use and climate change: prospects for environmental governance in the Amazon.
Perz, Stephen; Brilhante, Silvia; Brown, Foster; Caldas, Marcellus; Ikeda, Santos; Mendoza, Elsa; Overdevest, Christine; Reis, Vera; Reyes, Juan Fernando; Rojas, Daniel; Schmink, Marianne; Souza, Carlos; Walker, Robert
2008-05-27
Some coupled land-climate models predict a dieback of Amazon forest during the twenty-first century due to climate change, but human land use in the region has already reduced the forest cover. The causation behind land use is complex, and includes economic, institutional, political and demographic factors. Pre-eminent among these factors is road building, which facilitates human access to natural resources that beget forest fragmentation. While official government road projects have received considerable attention, unofficial road building by interest groups is expanding more rapidly, especially where official roads are being paved, yielding highly fragmented forest mosaics. Effective governance of natural resources in the Amazon requires a combination of state oversight and community participation in a 'hybrid' model of governance. The MAP Initiative in the southwestern Amazon provides an example of an innovative hybrid approach to environmental governance. It embodies a polycentric structure that includes government agencies, NGOs, universities and communities in a planning process that links scientific data to public deliberations in order to mitigate the effects of new infrastructure and climate change.
NASA Astrophysics Data System (ADS)
Foster, S. Q.; Johnson, R. M.; Carbone, L.; Eastburn, T.; Munoz, R.; Lu, G.; Ammann, C.
2004-05-01
The study of climate and global change is an important on-going focal area for scientists at the National Center for Atmospheric Research (NCAR). Programs overseen by the University Corporation for Atmospheric Research Office of Education and Outreach (UCAR-EO) help to translate NCAR's scientific programs, methodologies, and technologies, and their societal benefits to over 80,000 visitors to the NCAR Mesa Laboratory each year. This is accomplished through the implementation of exhibits, guided tours, an audiotour, programs for school groups, and a teachers' guide to exhibits which is currently in development. The Climate Discovery Exhibit unveiled in July 2003 offers visitors a visually engaging and informative overview of information, graphics, artifacts, and interactives describing the Earth system's dynamic processes that contribute to and mediate climate change, the history of our planet's changing climate, and perspectives on geographic locations and societies around the world that have potential to be impacted by a changing climate. Climate Futures, an addition to this exhibit to open in the summer of 2004, will help visitors to understand why scientists seek to model the global climate system and how information about past and current climate are used to validate models and build scenarios for Earth's future climate, while clarifying the effects of natural and human-induced contributions to these predictions. UCAR-EO further strives to enhance public understanding and to dispel misconceptions about climate change by bringing scientists' explanations to visitors who learn about atmospheric sciences while on staff-guided tours and/or while using an audiotour developed in 2003 with a grant from the National Science Foundation. With advanced reservations, a limited number of visitors may experience demonstrations of climate models in the NCAR Visualization Laboratory. An instructional module for approximately 5,000 visiting school children and a teachers guide for the Climate Discovery Exhibit is in the development and field testing phase with a goal to promote interest in and understanding of how climate change studies align with K-12 science standards. Over the next year, much of the content will become available to national audiences via the new NCAR EO web site (www.ncar.ucar.edu/eo), UCAR-EO's summer teachers workshops, and sessions at the National Science Teacher Association meetings.
NASA Astrophysics Data System (ADS)
Goldman, G. T.; Carlson, C.
2014-12-01
To enact effective policies to address climate change, decision makers need both scientific and political support. One major barrier to U.S. climate policy enactment has been the opposition of private sector actors to proposed policies and to climate science itself. Increasingly, the public and investors are holding companies accountable for their actions around climate change—including political activies, affiliations with trade groups, and involvement with climate science. However, this accountability is inhibited by the prominent role that trade associations have played in climate policy debates in recent years. The opaque nature of such groups is problematic, as it inhibits the public from understanding who is obstructing progress on addressing climate change, and in some cases, impedes the public's climate literacy. Voluntary climate reporting can yield some information on companies' climate engagement and demonstrates the need for greater transparency in corporate political activities around climate change. We analyze CDP climate reporting data from 1,824 companies to assess the degree to which corporate actors disclosed their political influence on climate policies through their trade associations. Results demonstrate the limitations of voluntary reporting and the extent to which companies utilize their trade associations to influence climate change policy debates without being held accountable for these positions. Notably, many companies failed to acknowledge their board seat on trade groups with significant climate policy engagement. Of those that did acknowledge their board membership, some claimed not to agree with their trade associations' positions on climate change. These results raise questions about who trade groups are representing when they challenge the science or obstruct policies to address climate change. Recommendations for overcoming this barrier to informed decision making to address climate change will be discussed.
Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.
2014-01-01
Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.
Evaluating Water Demand Using Agent-Based Modeling
NASA Astrophysics Data System (ADS)
Lowry, T. S.
2004-12-01
The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.
Climate Modeling at the Austrian Weather Service (ZAMG)
NASA Astrophysics Data System (ADS)
Matulla, C.; Anders, I.; Auer, I.
2009-05-01
In later 2007 the Austrian Weather Service (ZAMG) established a group that shall deal with climate change modeling. Two of the group's main goals are to provide climate change scenarios for the assessment of the impact on ecosystems and to reconstruct past climate states along with their change. The former aim is to derive estimates of might happen to our ecosystems under different emission-pathways, whilst the latter goal is to better understand what has caused characteristical changes, which are to be found in proxies. Both aims can be achieved by empirical or dynamical downscaling models, which are ultimately based on the reliability of the driving GCMs results. It is well known that empirical and dynamical downscaling models do have advantages and disadvantages, which are different. As such it appears reasonable to use the approach which is better adapted to the considered question. It may be meaningful to apply empirical downscaling if long periods of time (such as substantial parts of the Holocene) are in the center of attention, whereas dynamical downscaling may be better suited to address questions that are related to decades. Up to now we were more involved with empirical downscaling that helped us to work together with scientists assessing the impact on ecosystems, as for instance, fish in a river (Matulla et al. 2007), forests (Lexer et al. 2002) or phenological phases (Scheifinger et al. 2007). After catching a glimpse of those results, we will turn to dynamical modeling. Here we would like to present findings from case studies, which are related to the more recent past. Our next target is the modelling of possible future climate conditions within the Greater Alpine Region (GAR, see e.g. Auer et al. 2007) as well as some characteristical periods throughout the Holocene as for instance the 8.2k event. This event is to be found in a variety of proxies within and also outside GAR. Auer I., Boehm R., Jurkovic A., Lipa W., Orlik A., Potzmann R., Schoener W., Ungersboeck M., Matulla C., Briffa K., Jones P. D., Efthymiadis D., Brunetti M., Nanni T., Maugeri M., Mercalli L., Mestre O., Moisselin J.-M., Begert M., Müller-Westermeier G., Kveton V., Bochnicek O., Stastny P., Lapin M., Szalai S., Szentimrey T., Cegnar T., Dolinar M., Gajic-Capka M., Zaninovic K., Majstorovic Z., Nieplova E., 2007. HISTALP - Historical instrumental climatological surface time series of the greater Alpine region 1760-2003. International Journal of Climatology, 27, 17-46 Lexer M.J., Hoenninger K., Scheifinger H., Matulla C., Groll N., Kromp-Kolb H., Schaudauer K., Starlinger F., Englisch M. (2002): The sensitivity of Austrian forests to scenarios of climate change: a large-scale risk assessment based on a modified gap model and forest inventory data. Forest Ecology and Management, 162, 53-72 Matulla, C., S. Schmutz, A. Melcher, T. Gerersdorfer and P. Haas, 2007: Climatic Change impact on fish fauna for an Inner-Alpine River based on a transient AOGCM simulation, International Journal of Biometeorology, 52(2), 127-137 Scheifinger H., C. Matulla, P. Cate, A. Kahrer, E. Koch, 2007: Climate impact on plant and insect phenology in Austria (http://epub.oeaw.ac.at/3966-9inhalt).
Cluster-based analysis of multi-model climate ensembles
NASA Astrophysics Data System (ADS)
Hyde, Richard; Hossaini, Ryan; Leeson, Amber A.
2018-06-01
Clustering - the automated grouping of similar data - can provide powerful and unique insight into large and complex data sets, in a fast and computationally efficient manner. While clustering has been used in a variety of fields (from medical image processing to economics), its application within atmospheric science has been fairly limited to date, and the potential benefits of the application of advanced clustering techniques to climate data (both model output and observations) has yet to be fully realised. In this paper, we explore the specific application of clustering to a multi-model climate ensemble. We hypothesise that clustering techniques can provide (a) a flexible, data-driven method of testing model-observation agreement and (b) a mechanism with which to identify model development priorities. We focus our analysis on chemistry-climate model (CCM) output of tropospheric ozone - an important greenhouse gas - from the recent Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Tropospheric column ozone from the ACCMIP ensemble was clustered using the Data Density based Clustering (DDC) algorithm. We find that a multi-model mean (MMM) calculated using members of the most-populous cluster identified at each location offers a reduction of up to ˜ 20 % in the global absolute mean bias between the MMM and an observed satellite-based tropospheric ozone climatology, with respect to a simple, all-model MMM. On a spatial basis, the bias is reduced at ˜ 62 % of all locations, with the largest bias reductions occurring in the Northern Hemisphere - where ozone concentrations are relatively large. However, the bias is unchanged at 9 % of all locations and increases at 29 %, particularly in the Southern Hemisphere. The latter demonstrates that although cluster-based subsampling acts to remove outlier model data, such data may in fact be closer to observed values in some locations. We further demonstrate that clustering can provide a viable and useful framework in which to assess and visualise model spread, offering insight into geographical areas of agreement among models and a measure of diversity across an ensemble. Finally, we discuss caveats of the clustering techniques and note that while we have focused on tropospheric ozone, the principles underlying the cluster-based MMMs are applicable to other prognostic variables from climate models.
Community-based benchmarking of the CMIP DECK experiments
NASA Astrophysics Data System (ADS)
Gleckler, P. J.
2015-12-01
A diversity of community-based efforts are independently developing "diagnostic packages" with little or no coordination between them. A short list of examples include NCAR's Climate Variability Diagnostics Package (CVDP), ORNL's International Land Model Benchmarking (ILAMB), LBNL's Toolkit for Extreme Climate Analysis (TECA), PCMDI's Metrics Package (PMP), the EU EMBRACE ESMValTool, the WGNE MJO diagnostics package, and CFMIP diagnostics. The full value of these efforts cannot be realized without some coordination. As a first step, a WCRP effort has initiated a catalog to document candidate packages that could potentially be applied in a "repeat-use" fashion to all simulations contributed to the CMIP DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. Some coordination of community-based diagnostics has the additional potential to improve how CMIP modeling groups analyze their simulations during model-development. The fact that most modeling groups now maintain a "CMIP compliant" data stream means that in principal without much effort they could readily adopt a set of well organized diagnostic capabilities specifically designed to operate on CMIP DECK experiments. Ultimately, a detailed listing of and access to analysis codes that are demonstrated to work "out of the box" with CMIP data could enable model developers (and others) to select those codes they wish to implement in-house, potentially enabling more systematic evaluation during the model development process.
NASA Astrophysics Data System (ADS)
Choudhary, S.; Nayak, R.; Gore, A.
2013-12-01
There is an overwhelming international scientific consensus on climate change; however, the global community still lacks the resolve to implement meaningful solutions. No meaningful solutions can be found without educating and engaging non-scientific community in addressing the climate change. With more than 41 percent of world's population falling under 10-34 years age group, the future citizens, inspiring them is a great challenge for the climate scientists. In order to educate the youth and students in India, a model program named 'Climeducate' was created with the help of scientists in Indian Polar Research Network (IPRN), trained climate leaders in ';The Climate Reality Project', and a local organization (Planature Consultancy Services). This model was developed keeping in mind the obstacles that may be faced in reaching out to non-specialist audiences in different parts of India. The identified obstacles were 1- making such a presentation that could reveal the truth about the climate crisis in a way that ignites the moral courage in non-specialist audience 2- lack of funding for travel and boarding expenses of a climate communicator, 3- language barrier in educating local audiences, 4- logistical arrangements at the venue. In this presentation we will share how all the four obstacles were overcome. Audiences were also given short questionnaires before and after the presentation. Remarkable changes in the pattern of answers, data would be shared in the presentation, were observed between the two questionnaires. More importantly, a significant difference in audience engagement was observed comparing a presentation that integrated scientific data with audiovisuals prepared by The Climate Reality Project Chairman, Al Gore (also Former US Vice President) and the other using simple PowerPoint slides. With the success of this program which was implemented among 500 audiences in the eastern India, we aim to replicate this program soon in other parts of India. This presentation will outline how scientific story telling through an effective collaboration of network of scientists, climate mentors, school teachers and local organizations would derive significant results in inspiring, engaging and preparing non-specialists audiences to face the realities of climate change.
NASA Astrophysics Data System (ADS)
Addison, J. A.
2015-12-01
The Past Global Changes (PAGES) project of IGBP and Future Earth supports research to understand the Earth's past environment to improve future climate predictions and inform strategies for sustainability. Within this framework, the PAGES 2k Network was established to provide a focus on the past 2000 years, a period that encompasses Medieval Climate Anomaly warming, Little Ice Age cooling, and recent anthropogenically-forced climate change. The results of these studies are used for testing earth system models, and for understanding decadal- to centennial-scale variability, which is needed for long-term planning. International coordination and cooperation among the nine regional Working Groups that make up the 2k Network has been critical to the success of PAGES 2k. The collaborative approach is moving toward scientific achievements across the regional groups, including: (i) the development of a community-driven open-access proxy climate database; (ii) integration of multi-resolution proxy records; (iii) development of multivariate climate reconstructions; and (iv) a leap forward in the spatial resolution of paleoclimate reconstructions. The last addition to the 2k Network, the Ocean2k Working Group has further innovated the collaborative approach by: (1) creating an open, receptive environment to discuss ideas exclusively in the virtual space; (2) employing an array of real-time collaborative software tools to enable communication, group document writing, and data analysis; (3) consolidating executive leadership teams to oversee project development and manage grassroots-style volunteer pools; and (4) embracing the value-added role that international and interdisciplinary science can play in advancing paleoclimate hypotheses critical to understanding future change. Ongoing efforts for the PAGES 2k Network are focused on developing new standards for data quality control and archiving. These tasks will provide the foundation for new and continuing "trans-regional" 2k projects which address paleoclimate science that transcend regional boundaries. The PAGES 2k Network encourages participation by all investigators interested in this community-wide project.
A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers.
Varela, Sara; Lima-Ribeiro, Matheus S; Terribile, Levi Carina
2015-01-01
Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12-BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/.
A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers
Varela, Sara; Lima-Ribeiro, Matheus S.; Terribile, Levi Carina
2015-01-01
Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/. PMID:26068930
Impacts of weighting climate models for hydro-meteorological climate change studies
NASA Astrophysics Data System (ADS)
Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel
2017-06-01
Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.
Managing Climate Change Refugia for Biodiversity ...
Climate change threatens to create fundamental shifts in in the distributions and abundances of species. Given projected losses, increased emphasis on management for ecosystem resilience to help buffer fish and wildlife populations against climate change is emerging. Such efforts stake a claim for an adaptive, anticipatory planning response to the climate change threat. To be effective, approaches will need to address critical uncertainties in both the physical basis for projected landscape changes, as well as the biological responses of organisms. Recent efforts define future potential climate refugia based on air temperatures and associated microclimatic changes. These efforts reflect the relatively strong conceptual foundation for linkages between regional climate change and local responses and thermal dynamics. Yet important questions remain. Drawing on case studies, we illustrate some key uncertainties in the responses of species and their habitats to altered hydro-climatic regimes currently not well addressed by physical or ecological models. These uncertainties need not delay anticipatory planning, but rather highlight the need for identification and communication of actions with high probabilities of success, and targeted research within an adaptive management framework.In this workshop, we will showcase the latest science on climate refugia and participants will interact through small group discussions, relevant examples, and facilitated dialogue to i
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man
2015-01-01
Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.
NASA Astrophysics Data System (ADS)
Tumber-Davila, S. J.; Schenk, H. J.; Jackson, R. B.
2017-12-01
This synthesis examines plant rooting distributions globally, by doubling the number of entries in the Root Systems of Individual Plants database (RSIP) created by Schenk and Jackson. Root systems influence many processes, including water and nutrient uptake and soil carbon storage. Root systems also mediate vegetation responses to changing climatic and environmental conditions. Therefore, a collective understanding of the importance of rooting systems to carbon sequestration, soil characteristics, hydrology, and climate, is needed. Current global models are limited by a poor understanding of the mechanisms affecting rooting, carbon stocks, and belowground biomass. This improved database contains an extensive bank of records describing the rooting system of individual plants, as well as detailed information on the climate and environment from which the observations are made. The expanded RSIP database will: 1) increase our understanding of rooting depths, lateral root spreads and above and belowground allometry; 2) improve the representation of plant rooting systems in Earth System Models; 3) enable studies of how climate change will alter and interact with plant species and functional groups in the future. We further focus on how plant rooting behavior responds to variations in climate and the environment, and create a model that can predict rooting behavior given a set of environmental conditions. Preliminary results suggest that high potential evapotranspiration and seasonality of precipitation are indicative of deeper rooting after accounting for plant growth form. When mapping predicted deep rooting by climate, we predict deepest rooting to occur in equatorial South America, Africa, and central India.
Nurse executive transformational leadership found in participative organizations.
Dunham-Taylor, J
2000-05-01
The study examined a national sample of 396 randomly selected hospital nurse executives to explore transformational leadership, stage of power, and organizational climate. Results from a few nurse executive studies have found nurse executives were transformational leaders. As executives were more transformational, they achieved better staff satisfaction and higher work group effectiveness. This study integrates Bass' transformational leadership model with Hagberg's power stage theory and Likert's organizational climate theory. Nurse executives (396) and staff reporting to them (1,115) rated the nurse executives' leadership style, staff extra effort, staff satisfaction, and work group effectiveness using Bass and Avolio's Multifactor Leadership Questionnaire. Executives' bosses (360) rated executive work group effectiveness. Executives completed Hagberg's Personal Power Profile and ranked their organizational climate using Likert's Profile of Organizational Characteristics. Nurse executives used transformational leadership fairly often; achieved fairly satisfied staff levels; were very effective according to bosses; were most likely at stage 3 (power by achievement) or stage 4 (power by reflection); and rated their hospital as a Likert System 3 Consultative Organization. Staff satisfaction and work group effectiveness decreased as nurse executives were more transactional. Higher transformational scores tended to occur with higher educational degrees and within more participative organizations. Transformational qualities can be enhanced by further education, by achieving higher power stages, and by being within more participative organizations.
NASA Astrophysics Data System (ADS)
Burkhart, J. F.; Tallaksen, L. M.; Stordal, F.; Berntsen, T.; Westermann, S.; Kristjansson, J. E.; Etzelmuller, B.; Hagen, J. O.; Schuler, T.; Hamran, S. E.; Lande, T. S.; Bryn, A.
2015-12-01
Climate change is impacting the high latitudes more rapidly and significantly than any other region of the Earth because of feedback processes between the atmosphere and the underlying surface. A warmer climate has already led to thawing of permafrost, reducing snow cover and a longer growing season; changes, which in turn influence the atmospheric circulation and the hydrological cycle. Still, many studies rely on one-way coupling between the atmosphere and the land surface, thereby neglecting important interactions and feedbacks. The observation, understanding and prediction of such processes from local to regional and global scales, represent a major scientific challenge that requires multidisciplinary scientific effort. The successful integration of earth observations (remote and in-situ data) and model development requires a harmonized research effort between earth system scientists, modelers and the developers of technologies and sensors. LATICE, which is recognized as a priority research area by the Faculty of Mathematics and Natural Sciences at the University of Oslo, aims to advance the knowledge base concerning land atmosphere interactions and their role in controlling climate variability and climate change at high northern latitudes. The consortium consists of an interdisciplinary team of experts from the atmospheric and terrestrial (hydrosphere, cryosphere and biosphere) research groups, together with key expertise on earth observations and novel sensor technologies. LATICE addresses critical knowledge gaps in the current climate assessment capacity through: Improving parameterizations of processes in earth system models controlling the interactions and feedbacks between the land (snow, ice, permafrost, soil and vegetation) and the atmosphere at high latitudes, including the boreal, alpine and artic zone. Assessing the influence of climate and land cover changes on water and energy fluxes. Integrating remote earth observations with in-situ data and suitable models to allow studies of finer-scale processes governing land-atmosphere interactions. Addressing observational challenges through the development of novel observational products and networks.
Mitigation potential and global health impacts from emissions pricing of food commodities
NASA Astrophysics Data System (ADS)
Springmann, Marco; Mason-D'Croz, Daniel; Robinson, Sherman; Wiebe, Keith; Godfray, H. Charles J.; Rayner, Mike; Scarborough, Peter
2017-01-01
The projected rise in food-related greenhouse gas emissions could seriously impede efforts to limit global warming to acceptable levels. Despite that, food production and consumption have long been excluded from climate policies, in part due to concerns about the potential impact on food security. Using a coupled agriculture and health modelling framework, we show that the global climate change mitigation potential of emissions pricing of food commodities could be substantial, and that levying greenhouse gas taxes on food commodities could, if appropriately designed, be a health-promoting climate policy in high-income countries, as well as in most low- and middle-income countries. Sparing food groups known to be beneficial for health from taxation, selectively compensating for income losses associated with tax-related price increases, and using a portion of tax revenues for health promotion are potential policy options that could help avert most of the negative health impacts experienced by vulnerable groups, whilst still promoting changes towards diets which are more environmentally sustainable.
Scenarios Based on Shared Socioeconomic Pathway Assumptions
NASA Astrophysics Data System (ADS)
Edmonds, J.
2013-12-01
A set of new scenarios is being developed by the international scientific community as part of a larger program that was articulated in Moss, et al. (2009), published in Nature. A long series of meetings including climate researchers drawn from the climate modeling, impacts, adaptation and vulnerability (IAV) and integrated assessment modeling (IAM) communities have led to the development of a set of five Shared Socioeconomic Pathways (SSPs), which define the state of human and natural societies at a macro scale over the course of the 21st century without regard to climate mitigation or change. SSPs were designed to explore a range of possible futures consistent with greater or lesser challenges to mitigation and challenges to adaptation. They include a narrative storyline and a set of quantified measures--e.g. demographic and economic profiles--that define the high-level state of society as it evolves over the 21st century under the assumption of no significant climate feedback. SSPs can be used to develop quantitative scenarios of human Earth systems using IAMs. IAMs produce information about greenhouse gas emissions, energy systems, the economy, agriculture and land use. Each set of SSPs will have a different human Earth system realization for each IAM. Five groups from the IAM community have begun to explore the implications of SSP assumptions for emissions, energy, economy, agriculture and land use. We report the quantitative results of initial experiments from those groups. A major goal of the Moss, et al. strategy was to enable the use of CMIP5 climate model ensemble products for IAV research. CMIP5 climate scenarios used four Representative Concentration Pathway (RCP) scenarios, defined in terms of radiative forcing in the year 2100: 2.6, 4.5, 6.0, and 8.5 Wm-2. There is no reason to believe that the SSPs will generate year 2100 levels of radiative forcing that correspond to the four RCP levels, though it is important that at least one SSP produce a scenario with at least 8.5 Wm-2. To address this problem each SSP scenario can be treated as a reference scenario, to which emissions mitigation policies can be applied to create a set of RCP replications. These RCP replications have the underlying SSP socio-economic assumptions in addition to policy assumptions and radiative forcing levels consistent with the CMIP5 products. We report quantitative results of initial experiments from the five participating groups.
Buotte, Polly C; Peterson, David L; McKelvey, Kevin S; Hicke, Jeffrey A
2016-03-15
Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability assessment conducted by the US Forest Service. During this assessment, five subregional workshops were held to capture variability in vulnerability and to develop adaptation tactics. At each workshop, participants answered a questionnaire to: 1) identify species, resources, or other information missing from the regional assessment, and 2) describe subregional vulnerability to climate change. Workshop participants divided into six resource groups; here we focus on wildlife resources. Participants identified information missing from the regional assessment and multiple instances of subregional variability in climate change vulnerability. We provide recommendations for improving the process of capturing subregional variability in a regional vulnerability assessment. We propose a revised conceptual framework structured around pathways of climate influence, each with separate rankings for exposure, sensitivity, and adaptive capacity. These revisions allow for a quantitative ranking of species, pathways, exposure, sensitivity, and adaptive capacity across subregions. Rankings can be used to direct the development and implementation of future regional research and monitoring programs. The revised conceptual framework is equally applicable as a stand-alone model for assessing climate change vulnerability and as a nested model within a regional assessment for capturing subregional variability in vulnerability. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Su, Y.; Liu, L.; Fang, X. Q.; Ma, Y. N.
2015-07-01
In ancient China, the change in regional agriculture and animal husbandry productivity caused by climate change led to either wars or peaceful relations between nomadic and farming groups. From the Western Han Dynasty to the Tang Dynasty there were 367 wars between the two groups. The nomadic people initiated 69 % of the wars, but 62.4 % were won by the farmers. On a 30 year-period timescale, warm climates corresponded to a high incidence of wars. The conflicts between the nomadic and farming groups took place in some areas which are sensitive to climate change. During the cold periods, the battlefields were mostly in the southern regions. The main causes which leading to the above results are following: (1) warm climate provided a solid material foundation for nomadic and farming groups, especially contributed to improve the productivity of nomadic group; meanwhile, the excessive desire for essential means of subsistence in nomadic group could led to wars. (2) During the cold periods, people of farming group moved to the south and construct the south, meanwhile, nomadic group occupied the central plains, thus the battlefields also changed. As the background, climate change plays an indirect role in wars between groups.
Examining Treatment Climate Across Prison-Based Substance Abuse Treatment Groups.
Kelly, Christopher E; Welsh, Wayne N
2016-06-06
With notable exceptions, few studies have looked critically at the role and effects of factors other than individual or programmatic differences that contribute to the climate within substance abuse treatment programs. De Leon's work on the therapeutic community, however, indicates that factors beyond the individual and program can contribute to the overall functioning of similarly situated communities. In this study, we introduce and examine the concept of the "treatment group," the level of aggregation between the individual who participates in treatment and the organization that provides it. The treatment group refers to the social context and dynamics that operate among treatment participants, and we sought to study differences in treatment climate across 12 prison-based treatment groups within a single prison. Using data from 604 participants who were assigned at random to one of the 12 groups, we analyzed differences on seven treatment climate indicators from one month and six months into the program across the treatment groups. No differences were found among the treatment groups at after one month; however, after 6 months, significant differences emerged across the groups on three treatment climate variables: program structure, counselor rapport, and counselor competence. This study is among the first of its kind to conceptualize and examine treatment climate across otherwise similar groups and find that differences emerge on several indicators of climate. As such, we argue that the treatment group may be important to consider in both the delivery and evaluation of substance abuse treatment.
Charter for the ARM Atmospheric Modeling Advisory Group
DOE Office of Scientific and Technical Information (OSTI.GOV)
Advisory Group, ARM Atmospheric Modeling
The Atmospheric Modeling Advisory Group of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility is guided by the following: 1. The group will provide feedback on the overall project plan including input on how to address priorities and trade-offs in the modeling and analysis workflow, making sure the modeling follows general best practices, and reviewing the recommendations provided to ARM for the workflow implementation. 2. The group will consist of approximately 6 members plus the PI and co-PI of the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) pilot project. The ARM Technical Director,more » or his designee, serves as an ex-officio member. This size is chosen based on the ability to efficiently conduct teleconferences and to span the general needs for input to the LASSO pilot project.« less
NASA Astrophysics Data System (ADS)
Gyakum, J. R.; Austin, B. N.; Curtis, D. C.; Anderson, M.; Alpert, H.; Young, S.; Herson, A.; Schwarz, A.; Kavvas, M. L.; Langridge, R.; Lynn, E.; Anderson, J.; Redmond, K. T.; Dettinger, M. D.; Correa, M.; Franco, G.; Cayan, D.; Georgakakos, K.
2015-12-01
Diverse areas of expertise are needed to describe and assess a changing climate and provide guidance for the agency that runs the largest state-built, multi-purpose water project in the U.S. California's State Water Project provides: drinking water for more than 25 million people, flood control, power generation, recreation, fish and wildlife protection, and water quality improvements. Hydrologic impacts under a changing climate include rising seas, reduced ratio of snow to rain, earlier snowmelt and higher temperatures; all of which are being detected. To improve the scientific basis for decisions and enhance the consistency of climate change approaches, the California Department of Water Resources (DWR) empaneled a Climate Change Technical Advisory Group (CCTAG) for guidance on the scientific aspects of climate change, its impacts on water resources, the use and creation of planning approaches and analytical tools, and the development of adaptation responses. To carry out DWR's mission, incorporation of climate change into DWR's planning, projects, and other activities must be consistent, science-based, and continually improved through an iterative process. Hydrologists, academicians, modelers, planners, lawyers and practitioners convened regularly to tackle these complicated issues in water management policy, including climate change impacts on extreme events. Actions taken in response to the CCTAG recommendations will move California toward more sustainable management of water and related resources. DWR will release a technical report of CCTAG guidance and perspectives in 2015. The process to convene, collaborate and distribute the findings of this CCTAG will be the focus of this presentation. An academician and water resources practitioner will share their perspectives on the processes driving CCTAG's work.
The Monash University Interactive Simple Climate Model
NASA Astrophysics Data System (ADS)
Dommenget, D.
2013-12-01
The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.
NASA Technical Reports Server (NTRS)
Roberts, J. Brent; Robertson, Franklin R.; Funk, Chris
2014-01-01
Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.
NASA Astrophysics Data System (ADS)
Trtanj, J.; Balbus, J. M.; Brown, C.; Shimamoto, M. M.
2017-12-01
The transmission and spread of infectious diseases, especially vector-borne diseases, water-borne diseases and zoonosis, are influenced by short and long-term climate factors, in conjunction with numerous other drivers. Public health interventions, including vaccination, vector control programs, and outreach campaigns could be made more effective if the geographic range and timing of increased disease risk could be more accurately targeted, and high risk areas and populations identified. While some progress has been made in predictive modeling for transmission of these diseases using climate and weather data as inputs, they often still start after the first case appears, the skill of those models remains limited, and their use by public health officials infrequent. And further, predictions with lead times of weeks, months or seasons are even rarer, yet the value of acting early holds the potential to save more lives, reduce cost and enhance both economic and national security. Information on high-risk populations and areas for infectious diseases is also potentially useful for the federal defense and intelligence communities as well. The US Global Change Research Program, through its Interagency Group on Climate Change and Human Health (CCHHG), has put together a science plan that pulls together federal scientists and programs working on predictive modeling of climate-sensitive diseases, and draws on academic and other partners. Through a series of webinars and an in-person workshop, the CCHHG has convened key federal and academic stakeholders to assess the current state of science and develop an integrated science plan to identify data and observation systems needs as well as a targeted research agenda for enhancing predictive modeling. This presentation will summarize the findings from this effort and engage AGU members on plans and next steps to improve predictive modeling for infectious diseases.
Pinkernell, Stefan; Beszteri, Bánk
2014-08-01
Fragilariopsis kerguelensis, a dominant diatom species throughout the Antarctic Circumpolar Current, is coined to be one of the main drivers of the biological silicate pump. Here, we study the distribution of this important species and expected consequences of climate change upon it, using correlative species distribution modeling and publicly available presence-only data. As experience with SDM is scarce for marine phytoplankton, this also serves as a pilot study for this organism group. We used the maximum entropy method to calculate distribution models for the diatom F. kerguelensis based on yearly and monthly environmental data (sea surface temperature, salinity, nitrate and silicate concentrations). Observation data were harvested from GBIF and the Global Diatom Database, and for further analyses also from the Hustedt Diatom Collection (BRM). The models were projected on current yearly and seasonal environmental data to study current distribution and its seasonality. Furthermore, we projected the seasonal model on future environmental data obtained from climate models for the year 2100. Projected on current yearly averaged environmental data, all models showed similar distribution patterns for F. kerguelensis. The monthly model showed seasonality, for example, a shift of the southern distribution boundary toward the north in the winter. Projections on future scenarios resulted in a moderately to negligibly shrinking distribution area and a change in seasonality. We found a substantial bias in the publicly available observation datasets, which could be reduced by additional observation records we obtained from the Hustedt Diatom Collection. Present-day distribution patterns inferred from the models coincided well with background knowledge and previous reports about F. kerguelensis distribution, showing that maximum entropy-based distribution models are suitable to map distribution patterns for oceanic planktonic organisms. Our scenario projections indicate moderate effects of climate change upon the biogeography of F. kerguelensis.
Modeling soil temperature change in Seward Peninsula, Alaska
NASA Astrophysics Data System (ADS)
Debolskiy, M. V.; Nicolsky, D.; Romanovsky, V. E.; Muskett, R. R.; Panda, S. K.
2017-12-01
Increasing demand for assessment of climate change-induced permafrost degradation and its consequences promotes creation of high-resolution modeling products of soil temperature changes. This is especially relevant for areas with highly vulnerable warm discontinuous permafrost in the Western Alaska. In this study, we apply ecotype-based modeling approach to simulate high-resolution permafrost distribution and its temporal dynamics in Seward Peninsula, Alaska. To model soil temperature dynamics, we use a transient soil heat transfer model developed at the Geophysical Institute Permafrost Laboratory (GIPL-2). The model solves one dimensional nonlinear heat equation with phase change. The developed model is forced with combination of historical climate and different future scenarios for 1900-2100 with 2x2 km resolution prepared by Scenarios Network for Alaska and Arctic Planning (2017). Vegetation, snow and soil properties are calibrated by ecotype and up-scaled by using Alaska Existing Vegetation Type map for Western Alaska (Flemming, 2015) with 30x30 m resolution provided by Geographic Information Network of Alaska (UAF). The calibrated ecotypes cover over 75% of the study area. We calibrate the model using a data assimilation technique utilizing available observations of air, surface and sub-surface temperatures and snow cover collected by various agencies and research groups (USGS, Geophysical Institute, USDA). The calibration approach takes into account a natural variability between stations in the same ecotype and finds an optimal set of model parameters (snow and soil properties) within the study area. This approach allows reduction in microscale heterogeneity and aggregated soil temperature data from shallow boreholes which is highly dependent on local conditions. As a result of this study we present a series of preliminary high resolution maps for the Seward Peninsula showing changes in the active layer depth and ground temperatures for the current climate and future climate change scenarios.
A coupled human-natural systems analysis of irrigated agriculture under changing climate
NASA Astrophysics Data System (ADS)
Giuliani, M.; Li, Y.; Castelletti, A.; Gandolfi, C.
2016-09-01
Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta-models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human-natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe.
From Dynamic Global Vegetation Modelling to Real-World regional and local Application
NASA Astrophysics Data System (ADS)
Steinkamp, J.; Forrest, M.; Kamm, K.; Leiblein-Wild, M.; Pachzelt, A.; Werner, C.; Hickler, T.
2015-12-01
Dynamic (global) vegetation models (DGVM) can be applied to any spatial resolution on the local, national, continental and global scale given suitable climatic and geographic input forcing data. LPJ-GUESS, the main DGVM applied in our research group, uses the plant functional type (PFT) concept in the global setup with typically about 10-20 tree PFTs (subdivided into tropical, temperate and boreal) and two herbaceous PFTs by default. When modelling smaller spatial extents, such as continental (e.g. Europe/North America) national domains, or individual sites (e.g. Frankfurt, Germany), i.e. the scale of decision making, it becomes necessary to refine the PFT representation, the model initialization and validation and, in some case, to include additional processes. I will present examples of LPJ-GUESS applications at the continental to local scale performed by our working group including i.) a European simulation representing the main tree species and Mediterranean shrubs, ii.) a climate impact study for Turkey, iii.) coupled dynamic large grazer-vegetation modelling across Africa and, iv.) modelling an allergenic and in Europe invasive shrub (Ambrosia artemisiifolia), iv.) simulating water usage by an oak-pine forest stand near Frankfurt, and v.) stand specific differences in modelling at the FACE sites. Finally, I will present some thoughts on how to advance the models in terms of more detailed and realistic PFT or species parameterizations accounting for adaptive functional trait responses also within species.
NASA Astrophysics Data System (ADS)
Mani, N. J.; Waliser, D. E.; Jiang, X.
2014-12-01
While the boreal summer monsoon intraseasonal variability (BSISV) exerts profound influence on the south Asian monsoon, the capability of present day dynamical models in simulating and predicting the BSISV is still limited. The global model evaluation project on vertical structure and diabatic processes of the Madden Julian Oscillations (MJO) is a joint venture, coordinated by the Working Group on Numerical Experimentation (WGNE) MJO Task Force and GEWEX Atmospheric System Study (GASS) program, for assessing the model deficiencies in simulating the ISV and for improving our understanding of the underlying processes. In this study the simulation of the northward propagating BSISV is investigated in 26 climate models with special focus on the vertical diabatic heating structure and clouds. Following parallel lines of inquiry as the MJO Task Force has done with the eastward propagating MJO, we utilize previously proposed and newly developed model performance metrics and process diagnostics and apply them to the global climate model simulations of BSISV.
Modeling the impact of climate warming on the range of brook trout in the Blue Ridge Mountains, USA
NASA Astrophysics Data System (ADS)
Bartlett, M. G.
2012-12-01
Brook trout in the Eastern United States (Salvelinus fontinalis) thrive in a relatively narrow range of stream temperatures. Over the past several centuries, the introduction of competitive species has pushed brook trout to the cooler, upstream margins of what use to be a much more extensive range within most drainages. Over the next several decades, climate change may put further thermal pressure on the species, increasing the fragmentation of their distribution and shrinking their present range. Because the size and connectivity of habitats seem to influence the persistence of local populations, climate warming leading to increased fragmentation of remaining habitats could accelerated species decline. Using the Regional Hydrological and Ecological Simulation System (RHYSSys), I modeled the projected habitat changes for a group of native brook trout streams in the Blue Ridge Mountains of South-Central Virginia, USA. The modeling process is illustrative of the need for better understanding of the couplings that exist between geomorphology, hydrology, and ecology, particularly in mountain environments. Model results are quantified according to the degree of decrease in stream-miles of habitat and the increase in the fragmentation of the habitat as a function of the warming rate (degrees per decade). These results may help inform habitat management strategies for the coming several decades in the region, and the modeling process helps highlight the need for more refined understanding of climate change's impacts on habitability.
Descriptive modelling to predict deoxynivalenol in winter wheat in the Netherlands.
Van Der Fels-Klerx, H J; Burgers, S L G E; Booij, C J H
2010-05-01
Predictions of deoxynivalenol (DON) content in wheat at harvest can be useful for decision-making by stakeholders of the wheat feed and food supply chain. The objective of the current research was to develop quantitative predictive models for DON in mature winter wheat in the Netherlands for two specific groups of end-users. One model was developed for use by farmers in underpinning Fusarium spp. disease management, specifically the application of fungicides around wheat flowering (model A). The second model was developed for industry and food safety authorities, and considered the entire wheat cultivation period (model B). Model development was based on observational data collected from 425 fields throughout the Netherlands between 2001 and 2008. For each field, agronomical information, climatic data and DON levels in mature wheat were collected. Using multiple regression analyses, the set of biological relevant variables that provided the highest statistical performance was selected. The two final models include the following variables: region, wheat resistance level, spraying, flowering date, several climatic variables in the different stages of wheat growing, and length of the period between flowering and harvesting (model B only). The percentages of variance accounted for were 64.4% and 65.6% for models A and B, respectively. Model validation showed high correlation between the predicted and observed DON levels. The two models may be applied by various groups of end-users to reduce DON contamination in wheat-derived feed and food products and, ultimately, reduce animal and consumer health risks.
Harmonisation of Global Land-Use Scenarios for the Period 1500-2100 for IPCC-AR5
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hurtt, George; Chini, Louise Parsons; Frolking, Steve
2009-06-01
In preparation for the fifth Intergovernmental Panel on Climate Change climate change assessment (IPCC-AR5), the international community is developing new advanced computer models (CMs) to address the combined effects of human activities (e.g. land-use and fossil fuel emissions) on the carbon-climate system. In addition, four Representative Concentration Pathway (RCP) scenarios of the future (2005-2100) are being developed by four Integrated Assessment Modeling teams (IAMs) to be used as input to the CMs for future climate projections. The diversity of requirements and approaches among CMs and IAMs for tracking land-use changes (past, present, and future), presents major challenges for treating land-usemore » comprehensively and consistently between these communities. As part of an international working group, we have been working to meet these challenges by developing a "harmonized" set of land-use change scenarios that smoothly connects gridded historical reconstructions of land-use with future projections, in a format required by CMs. This approach to harmonizing the treatment of land-use between two key modeling communities, CMs and IAMs, represents a major advance that will facilitate more consistent and fuller treatments of land-use/land-use change effects including both CO2 emissions and corresponding land-surface changes.« less
Carroll, Carlos; Roberts, David R; Michalak, Julia L; Lawler, Joshua J; Nielsen, Scott E; Stralberg, Diana; Hamann, Andreas; Mcrae, Brad H; Wang, Tongli
2017-11-01
As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Aranda, Silvia C.; Gabriel, Rosalina; Borges, Paulo A. V.; Santos, Ana M. C.; de Azevedo, Eduardo Brito; Patiño, Jairo; Hortal, Joaquín; Lobo, Jorge M.
2014-01-01
Species richness on oceanic islands has been related to a series of ecological factors including island size and isolation (i.e. the Equilibrium Model of Island Biogeography, EMIB), habitat diversity, climate (i.e., temperature and precipitation) and more recently island ontogeny (i.e. the General Dynamic Model of oceanic island biogeography, GDM). Here we evaluate the relationship of these factors with the diversity of bryophytes in the Macaronesian region (Azores, Madeira, Canary Islands and Cape Verde). The predictive power of EMIB, habitat diversity, climate and the GDM on total bryophyte richness, as well as moss and liverwort richness (the two dominant bryophyte groups), was evaluated through ordinary least squares regressions. After choosing the best subset of variables using inference statistics, we used partial regression analyses to identify the independent and shared effects of each model. The variables included within each model were similar for mosses and liverworts, with orographic mist layer being one of the most important predictors of richness. Models combining climate with either the GDM or habitat diversity explained most of richness variation (up to 91%). There was a high portion of shared variance between all pairwise combinations of factors in mosses, while in liverworts around half of the variability in species richness was accounted for exclusively by climate. Our results suggest that the effects of climate and habitat are strong and prevalent in this region, while geographical factors have limited influence on Macaronesian bryophyte diversity. Although climate is of great importance for liverwort richness, in mosses its effect is similar to or, at least, indiscernible from the effect of habitat diversity and, strikingly, the effect of island ontogeny. These results indicate that for highly vagile taxa on oceanic islands, the dispersal process may be less important for successful colonization than the availability of suitable ecological conditions during the establishment phase. PMID:25003186
Quantifying the effect of varying GHG's concentration in Regional Climate Models
NASA Astrophysics Data System (ADS)
López-Romero, Jose Maria; Jerez, Sonia; Palacios-Peña, Laura; José Gómez-Navarro, Juan; Jiménez-Guerrero, Pedro; Montavez, Juan Pedro
2017-04-01
Regional Climate Models (RCMs) are driven at the boundaries by Global Circulation Models (GCM), and in the particular case of Climate Change projections, such simulations are forced by varying greenhouse gases (GHGs) concentrations. In hindcast simulations driven by reanalysis products, the climate change signal is usually introduced in the assimilation process as well. An interesting question arising in this context is whether GHGs concentrations have to be varied within the RCMs model itself, or rather they should be kept constant. Some groups keep the GHGs concentrations constant under the assumption that information about climate change signal is given throughout the boundaries; sometimes certain radiation parameterization schemes do not permit such changes. Other approaches vary these concentrations arguing that this preserves the physical coherence respect to the driving conditions for the RCM. This work aims to shed light on this topic. For this task, various regional climate simulations with the WRF model for the 1954-2004 period have been carried out for using a Euro-CORDEX compliant domain. A series of simulations with constant and variable GHGs have been performed using both, a GCM (ECHAM6-OM) and a reanalysis product (ERA-20C) data. Results indicate that there exist noticeable differences when introducing varying GHGs concentrations within the RCM domain. The differences in 2-m temperature series between the experiments with varying or constant GHGs concentration strongly depend on the atmospheric conditions, appearing a strong interannual variability. This suggests that short-term experiments are not recommended if the aim is to assess the role of varying GHGs. In addition, and consistently in both GCM and reanalysis-driven experiments, the magnitude of temperature trends, as well as the spatial pattern represented by varying GHGs experiment, are closer to the driving dataset than in experiments keeping constant the GHGs concentration. These results point towards the need for the inclusion of varying GHGs concentration within the RCM itself when dynamically downscaling global datasets, both in GCM and hindcast simulations.
1997-11-08
Most public-health assessments of climate-control policies have focused on long-term impacts of global change. Our interdisciplinary working group assesses likely short-term impacts on public health. We combined models of energy consumption, carbon emissions, and associated atmospheric particulate-matter (PM) concentration under two different forecasts: business-as-usual (BAU); and a hypothetical climate-policy scenario, where developed and developing countries undertake significant reductions in carbon emissions. We predict that by 2020, 700,000 avoidable deaths (90% CI 385,000-1,034,000) will occur annually as a result of additional PM exposure under the BAU forecasts when compared with the climate-policy scenario. From 2000 to 2020, the cumulative impact on public health related to the difference in PM exposure could total 8 million deaths globally (90% CI 4.4-11.9 million). In the USA alone, the avoidable number of annual deaths from PM exposure in 2020 (without climate-change-control policy) would equal in magnitude deaths associated with human immunodeficiency diseases or all liver diseases in 1995. The mortality estimates are indicative of the magnitude of the likely health benefits of the climate-policy scenario examined and are not precise predictions of avoidable deaths. While characterized by considerable uncertainty, the short-term public-health impacts of reduced PM exposures associated with greenhouse-gas reductions are likely to be substantial even under the most conservative set of assumptions.
NASA Astrophysics Data System (ADS)
Gariano, Stefano Luigi; Guzzetti, Fausto
2017-04-01
According to the fifth report of the Intergovernmental Panel on Climate Change, "warming of the climate system is unequivocal". The influence of climate changes on slope stability and landslides is also undisputable. Nevertheless, the quantitative evaluation of the impact of global warming, and the related changes in climate, on landslides remains a complex question to be solved. The evidence that climate and landslides act at only partially overlapping spatial and temporal scales complicates the evaluation. Different research fields, including e.g., climatology, physics, hydrology, geology, hydrogeology, geotechnics, soil science, environmental science, and social science, must be considered. Climatic, environmental, demographic, and economic changes are strictly correlated, with complex feedbacks, to landslide occurrence and variation. Thus, a holistic, multidisciplinary approach is necessary. We reviewed the literature on landslide-climate studies, and found a bias in their geographical distribution, with several studies centered in Europe and North America, and large parts of the world not investigated. We examined advantages and drawbacks of the approaches adopted to evaluate the effects of climate variations on landslides, including prospective modelling and retrospective methods that use landslide and climate records, and paleo-environmental information. We found that the results of landslide-climate studies depend more on the emission scenarios, the global circulation models, the regional climate models, and the methods to downscale the climate variables, than on the description of the variables controlling slope processes. Using ensembles of projections based on a range of emissions scenarios would reduce (or at least quantify) the uncertainties in the obtained results. We performed a preliminary global assessment of the future landslide impact, presenting a global distribution of the projected impact of climate change on landslide activity and abundance. Where global warming is expected to increase, the frequency and intensity of severe rainfall events, a primary trigger of shallow, rapid-moving landslides that cause many landslide fatalities, an increase in the number of people exposed to landslide risk is to be expected. Furthermore, we defined a group of objective and reproducible methods for the quantitative evaluation of the past and future (expected) variations in landslide occurrence and distribution, and in the impact and risk to the population, as a result of changes in climatic and environmental factors (particularly, land use changes), at regional scale. The methods were tested in a southern Italian region, but they can easily applied in other physiographic and climatic regions, where adequate information is available.
Herding cats? A multi-model perspective on tropospheric ozone
NASA Astrophysics Data System (ADS)
Young, P. J.
2015-12-01
Various global multi-model studies have investigated tropospheric ozone changes over multi-decadal timescales. Several robust features emerge, which - for instance - allows the IPCC to associate high confidence in the radiative forcing associated with ozone increases between 1750 and the present day. However, such quantities hide the spread in results between different models, particularly when looking at seasonal and regional scales, and including for comparisons with observations. What can we learn about our scientific understanding from the model spread? What can we learn about models from the model spread? And can we make recommendations for deficient or missing processes if we wish to use our models for environmental prediction? Of course, these questions also have to be asked in the context of what we want the model(s) to do (air quality, climate, stratospheric ozone depletion etc.). This poster will report ongoing work in my group which draws on results from multi-model experiments conducted in support of the most recent IPCC report (CMIP5 and ACCMIP), with an eye to the expected outcomes from the ongoing Chemistry-Climate Model Initiative (CCMI) model simulations.
Huang, Yueng-Hsiang; Lee, Jin; Chen, Zhuo; Perry, MacKenna; Cheung, Janelle H; Wang, Mo
2017-06-01
Zohar and Luria's (2005) safety climate (SC) scale, measuring organization- and group- level SC each with 16 items, is widely used in research and practice. To improve the utility of the SC scale, we shortened the original full-length SC scales. Item response theory (IRT) analysis was conducted using a sample of 29,179 frontline workers from various industries. Based on graded response models, we shortened the original scales in two ways: (1) selecting items with above-average discriminating ability (i.e. offering more than 6.25% of the original total scale information), resulting in 8-item organization-level and 11-item group-level SC scales; and (2) selecting the most informative items that together retain at least 30% of original scale information, resulting in 4-item organization-level and 4-item group-level SC scales. All four shortened scales had acceptable reliability (≥0.89) and high correlations (≥0.95) with the original scale scores. The shortened scales will be valuable for academic research and practical survey implementation in improving occupational safety. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Characterization of potential fire regimes: applying landscape ecology to fire management in Mexico
NASA Astrophysics Data System (ADS)
Jardel, E.; Alvarado, E.; Perez-Salicrup, D.; Morfín-Rios, J.
2013-05-01
Knowledge and understanding of fire regimes is fundamental to design sound fire management practices. The high ecosystem diversity of Mexico offers a great challenge to characterize the fire regime variation at the landscape level. A conceptual model was developed considering the main factors controlling fire regimes: climate and vegetation cover. We classified landscape units combining bioclimatic zones from the Holdridge life-zone system and actual vegetation cover. Since bioclimatic conditions control primary productivity and biomass accumulation (potential fuel), each landscape unit was considered as a fuel bed with a particular fire intensity and behavior potential. Climate is also a determinant factor of post-fire recovery rates of fuel beds, and climate seasonality (length of the dry and wet seasons) influences fire probability (available fuel and ignition efficiency). These two factors influence potential fire frequency. Potential fire severity can be inferred from fire frequency, fire intensity and behavior, and vegetation composition and structure. Based in the conceptual model, an exhaustive literature review and expert opinion, we developed rules to assign a potential fire regime (PFR) defined by frequency, intensity and severity (i.e. fire regime) to each bioclimatic-vegetation landscape unit. Three groups and eight types of potential fire regimes were identified. In Group A are fire-prone ecosystems with frequent low severity surface fires in grasslands (PFR type I) or forests with long dry season (II) and infrequent high-severity fires in chaparral (III), wet temperate forests (IV, fire restricted by humidity), and dry temperate forests (V, fire restricted by fuel recovery rate). Group B includes fire-reluctant ecosystems with very infrequent or occasional mixed severity surface fires limited by moisture in tropical rain forests (VI) or fuel availability in seasonally dry tropical forests (VII). Group C and PFR VIII include fire-free environments that correspond to deserts. Application of PFR model to fire management is discussed.
NASA Astrophysics Data System (ADS)
Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro
2018-04-01
Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation. The modelling results showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30 % in the model error) and AE (between 20 and 75 %) is important to provide a better description of aerosol-radiation-cloud interactions in regional climate models.
Schmitt, Thomas; Habel, Jan Christian; Rödder, Dennis; Louy, Dirk
2014-07-01
Mountain species have evolved important genetic differentiation due to past climatic fluctuations. The genetic uniqueness of many of these lineages is now at risk due to global warming. Here, we analyse allozyme polymorphisms of 1306 individuals (36 populations) of the mountain butterfly Erebia manto and perform Species Distribution Models (SDMs). As a consensus of analyses, we obtained six most likely genetic clusters: (i) Pyrenees with Massif Central; (ii) Vosges; (iii-v) Alps including the Slovakian Carpathians; (vi) southern Carpathians. The Vosges population showed the strongest genetic split from all other populations, being almost as strong as the split between E. manto and its sister species Erebia eriphyle. The distinctiveness of the Pyrenees-Massif Central group and of the southern Carpathians group from all other groups is also quite high. All three groups are assumed to have survived more than one full glacial-interglacial cycle close to their current distributions with up-hill and down-slope shifts conforming climatic conditions. In contrast with these well-differentiated groups, the three groups present in the Alps and the Slovakian Carpathians show a much shallower genetic structure and thus also should be of a more recent origin. As predicted by our SDM projections, rising temperatures will strongly impact the distribution of E. manto. While the populations in the Alps are predicted to shrink, the survival of the three lineages present here should not be at risk. The situation of the three other lineages is quite different. All models predict the extinction of the Vosges lineage in the wake of global warming, and also the southern Carpathians and Pyrenees-Massif Central lineages might be at high risk to disappear. Thus, albeit global warming will therefore be unlikely to threaten E. manto as a species, an important proportion of the species' intraspecific differentiation and thus uniqueness might be lost. © 2014 John Wiley & Sons Ltd.
Interannual Variation in Phytoplankton Concentration and Community in the Pacific Ocean
NASA Technical Reports Server (NTRS)
Rousseaux, C. S.; Gregg, W. W.
2011-01-01
Climate events such as El Nino have been shown to have an effect on the biology of our ocean. Because of the lack of data, we still have very little knowledge about the spatial and temporal effect these climate events may have on biological marine systems. In this study, we used the NASA Ocean Biogeochemical Model (NOBM) to assess the interannual variability in phytoplankton community in the Pacific Ocean between 1998 and 2005. In the North Central and Equatorial Pacific Ocean, changes in the Multivariate El Nino Index were associated with changes in phytoplankton composition. The model identified an increase in diatoms of approx.33 % in the equatorial Pacific in 1999 during a La Nina event. This increase in diatoms coincided with a decrease of approx.11 % in cyanobacteria concentration. The inverse relationship between cyanobacteria and diatoms concentration was significant (p<0.05) throughout the period of study. The use of a numerical model allows us to assess the impact climate variability has on key phytoplankton groups known to lead to contrasting food chain at a spatial and temporal resolution unachievable when relying solely on in-situ observations.
Koivunen, Marita; Anttila, Minna; Kuosmanen, Lauri; Katajisto, Jouko; Välimäki, Maritta
2015-01-01
Objectives: To describe the association of team climate with attitudes toward information and communication technology among nursing staff working on acute psychiatric wards. Background: Implementation of ICT applications in nursing practice brings new operating models to work environments, which may affect experienced team climate on hospital wards. Method: Descriptive survey was used as a study design. Team climate was measured by the Finnish modification of the Team Climate Inventory, and attitudes toward ICT by Burkes' questionnaire. The nursing staff (N = 181, n = 146) on nine acute psychiatric wards participated in the study. Results: It is not self-evident that experienced team climate associates with attitudes toward ICT, but there are some positive relationships between perceived team climate and ICT attitudes. The study showed that nurses' motivation to use ICT had statistically significant connections with experienced team climate, participative safety (p = 0.021), support for innovation (p = 0.042) and task orientation (p = 0.042). Conclusion: The results suggest that asserting team climate and supporting innovative operations may lead to more positive attitudes toward ICT. It is, in particular, possible to influence nurses' motivation to use ICT. More attention should be paid to psychosocial factors such as group education and co-operation at work when ICT applications are implemented in nursing.
Ellis, Christopher J; Yahr, Rebecca; Belinchón, Rocío; Coppins, Brian J
2014-07-01
The biodiversity response to climate change is a major focus in conservation research and policy. Predictive models that are used to project the impact of climate change scenarios - such as bioclimatic envelope models - are widely applied and have come under severe scrutiny. Criticisms of such models have focussed on at least two problems. First, there is an assumption that climate is the primary driver of observed species distributions ('climatic equilibrium'), when other biogeographical controls are often reliably established. Second, a species' sensitivity to macroclimate may become less relevant when impacts are down-scaled to a local level, incorporating a modifying effect of species interactions structuring communities. This article examines the role of different drivers (climate, pollution and landscape habitat structure) in explaining spatial community variation for a widely applied bioindicator group: lichen epiphytes. To provide an analysis free of 'legacy effects' (e.g. formerly higher pollution loads), the study focused on hazel stems as a relatively short-lived and recently colonized substratum. For communities during the present day, climate is shown to interact with stem size/age as the most likely explanation of community composition, thus coupling a macroclimatic and community-scale effect. The position of present-day communities was projected into ordination space for eight sites in England and compared to the position of historical epiphyte communities from the same sites, reconstructed using preserved hazel wattles dating mainly to the 16th Century. This comparison of community structure for the late- to post-Mediaeval period, with the post-Industrial period, demonstrated a consistent shift among independent sites towards warmer and drier conditions, concurrent with the end of the Little Ice Age. Long-term temporal sensitivity of epiphyte communities to climate variation thus complements spatial community patterns. If more widely applied, preserved lichen epiphytes have potential to generate new baseline conditions of environment and biodiversity for preindustrial lowland Europe. © 2014 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Lottle, Lorna; Arheimer, Berit; Gyllensvärd, Frida; Dejong, Fokke; Ludwig, Fulco; Hutjes, Ronald; Martinez, Bernat
2017-04-01
Copernicus Climate Change Service (C3S) is still in the development phase and will combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate and climate dependent sectors in Europe and worldwide. C3S will provide key indicators on climate change drivers and selected sectorial impacts. The aim of these indicators will be to support adaptation and mitigation. This presentation will show one service already operational as a proof-of-concept of this future climate service. The project "Service for Water Indicators in Climate Change Adaptation" (SWICCA) has developed a sectorial information service for water management. It offers readily available climate-impact data, for open access from the web-site http://swicca.climate.copernicus.eu/. The development is user-driven with the overall goal to speed up the workflow in climate-change adaptation of water management across Europe. The service is co-designed by consultant engineers and agencies in 15 case-studies spread out over the continent. SWICCA has an interactive user-interface, which shows maps and graphs, and facilitates data download in user-friendly formats. In total, more than 900 open dataset are given for various hydrometeorological (and a few socioeconomical) variables, model ensembles, resolutions, time-periods and RCPs. The service offers more than 40 precomputed climate impact indicators (CIIs) and transient time-series of 4 essential climate variables ECVs) with high spatial and temporal resolution. To facilitate both near future and far future assessments, SWICCA provides the indicators for different time ranges; normally, absolute values are given for a reference period (e.g. 1971-2000) and the expected future changes for different 30-year periods, such as early century (2011-2040), mid-century (2041-2070) and end-century (2071-2100). An ensemble of model results is always given to indicate confidence in the estimates. The SWICCA demonstrator also includes user guidance, information sheets, tutorials, and links to other relevant websites. The aim of this service is to provide research data and guidance for climate impact assessments in the water sector. The main target group is consulting engineers (so called Purveyors) working with climate change adaptation in the water sector. By using indicators, climate impact assessments can be done without having to run a full production chain from raw climate model results - instead the indicators can be included in the local workflow with local methods applied, to facilitate decision-making and strategies to meet the future. Working with real users will ensure that useful data is inserted into the C3S Climate Data Store (CDS).
NASA Astrophysics Data System (ADS)
Anderson, G.
2012-04-01
Climate Services for Development Planning and Implementation: A Framework for Assessing and Valuing Climate Services Anderson, Glen D. While weather forecasting products have been available globally for decades, the full suite of climate services - including historical and real time observational meteorological data, daily, weekly, and seasonal forecasts, and longer-term climate projections - has only been under development in the last 15 to 20 years. Climate services have been developed and implemented quite quickly in developed countries for public and private sector users. However, diffusion of these tools in developing countries has been slower for several reasons related to 1) lack of awareness of the opportunities and benefits of climate services; 2) spotty record of managing local weather and climate data; and 3) limited resources to build and sustain capacity in providing climate services. The Climate Services Partnership (CSP) was formed during the International Conference on Climate Services (ICCS) in October 2011. The CSP seeks to improve the provision and development of climate services worldwide. During the ICCS, three working groups were formed to carry out the work program of the CSP leading up to the second ICCS in Berlin in September 2012. The Economic Valuation of Climate Services Working Group, chaired by John Zillman and myself, is collaborating on several activities to demonstrate the benefits of climate services and help providers prioritize opportunities for expanding the use of climate services. The proposed paper will provide an overview of the Working Group's activities leading up to the next ICCS and describe specific work that is underway and expected to be completed prior to the EGU meetings. The focal point of the Working Group's activities is the development of matrix to help identify and value the best opportunities for using climate services. Different categories of climate services will be listed in rows and potential users of climate services arrayed in columns. The Working Group is meeting at the American Meteorological Society meetings in January to finalize the matrix and carry out the following analyses: 1) Working Group members in attendance will offer their views on the potential application of climate services for each user group. For simplicity, each cell of the matrix will be assigned a value of "high", "medium", or "low" importance. This will be a starting point and follow-up steps are planned to refine these rankings. 2) The second step will be to review the list of climate services projects and applications (approximately 100) that was developed by the Developing Country Task Team that met in conjunction with the ICCT and assign the climate services in the list to appropriate cells in the matrix. Although not rigorous, it will allow the Working Group to revisit the initial rankings in light of the empirical record. In concert with this review, the matrix will be shared with CSP members to elicit their comments on the rankings and to identify additional climate services projects and applications. 3) A typology of potential economic benefits will be developed and used to describe the benefits in specific cells of the matrix. This work will provide the basis for follow-up case study analysis and preparation of a synthesis paper on valuing climate services benefits.
Acadia National Park Climate Change Scenario Planning Workshop summary
Star, Jonathan; Fisichelli, Nicholas; Bryan, Alexander; Babson, Amanda; Cole-Will, Rebecca; Miller-Rushing, Abraham J.
2016-01-01
This report summarizes outcomes from a two-day scenario planning workshop for Acadia National Park, Maine (ACAD). The primary objective of the workshop was to help ACAD senior leadership make management and planning decisions based on up-to-date climate science and assessments of future uncertainty. The workshop was also designed as a training program, helping build participants' capabilities to develop and use scenarios. The details of the workshop are given in later sections. The climate scenarios presented here are based on published global climate model output. The scenario implications for resources and management decisions are based on expert knowledge distilled through scientist-manager interaction during workgroup break-out sessions at the workshop. Thus, the descriptions below are from these small-group discussions in a workshop setting and should not be taken as vetted research statements of responses to the climate scenarios, but rather as insights and examinations of possible futures (Martin et al. 2011, McBride et al. 2012).
Granath, Gustaf; Limpens, Juul; Posch, Maximilian; Mücher, Sander; de Vries, Wim
2014-04-01
To quantify potential nitrogen (N) deposition impacts on peatland carbon (C) uptake, we explored temporal and spatial trends in N deposition and climate impacts on the production of the key peat forming functional group (Sphagnum mosses) across European peatlands for the period 1900-2050. Using a modelling approach we estimated that between 1900 and 1950 N deposition impacts remained limited irrespective of geographical position. Between 1950 and 2000 N deposition depressed production between 0 and 25% relative to 1900, particularly in temperate regions. Future scenarios indicate this trend will continue and become more pronounced with climate warming. At the European scale, the consequences for Sphagnum net C-uptake remained small relative to 1900 due to the low peatland cover in high-N areas. The predicted impacts of likely changes in N deposition on Sphagnum productivity appeared to be less than those of climate. Nevertheless, current critical loads for peatlands are likely to hold under a future climate. Copyright © 2014 Elsevier Ltd. All rights reserved.
Global climate change: Social and economic research issues
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rice, M.; Snow, J.; Jacobson, H.
This workshop was designed to bring together a group of scholars, primarily from the social sciences, to explore research that might help in dealing with global climate change. To illustrate the state of present understanding, it seemed useful to focus this workshop on three broad questions that are involved in coping with climate change. These are: (1) How can the anticipated economic costs and benefits of climate change be identified; (2) How can the impacts of climate change be adjusted to or avoided; (3) What previously studied models are available for institutional management of the global environment? The resulting discussionsmore » may (1) identify worthwhile avenues for further social science research, (2) help develop feedback for natural scientists about research information from this domain needed by social scientists, and (3) provide policymakers with the sort of relevant research information from the social science community that is currently available. Individual papers are processed separately for the database.« less
Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources
Palmquist, Kyle A.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, Willliam K.
2016-01-01
In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big sagebrush regeneration and survival will be negatively impacted, potentially resulting in shifts in the relative abundance of big sagebrush plant functional groups. Our results also highlight the importance of assessing multiple GCMs to understand the range of climate change outcomes on ecohydrology, which was contingent on the GCM chosen.
Balshi, M. S.; McGuire, A.D.; Duffy, P.; Flannigan, M.; Walsh, J.; Melillo, J.
2009-01-01
Fire is a common disturbance in the North American boreal forest that influences ecosystem structure and function. The temporal and spatial dynamics of fire are likely to be altered as climate continues to change. In this study, we ask the question: how will area burned in boreal North America by wildfire respond to future changes in climate? To evaluate this question, we developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5?? (latitude ?? longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was substantially more predictable in the western portion of boreal North America than in eastern Canada. Burned area was also not very predictable in areas of substantial topographic relief and in areas along the transition between boreal forest and tundra. At the scale of Alaska and western Canada, the empirical fire models explain on the order of 82% of the variation in annual area burned for the period 1960-2002. July temperature was the most frequently occurring predictor across all models, but the fuel moisture codes for the months June through August (as a group) entered the models as the most important predictors of annual area burned. To predict changes in the temporal and spatial dynamics of fire under future climate, the empirical fire models used output from the Canadian Climate Center CGCM2 global climate model to predict annual area burned through the year 2100 across Alaska and western Canada. Relative to 1991-2000, the results suggest that average area burned per decade will double by 2041-2050 and will increase on the order of 3.5-5.5 times by the last decade of the 21st century. To improve the ability to better predict wildfire across Alaska and Canada, future research should focus on incorporating additional effects of long-term and successional vegetation changes on area burned to account more fully for interactions among fire, climate, and vegetation dynamics. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing Ltd.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-22
... supportive environment in which a utility can take steps to be climate ready. In this meeting, the Working... Ready Water Utilities Working Group Meeting Announcement AGENCY: Environmental Protection Agency (EPA... fourth in-person meeting of the Climate Ready Water Utilities (CRWU) Working Group of the National...
NASA Astrophysics Data System (ADS)
Mujumdar, Pradeep P.
2014-05-01
Climate change results in regional hydrologic change. The three prominent signals of global climate change, viz., increase in global average temperatures, rise in sea levels and change in precipitation patterns convert into signals of regional hydrologic change in terms of modifications in water availability, evaporative water demand, hydrologic extremes of floods and droughts, water quality, salinity intrusion in coastal aquifers, groundwater recharge and other related phenomena. A major research focus in hydrologic sciences in recent years has been assessment of impacts of climate change at regional scales. An important research issue addressed in this context deals with responses of water fluxes on a catchment scale to the global climatic change. A commonly adopted methodology for assessing the regional hydrologic impacts of climate change is to use the climate projections provided by the General Circulation Models (GCMs) for specified emission scenarios in conjunction with the process-based hydrologic models to generate the corresponding hydrologic projections. The scaling problem arising because of the large spatial scales at which the GCMs operate compared to those required in distributed hydrologic models, and their inability to satisfactorily simulate the variables of interest to hydrology are addressed by downscaling the GCM simulations to hydrologic scales. Projections obtained with this procedure are burdened with a large uncertainty introduced by the choice of GCMs and emission scenarios, small samples of historical data against which the models are calibrated, downscaling methods used and other sources. Development of methodologies to quantify and reduce such uncertainties is a current area of research in hydrology. In this presentation, an overview of recent research carried out by the author's group on assessment of hydrologic impacts of climate change addressing scale issues and quantification of uncertainties is provided. Methodologies developed with conditional random fields, Dempster-Shafer theory, possibility theory, imprecise probabilities and non-stationary extreme value theory are discussed. Specific applications on uncertainty quantification in impacts on streamflows, evaporative water demands, river water quality and urban flooding are presented. A brief discussion on detection and attribution of hydrologic change at river basin scales, contribution of landuse change and likely alterations in return levels of hydrologic extremes is also provided.
Dragoni, Lisa
2005-11-01
This article attends to a broad range of practically significant employee motivations and provides insight into how to enhance individual-level performance by examining individual-level state goal orientation emergence in organizational work groups. Leadership and multilevel climate processes are theorized to parallel each dimension of state goal orientation to cue and ultimately induce the corresponding achievement focus among individual work group members. It is argued that the patterns of leader behavior, which elucidate the leader's achievement priority, shape group members' psychological and work group climate to embody this priority. Resulting multilevel climate perceptions signal and compel group members to adopt the ascribed form of state goal orientation. The quality of the leader-member exchange relationship is viewed as a means to clarify leader messages in the formation of group members' psychological climate and internalize these cues in the emergence of state goal orientation. Considerations for future research and practice are discussed. ((c) 2005 APA, all rights reserved).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Meehl, G A; Covey, C; McAvaney, B
The Coupled Model Intercomparison Project (CMIP) is designed to allow study and intercomparison of multi-model simulations of present-day and future climate. The latter are represented by idealized forcing of compounded 1% per year CO2 increase to the time of CO2 doubling near year 70 in simulations with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice and land surface. Results from CMIP diagnostic subprojects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September, 2003. Significant progress in diagnosing and understanding results from global coupled models hasmore » been made since the First CMIP Workshop in Melbourne, Australia in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multi-century surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models is now usually around 2.5 degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial tropics. Some new-generation coupled models have atmospheric model resolutions of around 1.5 degrees latitude-longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to 20th and 21st century climate simulations with a variety of forcings (e.g. volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases (GHGs), with the anthropogenic forcings for future climate as well). However, persistent systematic errors noted in previous generations of global coupled models still are present in the present generation (e.g. over-extensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and imminent commencement of the IPCC Fourth Assessment Report (AR4) has prompted rapid coupled model development, which will lead to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, 20th, 21st and 22nd century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort, and details are provided below in how to do so.« less
Distribution of Cenozoic plant relicts in China explained by drought in dry season.
Huang, Yongjiang; Jacques, Frédéric M B; Su, Tao; Ferguson, David K; Tang, Hui; Chen, Wenyun; Zhou, Zhekun
2015-09-15
Cenozoic plant relicts are those groups that were once widespread in the Northern Hemisphere but are now restricted to some small isolated areas as a result of drastic climatic changes. They are good proxies to study how plants respond to climatic changes since their modern climatic requirements are known. Herein we look at the modern distribution of 65 palaeoendemic genera in China and compare it with the Chinese climatic pattern, in order to find a link between the plant distribution and climate. Central China and Taiwan Island are shown to be diversity centres of Cenozoic relict genera, consistent with the fact that these two regions have a shorter dry season with comparatively humid autumn and spring in China. Species distribution models indicate that the precipitation parameters are the most important variables to explain the distribution of relict genera. The Cenozoic wide-scale distribution of relict plants in the Northern Hemisphere is therefore considered to be linked to the widespread humid climate at that time, and the subsequent contraction of their distributional ranges was probably caused by the drying trend along with global cooling.
Earth System Grid II, Turning Climate Datasets into Community Resources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Middleton, Don
2006-08-01
The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects,more » we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.« less
Distribution of Cenozoic plant relicts in China explained by drought in dry season
Huang, Yongjiang; Jacques, Frédéric M. B.; Su, Tao; Ferguson, David K.; Tang, Hui; Chen, Wenyun; Zhou, Zhekun
2015-01-01
Cenozoic plant relicts are those groups that were once widespread in the Northern Hemisphere but are now restricted to some small isolated areas as a result of drastic climatic changes. They are good proxies to study how plants respond to climatic changes since their modern climatic requirements are known. Herein we look at the modern distribution of 65 palaeoendemic genera in China and compare it with the Chinese climatic pattern, in order to find a link between the plant distribution and climate. Central China and Taiwan Island are shown to be diversity centres of Cenozoic relict genera, consistent with the fact that these two regions have a shorter dry season with comparatively humid autumn and spring in China. Species distribution models indicate that the precipitation parameters are the most important variables to explain the distribution of relict genera. The Cenozoic wide-scale distribution of relict plants in the Northern Hemisphere is therefore considered to be linked to the widespread humid climate at that time, and the subsequent contraction of their distributional ranges was probably caused by the drying trend along with global cooling. PMID:26369980
Graham, Matthew R; Jaeger, Jef R; Prendini, Lorenzo; Riddle, Brett R
2013-12-01
The distribution of Beck's Desert Scorpion, Paruroctonus becki (Gertsch and Allred, 1965), spans the 'warm' Mojave Desert and the western portion of the 'cold' Great Basin Desert. We used genetic analyses and species distribution modeling to test whether P. becki persisted in the Great Basin Desert during the Last Glacial Maximum (LGM), or colonized the area as glacial conditions retreated and the climate warmed. Phylogenetic and network analyses of mitochondrial cytochrome c oxidase 1 (cox1), 16S rDNA, and nuclear internal transcribed spacer (ITS-2) DNA sequences uncovered five geographically-structured groups in P. becki with varying degrees of statistical support. Molecular clock estimates and the geographical arrangement of three of the groups suggested that Pliocene geological events in the tectonically dynamic Eastern California Shear Zone may have driven diversification by vicariance. Diversification was estimated to have continued through the Pleistocene, during which a group endemic to the western Great Basin diverged from a related group in the eastern Mojave Desert and western Colorado Plateau. Demographic and network analyses suggested that P. becki underwent a recent expansion in the Great Basin. According to a landscape interpolation of genetic distances, this expansion appears to have occurred from the northwest, implying that P. becki may have persisted in part of the Great Basin during the LGM. This prediction is supported by species distribution models which suggest that climate was unsuitable throughout most of the Great Basin during the LGM, but that small patches of suitable climate may have remained in areas of the Lahontan Trough. Published by Elsevier Inc.
Divergence and diversification in North American Psoraleeae (Fabaceae) due to climate change
Egan, Ashley N; Crandall, Keith A
2008-01-01
Background Past studies in the legume family (Fabaceae) have uncovered several evolutionary trends including differential mutation and diversification rates across varying taxonomic levels. The legume tribe Psoraleeae is shown herein to exemplify these trends at the generic and species levels. This group includes a sizable diversification within North America dated at approximately 6.3 million years ago with skewed species distribution to the most recently derived genus, Pediomelum, suggesting a diversification rate shift. We estimate divergence dates of North American (NAm) Psoraleeae using Bayesian MCMC sampling in BEAST based on eight DNA regions (ITS, waxy, matK, trnD-trnT, trnL-trnF, trnK, trnS-trnG, and rpoB-trnC). We also test the hypothesis of a diversification rate shift within NAm Psoraleeae using topological and temporal methods. We investigate the impact of climate change on diversification in this group by (1) testing the hypothesis that a shift from mesic to xeric habitats acted as a key innovation and (2) investigating diversification rate shifts along geologic time, discussing the impact of Quaternary climate oscillations on diversification. Results NAm Psoraleeae represents a recent, rapid radiation with several genera originating during the Pleistocene, 1 to 2 million years ago. A shift in diversification rate is supported by both methods with a 2.67-fold increase suggested around 2 million years ago followed by a 8.73-fold decrease 440,000 years ago. The hypothesis that a climate regime shift from mesic to xeric habitats drove increased diversification in affected taxa was not supported. Timing of the diversification rate increase supports the hypothesis that glaciation-induced climate changes during the Quaternary influenced diversification of the group. Nonrandom spatial diversification also exists, with greater species richness in the American Southwest. Conclusion This study outlines NAm Psoraleeae as a model example of a recent, rapid radiation. Diversification rate shifts in NAm Psoraleeae are not due to current climate regimes as represented by habitat, but instead to past global climate change resulting from Quaternary glaciations. NAm Psoraleeae diversification is a good example of how earthly dynamics including global climate change and topography work together to shape biodiversity. PMID:19091055
Application of a hybrid association rules/decision tree model for drought monitoring
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Molajou, Amir
2017-12-01
The previous researches have shown that the incorporation of the oceanic-atmospheric climate phenomena such as Sea Surface Temperature (SST) into hydro-climatic models could provide important predictive information about hydro-climatic variability. In this paper, the hybrid application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between drought of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend SSTs of the Black, Mediterranean and Red Seas. Two major steps of the proposed model were the classification of de-trend SST data and selecting the most effective groups and extracting hidden information involved in the data. The techniques of decision tree which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and Heidke Skill Score (HSS) measures were calculated and compared for different considering lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast drought and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and drought of Tabriz and Kermanshah synoptic stations so that the confidence between the monthly Standardized Precipitation Index (SPI) values and the de-trend SST of seas is higher than 70 and 80% respectively for Tabriz and Kermanshah synoptic stations.
NASA Astrophysics Data System (ADS)
Camargo, P. B. D.; Ferreira, M. L.; Oliveira Junior, R. C.; Saleska, S. R.
2014-12-01
Tree growth is a biotic variable of great importance in understanding the dynamics of tree communities and may be used as a tool in studies of biological or climate modeling. Some climate models predict more recurrent climate anomalies in this century, which may alter the functioning of tropical forests with serious structural and demographic implications. The present study aimed to evaluate the profile of tree growth and litterfall production in an eastern Amazon forest, which has suffered recent climatic disturbances. We contrasted different functional groups based on wood density (stem with 0.55; 0.56-0.7; >0.7 g cm-3), light availability (crown illumination index; high illuminated crown - IIC1 until shaded crown - IIC5), and, size class (trees 10-22.5; 22.6-35; 35.1-55; 55,1-90; >90 cm dbh). Tree diameter increment was monthly measured from November 2011 to September 2013 by using dendrometer bands installed on 850 individuals from different families. Litterfall was collected in 64 circular traps, oven dried and weighed, separated into leaves, twigs, reproductive parts and miscellaneous. During the rainy season the sampled trees had the highest rates of tree diametric increment. When analyzing the data by functional groups, large trees had faster growth, but when grouped by wood density, trees with wood density up to 0.55 and between 0.56 and 0.7 g cm-3 had the fastest rates of growth. When grouped by crown illumination index, trees exposed to higher levels of light grew more in comparison to partially shaded trees. Maximum daily air temperature and precipitation were the most important environmental variables in determining the diametric increment profile of the trees. Litterfall production was estimated to be 7.1 Mg ha-1.year-1 and showed a strong seasonal pattern, with dry season production being higher than in the rainy season. Leaves formed the largest fraction of the litterfall, followed by twigs, reproductive parts, and finally miscellaneous. These results show that the profile of tree diametric growth and litterfall production are recorded at close intervals in the preterit analyzes in the same study area and highlights the efficiency of functional groups in determining the tree growth profile.
Earth Experiments in a Virtual World: Introducing Climate & Coding to High School Girls
NASA Astrophysics Data System (ADS)
Singh, H. A.; Twedt, J. R.
2017-12-01
In our increasingly technologically-driven and information-saturated world, literacy in STEM fields can be crucial for career advancement. Nevertheless, both systemic and interpersonal barriers can prevent individuals, particularly members of under-represented groups, from engaging in these fields. Here, we present a high school-level workshop developed to foster basic understanding of climate science while exposing students to the Python programming language. For the past four years, the workshop has been a part of the annual Expanding Your Horizons conference for high school girls, whose mission is to spark interest in STEM fields. Moving through current events in the realm of global climate policy, the fundamentals of climate, and the mathematical representation of planetary energy balance, the workshop culminates in an under-the-hood exploration of a basic climate model coded in the Python programming language. Students interact directly with the underlying code to run `virtual world' experiments that explore the impact of solar insolation, planetary albedo, the greenhouse effect, and meridional energy transport on global temperatures. Engagement with Python is through the Jupyter Notebook interface, which permits direct interaction with the code but is more user-friendly for beginners than a command-line approach. We conclude with further ideas for providing online access to workshop materials for educators, and additional venues for presenting such workshops to under-represented groups in STEM.
The Art and Science of Climate Model Tuning
Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew; ...
2017-03-31
The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less
The Art and Science of Climate Model Tuning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew
The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less
Probabilistic projections of 21st century climate change over Northern Eurasia
NASA Astrophysics Data System (ADS)
Monier, E.; Sokolov, A. P.; Schlosser, C. A.; Scott, J. R.; Gao, X.
2013-12-01
We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity, with a two-dimensional zonal-mean atmosphere, to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three dimensional atmospheric model; and a statistical downscaling, where a pattern scaling algorithm uses climate-change patterns from 17 climate models. This framework allows for key sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections; climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate); natural variability; and structural uncertainty. Results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also nd that dierent initial conditions lead to dierences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider all sources of uncertainty when modeling climate impacts over Northern Eurasia.
Probabilistic projections of 21st century climate change over Northern Eurasia
NASA Astrophysics Data System (ADS)
Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang
2013-12-01
We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.
NASA Technical Reports Server (NTRS)
Kahn, Ralph A.
2014-01-01
AeroCom is an open international initiative of scientists interested in the advancement of the understanding of global aerosol properties and aerosol impacts on climate. A central goal is to more strongly tie and constrain modeling efforts to observational data. A major element for exchanges between data and modeling groups are annual meetings. The meeting was held September 20 through October 2, 1014 and the organizers would like to post the presentations.
Selection of climate change scenario data for impact modelling.
Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg
2012-01-01
Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.
Climate Change Impacts on Environmental and Human Exposure to Mercury in the Arctic
Sundseth, Kyrre; Pacyna, Jozef M.; Banel, Anna; Pacyna, Elisabeth G.; Rautio, Arja
2015-01-01
This paper reviews information from the literature and the EU ArcRisk project to assess whether climate change results in an increase or decrease in exposure to mercury (Hg) in the Arctic, and if this in turn will impact the risks related to its harmful effects. It presents the state-of-the art of knowledge on atmospheric mercury emissions from anthropogenic sources worldwide, the long-range transport to the Arctic, and it discusses the likely environmental fate and exposure effects on population groups in the Arctic under climate change conditions. The paper also includes information about the likely synergy effects (co-benefits) current and new climate change polices and mitigation options might have on mercury emissions reductions in the future. The review concludes that reductions of mercury emission from anthropogenic sources worldwide would need to be introduced as soon as possible in order to assure lowering the adverse impact of climate change on human health. Scientific information currently available, however, is not in the position to clearly answer whether climate change will increase or decrease the risk of exposure to mercury in the Arctic. New research should therefore be undertaken to model the relationships between climate change and mercury exposure. PMID:25837201
Climate change impacts on environmental and human exposure to mercury in the arctic.
Sundseth, Kyrre; Pacyna, Jozef M; Banel, Anna; Pacyna, Elisabeth G; Rautio, Arja
2015-03-31
This paper reviews information from the literature and the EU ArcRisk project to assess whether climate change results in an increase or decrease in exposure to mercury (Hg) in the Arctic, and if this in turn will impact the risks related to its harmful effects. It presents the state-of-the art of knowledge on atmospheric mercury emissions from anthropogenic sources worldwide, the long-range transport to the Arctic, and it discusses the likely environmental fate and exposure effects on population groups in the Arctic under climate change conditions. The paper also includes information about the likely synergy effects (co-benefits) current and new climate change polices and mitigation options might have on mercury emissions reductions in the future. The review concludes that reductions of mercury emission from anthropogenic sources worldwide would need to be introduced as soon as possible in order to assure lowering the adverse impact of climate change on human health. Scientific information currently available, however, is not in the position to clearly answer whether climate change will increase or decrease the risk of exposure to mercury in the Arctic. New research should therefore be undertaken to model the relationships between climate change and mercury exposure.
Creating dialogue: a workshop on "Uncertainty in Decision Making in a Changing Climate"
NASA Astrophysics Data System (ADS)
Ewen, Tracy; Addor, Nans; Johnson, Leigh; Coltekin, Arzu; Derungs, Curdin; Muccione, Veruska
2014-05-01
Uncertainty is present in all fields of climate research, spanning from projections of future climate change, to assessing regional impacts and vulnerabilities, to adaptation policy and decision-making. In addition to uncertainties, managers and planners in many sectors are often confronted with large amounts of information from climate change research whose complex and interdisciplinary nature make it challenging to incorporate into the decision-making process. An overarching issue in tackling this problem is the lack of institutionalized dialogue between climate researchers, decision-makers and user groups. Forums that facilitate such dialogue would allow climate researchers to actively engage with end-users and researchers in different disciplines to better characterize uncertainties and ultimately understand which ones are critically considered and incorporated into decisions made. We propose that the introduction of students to these challenges at an early stage of their education and career is a first step towards improving future dialogue between climate researchers, decision-makers and user groups. To this end, we organized a workshop at the University of Zurich, Switzerland, entitled "Uncertainty in Decision Making in a Changing Climate". It brought together 50 participants, including Bachelor, Master and PhD students and academic staff, and nine selected speakers from academia, industry, government, and philanthropy. Speakers introduced participants to topics ranging from uncertainties in climate model scenarios to managing uncertainties in development and aid agencies. The workshop consisted of experts' presentations, a panel discussion and student group work on case studies. Pedagogical goals included i) providing participants with an overview of the current research on uncertainty and on how uncertainty is dealt with by decision-makers, ii) fostering exchange between practitioners, students, and scientists from different backgrounds, iii) exposing students, at an early stage of their professional life, to multidisciplinary collaborations and real-world problems involving decisions under uncertainty. An opinion survey conducted before and after the workshop enabled us to observe changes in participants' perspectives on what information and tools should be exchanged between researchers and decision-makers to better address uncertainty. Responses demonstrated a marked shift from a pre-workshop vertical conceptualizations of researcher—user group interaction to a post-workshop horizontal mode: in the former, researchers were portrayed as bestowing data-based products to decision-makers, while in the latter, both sets of actors engaged in institutionalized dialogues and frequent communication, exchanging their needs, expertise, and personnel. In addition to the survey, we will draw on examples from the course evaluation to illustrate the strengths and weaknesses of our approach. By doing so, we seek to encourage the organization of similar events by other universities, with the mid-term goal to improve future dialogue. From a pedagogical perspective, introducing students to these ideas at a very early stage in their research careers is an ideal opportunity to establish new modes of communication with an interdisciplinary perspective and strengthen dialogue between climate researchers, decision-makers and user groups.
Korkala, Essi A E; Hugg, Timo T; Jaakkola, Jouni J K
2014-01-01
Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns.
Korkala, Essi A. E.; Hugg, Timo T.; Jaakkola, Jouni J. K.
2014-01-01
Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns. PMID:25054549
INTIMATE: Integration of Ice-core Marine and Terrestrial records
NASA Astrophysics Data System (ADS)
Turney, C. S. M.; Hoek, W. Z.; Intimate Group
2009-04-01
The principal aim of the INTIMATE Project is to synthesize high-resolution ice, terrestrial and marine records spanning the period 60,000 to 8000 years ago (henceforth given as 60-8 ka) to better understand the impact and mechanisms of rapid and extreme climate change, thereby reducing the uncertainty of future predictions. The specific objectives of the INTIMATE Project are to: • lead the development of highly-precise and accurate age-depth models in ice-core, marine, and terrestrial records (including identification and validation of time-stratigraphic marker horizons) over the period 60-8 ka; • promote the development of quantified climate reconstruction methods; • determine the timing, rates of change, spatial variability and climate gradients during key periods at the regional, hemispheric and global level (in collaboration with the INQUA-recognized Australasian INTIMATE Project and future regional INTIMATE projects); • determine the environmental impact of rapid and extreme climate changes in the North Atlantic region (focusing on megafauna and vegetation); and develop climate and environmental reconstructions of change that may be used in climate modeling to better determine the mechanisms of change and how signals are propagated globally. For correlation, precise dating of the records from the different realms is imperative. The development of an event-stratigraphy for the Last Glacial-Interglacial Transition (Björck et al., 1998) provided a template to compare other, independently dated, palaeoclimate records with the high-resolution Greenland oxygen isotope records. The event-stratigraphy has recently been refined and updated to the new NGRIP record using the GICC05 timescale (Lowe et al., 2008), which will be outlined in this paper. References: Björck, S., Walker, M.J.C., Cwynar, L.C., Johnsen, S., Knudsen, K.-L., Lowe, J.J., Wohlfarth, B. and INTIMATE members (1998) An event stratigraphy for the Last Termination in the North Atlantic region based on the Greenland ice-core record: a proposal by the INTIMATE group, Journal of Quaternary Science 13, 283-292. Lowe, J.J., Rasmussen, S.O., Björck, S., Hoek, W.Z., Steffensen, J.P., Walker, M.J.C., Yu, Z. and INTIMATE group (2008) Precise dating and correlation of events in the North Atlantic region during the Last Termination: a revised protocol recommended by the INTIMATE group. Quaternary Science Reviews, 27, 6-17.
Improving Climate Projections Using "Intelligent" Ensembles
NASA Technical Reports Server (NTRS)
Baker, Noel C.; Taylor, Patrick C.
2015-01-01
Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.
Evans, Margaret E K; Smith, Stephen A; Flynn, Rachel S; Donoghue, Michael J
2009-02-01
We integrate climatic niche models and dated phylogenies to characterize the evolution of climatic niches in Oenothera sections Anogra and Kleinia (Onagraceae), and from that we make inferences on diversification in relation to climate. The evolution of climatic tolerances in Anogra + Kleinia has been heterogeneous, across phylogenetic groups and across different dimensions of climate. All the extant taxa occur in semiarid to arid conditions (annual precipitation of 10.1-49.1 cm and high temperatures in the warmest month of 28.5 degrees-40.1 degrees C), but there is striking variation among taxa in their climatic tolerances, especially temperature (minimum temperatures in the coldest month of -14.0 degrees to 5.3 degrees C) and summer versus winter precipitation (precipitation in the warmest quarter of 0.6-19.4 cm). Climatic disparity is especially pronounced in two subclades (californica, deltoides) that radiated in the southwestern United States and California, apparently including both divergent and convergent evolution of climatic tolerances. This niche evolution is remarkable, given the probable timescale of the radiation (approximately 1 million years). We suggest that the spatiotemporal climatic heterogeneity of western North America has served as a driver of diversification. Our data are also consistent with Axelrod's hypothesis that the spread of arid conditions in western North America stimulated diversification of arid-adapted lineages.
The role of building models in the evaluation of heat-related risks
NASA Astrophysics Data System (ADS)
Buchin, Oliver; Jänicke, Britta; Meier, Fred; Scherer, Dieter; Ziegler, Felix
2016-04-01
Hazard-risk relationships in epidemiological studies are generally based on the outdoor climate, despite the fact that most of humans' lifetime is spent indoors. By coupling indoor and outdoor climates with a building model, the risk concept developed can still be based on the outdoor conditions but also includes exposure to the indoor climate. The influence of non-linear building physics and the impact of air conditioning on heat-related risks can be assessed in a plausible manner using this risk concept. For proof of concept, the proposed risk concept is compared to a traditional risk analysis. As an example, daily and city-wide mortality data of the age group 65 and older in Berlin, Germany, for the years 2001-2010 are used. Four building models with differing complexity are applied in a time-series regression analysis. This study shows that indoor hazard better explains the variability in the risk data compared to outdoor hazard, depending on the kind of building model. Simplified parameter models include the main non-linear effects and are proposed for the time-series analysis. The concept shows that the definitions of heat events, lag days, and acclimatization in a traditional hazard-risk relationship are influenced by the characteristics of the prevailing building stock.
NASA Astrophysics Data System (ADS)
Gabaldón, Clara; Lorite, Ignacio J.; Inés Mínguez, M.; Dosio, Alessandro; Sánchez-Sánchez, Enrique; Ruiz-Ramos, Margarita
2013-04-01
The objective of this work is to generate and analyse adaptation strategies to cope with impacts of climate change on cereal cropping systems in Andalusia (Southern Spain) in a semi-arid environment, with focus on extreme events. In Andalusia, located in the South of the Iberian Peninsula, cereals crops may be affected by the increase in average temperatures, the precipitation variability and the possible extreme events. Those impacts may cause a decrease in both water availability and the pollination rate resulting on a decrease in yield and the farmer's profitability. Designing local and regional adaptation strategies to reduce these negative impacts is necessary. This study is focused on irrigated maize on five Andalusia locations. The Andalusia Network of Agricultural Trials (RAEA in Spanish) provided the experimental crop and soil data, and the observed climate data were obtained from the Agroclimatic Information Network of Andalusia and the Spanish National Meteorological Agency (AEMET in Spanish). The data for future climate scenarios (2013-2050) were generated by Dosio and Paruolo (2011) and Dosio et al. (2012), who corrected the bias of ENSEMBLES data for maximum and minimum temperatures and precipitation. ENSEMBLES data were the results of numerical simulations obtained from a group of regional climate models at high resolution (25 km) from the European Project ENSEMBLES (http://www.ensembles-eu.org/). Crop models considered were CERES-maize (Jones and Kiniry, 1986) under DSSAT platform, and CropSyst (Stockle et al., 2003). Those crop models were applied only on locations were calibration and validation were done. The effects of the adaptations strategies, such as changes in sowing dates or choice of cultivar, were evaluated regarding water consumption; changes in phenological dates were also analysed to compare with occurrence of extreme events of maximum temperature. These events represent a threat on summer crops due to the reduction on the duration of grain filling period with the consequent reduction in yield (Ruiz-Ramos et al., 2011) and with the supraoptimal temperatures in pollination. Finally, results of simulated impacts and adaptations were compared to previous studies done without bias correction of climatic projections, at low resolution and with previous versions of crop models (Mínguez et al., 2007). This study will contribute to MACSUR knowledge Hub within the Joint Programming Initiative on Agriculture, Food Security and Climate Change (FACCE - JPI) of EU and is financed by MULCLIVAR project (CGL2012-38923-C02-02) and IFAPA project AGR6126 from Junta de Andalucía, Spain. References Dosio A. and Paruolo P., 2011. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, VOL. 116, D16106, doi:10.1029/2011JD015934 Dosio A., Paruolo P. and Rojas R., 2012. Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research, Volume 117, D17, doi: 0.1029/2012JD017968 Jones, C.A., and J.R. Kiniry. 1986. CERES-Maize: A simulation model of maize growth and development. Texas A&M Univ. Press, College Station. Mínguez, M.I., M. Ruiz-ramos, C.H. Díaz-Ambrona, and M. Quemada. 2007. First-order impacts on winter and summer crops assessed with various high-resolution climate models in the Iberian Peninsula. Climatic Change 81: 343-355. Ruiz-Ramos, M., E. Sanchez, C. Galllardo, and M.I. Minguez. 2011. Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula. Natural Hazards and Earth System Science 11: 3275-3291. Stockle, C.O., M. Donatelli, and R. Nelson. 2003. CropSyst , a cropping systems simulation model. European Journal of Agronomy18: 289-307.
A potato model intercomparison across varying climates and productivity levels.
Fleisher, David H; Condori, Bruno; Quiroz, Roberto; Alva, Ashok; Asseng, Senthold; Barreda, Carolina; Bindi, Marco; Boote, Kenneth J; Ferrise, Roberto; Franke, Angelinus C; Govindakrishnan, Panamanna M; Harahagazwe, Dieudonne; Hoogenboom, Gerrit; Naresh Kumar, Soora; Merante, Paolo; Nendel, Claas; Olesen, Jorgen E; Parker, Phillip S; Raes, Dirk; Raymundo, Rubi; Ruane, Alex C; Stockle, Claudio; Supit, Iwan; Vanuytrecht, Eline; Wolf, Joost; Woli, Prem
2017-03-01
A potato crop multimodel assessment was conducted to quantify variation among models and evaluate responses to climate change. Nine modeling groups simulated agronomic and climatic responses at low-input (Chinoli, Bolivia and Gisozi, Burundi)- and high-input (Jyndevad, Denmark and Washington, United States) management sites. Two calibration stages were explored, partial (P1), where experimental dry matter data were not provided, and full (P2). The median model ensemble response outperformed any single model in terms of replicating observed yield across all locations. Uncertainty in simulated yield decreased from 38% to 20% between P1 and P2. Model uncertainty increased with interannual variability, and predictions for all agronomic variables were significantly different from one model to another (P < 0.001). Uncertainty averaged 15% higher for low- vs. high-input sites, with larger differences observed for evapotranspiration (ET), nitrogen uptake, and water use efficiency as compared to dry matter. A minimum of five partial, or three full, calibrated models was required for an ensemble approach to keep variability below that of common field variation. Model variation was not influenced by change in carbon dioxide (C), but increased as much as 41% and 23% for yield and ET, respectively, as temperature (T) or rainfall (W) moved away from historical levels. Increases in T accounted for the highest amount of uncertainty, suggesting that methods and parameters for T sensitivity represent a considerable unknown among models. Using median model ensemble values, yield increased on average 6% per 100-ppm C, declined 4.6% per °C, and declined 2% for every 10% decrease in rainfall (for nonirrigated sites). Differences in predictions due to model representation of light utilization were significant (P < 0.01). These are the first reported results quantifying uncertainty for tuber/root crops and suggest modeling assessments of climate change impact on potato may be improved using an ensemble approach. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Roesch-McNally, G. E.; Basche, A.; Tyndall, J.; Arbuckle, J. G.; Miguez, F.; Bowman, T.
2014-12-01
Scientists predict a number of climate changes for the US Midwest with expected declines in crop productivity as well as eco-hydrological impacts. More frequent extreme rain events particularly in the spring may well increase saturated soils thus complicating agronomic interests and also exacerbate watershed scale impairments (e.g., sediment, nutrient loss). In order to build more resilient production systems in light of climate change, farmers will increasingly need to implement conservation practices (singularly or more likely in combination) that enable farmers to manage profitable businesses yet mitigate consequential environmental impacts that have both in-field and off-farm implications. Cover crops are empirically known to promote many aspects of soil and water health yet even the most aggressive recent estimates show that only 1-2% of the total acreage in Iowa have been planted to cover crops. In order to better understand why farmers are reluctant to adopt cover crops across Iowa we combined agronomic and financial data from long-term field trials, working farm trials and model simulations so as to present comprehensive data-driven information to farmers in focus group discussions in order to understand existing barriers, perceived benefits and responses to the information presented. Four focus groups (n=29) were conducted across Iowa in four geographic regions. Focus group discussions help explore the nuance of farmers' responses to modeling outputs and their real-life agronomic realities, thus shedding light on the social and psychological barriers with cover crop utilization. Among the key insights gained, comprehensive data-driven research can influence farmer perspectives on potential cover crop impacts to cash crop yields, experienced costs are potentially quite variable, and having field/farm benefits articulated in economic terms are extremely important when farmers weigh the opportunity costs associated with adopting new practices. Our work represents multidisciplinary collaboration necessary to gain greater understanding of what it will take for farmers to cover the ground to prevent erosion and nutrient losses in the context of a changing climate.
Designing ecological climate change impact assessments to reflect key climatic drivers
Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.
2017-01-01
Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.
Designing ecological climate change impact assessments to reflect key climatic drivers.
Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T
2017-07-01
Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.
The Effects of Climate Model Similarity on Local, Risk-Based Adaptation Planning
NASA Astrophysics Data System (ADS)
Steinschneider, S.; Brown, C. M.
2014-12-01
The climate science community has recently proposed techniques to develop probabilistic projections of climate change from ensemble climate model output. These methods provide a means to incorporate the formal concept of risk, i.e., the product of impact and probability, into long-term planning assessments for local systems under climate change. However, approaches for pdf development often assume that different climate models provide independent information for the estimation of probabilities, despite model similarities that stem from a common genealogy. Here we utilize an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to develop probabilistic climate information, with and without an accounting of inter-model correlations, and use it to estimate climate-related risks to a local water utility in Colorado, U.S. We show that the tail risk of extreme climate changes in both mean precipitation and temperature is underestimated if model correlations are ignored. When coupled with impact models of the hydrology and infrastructure of the water utility, the underestimation of extreme climate changes substantially alters the quantification of risk for water supply shortages by mid-century. We argue that progress in climate change adaptation for local systems requires the recognition that there is less information in multi-model climate ensembles than previously thought. Importantly, adaptation decisions cannot be limited to the spread in one generation of climate models.
Integrated approaches to climate-crop modelling: needs and challenges.
Betts, Richard A
2005-11-29
This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate-vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (03) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation may be affected by changes in runoff as a direct consequence of climate change, and may also be affected by climate-related changes in demand for water for other uses. It is, therefore, necessary to consider the interactions between the responses of several impacts sectors to climate change. Overall, there is a strong case for a much closer coupling between models of climate, crops and hydrology, but this in itself poses challenges arising from issues of scale and errors in the models. A strategy is proposed whereby the pursuit of a fully coupled climate-chemistry-crop-hydrology model is paralleled by continued use of separate climate and land surface models but with a focus on consistency between the models.
NASA Astrophysics Data System (ADS)
Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.
2013-12-01
One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.
Populations of concern: Chapter 9
Gamble, Janet; Balbus, John; Berger, Martha; Bouye, Karen; Campbell, Vince; Chief, Karletta; Conlon, K.; Crimmins, Allison; Flanagan, Barry; Gonzalez-Maddux, C.; Hallisey, E.; Hutchins, S.; Jantarasami, L.; Khoury, S.; Kiefer, M.; Kolling, J.; Lynn, K.; Manangan, A.; McDonald, M.; Morello-Frosch, R.; Hiza, Margaret; Sheffield, P.; Thigpen Tart, K.; Watson, J.; Whyte, K.P.; Wolkin, A.F.
2016-01-01
Climate change is already causing, and is expected to continue to cause, a range of health impacts that vary across different population groups in the United States. The vulnerability of any given group is a function of its sensitivity to climate change related health risks, its exposure to those risks, and its capacity for responding to or coping with climate variability and change. Vulnerable groups of people, described here as populations of concern, include those with low income, some communities of color, immigrant groups (including those with limited English proficiency), Indigenous peoples, children and pregnant women, older adults, vulnerable occupational groups, persons with disabilities, and persons with preexisting or chronic medical conditions. Planners and public health officials, politicians and physicians, scientists and social service providers are tasked with understanding and responding to the health impacts of climate change. Collectively, their characterization of vulnerability should consider how populations of concern experience disproportionate, multiple, and complex risks to their health and well-being in response to climate change. Some groups face a number of stressors related to both climate and non-climate factors. For example, people living in impoverished urban or isolated rural areas, floodplains, coastlines, and other at-risk locations are more vulnerable not only to extreme weather and persistent climate change but also to social and economic stressors. Many of these stressors can occur simultaneously or consecutively. Over time, this “accumulation” of multiple, complex stressors is expected to become more evident1 as climate impacts interact with stressors associated with existing mental and physical health conditions and with other socioeconomic and demographic factors.
NASA Technical Reports Server (NTRS)
Han, Rongqing; Wang, Hui; Hu, Zeng-Zhen; Kumar, Arun; Li, Weijing; Long, Lindsey N.; Schemm, Jae-Kyung E.; Peng, Peitao; Wang, Wanqiu; Si, Dong;
2016-01-01
An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño-Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño-namely, eastern Pacific (EP) and central Pacific (CP) El Niño-and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.
Next-Generation Climate Modeling Science Challenges for Simulation, Workflow and Analysis Systems
NASA Astrophysics Data System (ADS)
Koch, D. M.; Anantharaj, V. G.; Bader, D. C.; Krishnan, H.; Leung, L. R.; Ringler, T.; Taylor, M.; Wehner, M. F.; Williams, D. N.
2016-12-01
We will present two examples of current and future high-resolution climate-modeling research that are challenging existing simulation run-time I/O, model-data movement, storage and publishing, and analysis. In each case, we will consider lessons learned as current workflow systems are broken by these large-data science challenges, as well as strategies to repair or rebuild the systems. First we consider the science and workflow challenges to be posed by the CMIP6 multi-model HighResMIP, involving around a dozen modeling groups performing quarter-degree simulations, in 3-member ensembles for 100 years, with high-frequency (1-6 hourly) diagnostics, which is expected to generate over 4PB of data. An example of science derived from these experiments will be to study how resolution affects the ability of models to capture extreme-events such as hurricanes or atmospheric rivers. Expected methods to transfer (using parallel Globus) and analyze (using parallel "TECA" software tools) HighResMIP data for such feature-tracking by the DOE CASCADE project will be presented. A second example will be from the Accelerated Climate Modeling for Energy (ACME) project, which is currently addressing challenges involving multiple century-scale coupled high resolution (quarter-degree) climate simulations on DOE Leadership Class computers. ACME is anticipating production of over 5PB of data during the next 2 years of simulations, in order to investigate the drivers of water cycle changes, sea-level-rise, and carbon cycle evolution. The ACME workflow, from simulation to data transfer, storage, analysis and publication will be presented. Current and planned methods to accelerate the workflow, including implementing run-time diagnostics, and implementing server-side analysis to avoid moving large datasets will be presented.
The CARIPANDA project: Climate change and water resources in the Adamello Natural Park of Italy
NASA Astrophysics Data System (ADS)
Bocchiola, D.
2009-04-01
The three years (2007-2009) CARIPANDA project funded by the Cariplo Foundation of Italy is aimed to evaluate scenarios for water resources in the Adamello natural Park of Italy in a window of 50 years or so (until 2050). The project is led by Ente Parco Adamello and involves Politecnico di Milano, Università Statale di Milano, Università di Brescia, and ARPA Lombardia as scientific partners, while ENEL hydropower Company of Italy joins the project as stake holder. The Adamello Natural Park is a noteworthy resource in the Italian Alps. The Adamello Group is made of several glacierized areas (c. 24 km2), of both debris covered and free ice types, including the widest Italian Glacier, named Adamello, spreading on an area of about c. 18 km2. Also the Adamello Natural Reserve, covering 217 km2 inside the Adamello Park and including the Adamello glaciers, hosts a number of high altitude safeguarded vegetal and animal species, the safety of which is a primary task of the Reserve. Project's activity involves analysis of local climate trend, field campaigns on glaciers, hydrological modelling and remote sensing of snow and ice covered areas, aimed to build a consistent model of the present hydrological conditions and of the areas. Then, properly tailored climate change projections for the area, obtained using local data driven downscaling of climate change projections from GCMs model, are used to infer the likely response to expected climate change conditions. With two years in the project now some preliminary findings can be highlighted and some preliminary trend analysis carried out. The proposed poster provides a resume of the main results of the project insofar, of interest as a benchmark for similar ongoing and foregoing projects about climate change impact on European mountainous natural areas.
David E. Rupp,
2016-05-05
The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.
Relationships between Climate, Process, and Performance in Continuous Quality Improvement Groups
ERIC Educational Resources Information Center
Wilkens, Roxanne; London, Manuel
2006-01-01
This study examined relationships between group climate (participants' learning orientation, feelings of psychological safety, and self-disclosure), process (feedback and conflict), and performance in continuous quality improvement groups. Forty-nine participants in eight hospital groups were surveyed as the groups neared completion. Groups were…
NASA Astrophysics Data System (ADS)
Lewis, Sophie; Karoly, David
2013-04-01
Changes in extreme climate events pose significant challenges for both human and natural systems. Some climate extremes are likely to become "more frequent, more widespread and/or more intense during the 21st century" (Intergovernmental Panel on Climate Change, 2007) due to anthropogenic climate change. Particularly in Australia, El Niño-Southern Oscillation (ENSO) has a relationship to the relative frequency of temperature and precipitation extremes. In this study, we investigate the record high two-summer rainfall observed in Australia (2010-2011 and 2011-2012). This record rainfall occurred in association with a two year extended La Niña event and resulted in severe and extensive flooding. We examine simulated changes in seasonal-scale rainfall extremes in the Australian region in a suite of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). In particular, we utilise the novel CMIP5 detection and attribution historical experiments with various forcings (natural forcings only and greenhouse gas forcings only) to examine the impact of various anthropogenic forcings on seasonal-scale extreme rainfall across Australia. Using these standard detection and attribution experiments over the period of 1850 to 2005, we examine La Niña contributions to the 2-season record rainfall, as well as the longer-term climate change contribution to rainfall extremes. Was there an anthropogenic influence in the record high Australian summer rainfall over 2010 to 2012, and if so, how much influence? Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report on the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., 996 pp., Cambridge Univ. Press, Cambridge, U. K.
Orlandini, Simone; Nejedlik, Pavol; Eitzinger, Josef; Alexandrov, Vesselin; Toulios, Leonidas; Calanca, Pierluigi; Trnka, Miroslav; Olesen, Jørgen E
2008-12-01
Climate plays a fundamental role in agriculture because of to its influence on production. All processes are regulated by specific climatic requirements. Furthermore, European agriculture, based on highly developed farming techniques, is mainly oriented to high quality food production that is more susceptible to meteorological hazards. These hazards can modify environment-genotype interactions, which can affect the quality of production. The COST 734 Action (Impacts of Climate Change and Variability on European Agriculture), launched in 2006, is composed of 28 signature countries and is funded by the European Commission. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The Action will concentrate on four different tasks: agroclimatic indices and simulation models, including review and assessment of tools used to relate climate and agricultural processes; evaluation of the current trends of agroclimatic indices and model outputs, including remote sensing; developing and assessing future regional and local scenarios of agroclimatic conditions; and risk assessment and foreseen impacts on agriculture. The work will be carried out by respective Working Groups. This paper presents the results of the analysis of the first phase of inventory activity. Specific questionnaires were disseminated among COST 734 countries to collect information on climate change analysis, studies, and impact at the European level. The results were discussed with respect to their spatial distribution in Europe and to identify possible common long- and short-term strategies for adaptation.
Public Engagement on Climate Change
NASA Astrophysics Data System (ADS)
Curry, J.
2011-12-01
Climate change communication is complicated by complexity of the scientific problem, multiple perspectives on the magnitude of the risk from climate change, often acrimonious disputes between scientists, high stakes policy options, and overall politicization of the issue. Efforts to increase science literacy as a route towards persuasion around the need for a policy like cap and trade have failed, because the difficulty that a scientist has in attempting to make sense of the social and political complexity is very similar to the complexity facing the general public as they try to make sense of climate science itself. In this talk I argue for a shift from scientists and their institutions as information disseminators to that of public engagement and enablers of public participation. The goal of engagement is not just to inform, but to enable, motivate and educate the public regarding the technical, political, and social dimensions of climate change. Engagement is a two-way process where experts and decision-makers seek input and learn from the public about preferences, needs, insights, and ideas relative to climate change impacts, vulnerabilities, solutions and policy options. Effective public engagement requires that scientists detach themselves from trying to control what the public does with the acquired knowledge and motivation. The goal should not be to "sell" the public on particular climate change solutions, since such advocacy threatens public trust in scientists and their institutions. Conduits for public engagement include the civic engagement approach in the context of community meetings, and perhaps more significantly, the blogosphere. Since 2006, I have been an active participant in the climate blogosphere, focused on engaging with people that are skeptical of AGW. A year ago, I started my own blog Climate Etc. at judithcurry.com. The demographic that I have focused my communication/engagement activities are the technically educated and scientifically literate public, many of whom have become increasingly skeptical of climate science the more they investigate the topic. Specific issues that this group has with climate science include concerns that science that cannot easily be separated from risk assessment and value judgments; concern that assessments (e.g. IPCC) have become a Maxwell's daemon for climate research; inadequate assessment of our ignorance of this complex scientific issue; elite scientists and scientific institutions losing credibility with the public; political exploitation of the public's lack of understanding; and concerns about the lack of public accountability of climate science and climate models that are being used as the basis for far reaching decisions and policies. Individuals in this group have the technical ability to understand and examine climate science arguments and are not prepared to cede judgment on this issue to the designated and self-proclaimed experts. This talk will describe my experiences in engaging with this group and what has been learned, both by myself and by participants in the discussion at Climate Etc.
Ribeiro, Priciane C; Souza, Matheus L; Muller, Larissa A C; Ellis, Vincenzo A; Heuertz, Myriam; Lemos-Filho, José P; Lovato, Maria Bernadete
2016-11-01
The Cerrado is the largest South American savanna and encompasses substantial species diversity and environmental variation. Nevertheless, little is known regarding the influence of the environment on population divergence of Cerrado species. Here, we searched for climatic drivers of genetic (nuclear microsatellites) and leaf trait divergence in Annona crassiflora, a widespread tree in the Cerrado. The sampling encompassed all phytogeographic provinces of the continuous area of the Cerrado and included 397 individuals belonging to 21 populations. Populations showed substantial genetic and leaf trait divergence across the species' range. Our data revealed three spatially defined genetic groups (eastern, western and southern) and two morphologically distinct groups (eastern and western only). The east-west split in both the morphological and genetic data closely mirrors previously described phylogeographic patterns of Cerrado species. Generalized linear mixed effects models and multiple regression analyses revealed several climatic factors associated with both genetic and leaf trait divergence among populations of A. crassiflora. Isolation by environment (IBE) was mainly due to temperature seasonality and precipitation of the warmest quarter. Populations that experienced lower precipitation summers and hotter winters had heavier leaves and lower specific leaf area. The southwestern area of the Cerrado had the highest genetic diversity of A. crassiflora, suggesting that this region may have been climatically stable. Overall, we demonstrate that a combination of current climate and past climatic changes have shaped the population divergence and spatial structure of A. crassiflora. However, the genetic structure of A. crassiflora reflects the biogeographic history of the species more strongly than leaf traits, which are more related to current climate. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Osburn, Christopher L.; Anderson, Nicholas J.; Stedmon, Colin A.; Giles, Madeline E.; Whiteford, Erika J.; McGenity, Terry J.; Dumbrell, Alex J.; Underwood, Graham J. C.
2017-12-01
Dissolved organic matter (DOM) concentration and quality were examined from Arctic lakes located in three clusters across south-west (SW) Greenland, covering the regional climatic gradient: cool, wet coastal zone; dry inland interior; and cool, dry ice-marginal areas. We hypothesized that differences in mean annual precipitation between sites would result in a reduced hydrological connectivity between lakes and their catchments and that this concentrates degraded DOM. The DOM in the inland lake group was characterized by a lower aromaticity and molecular weight, a low soil-like fluorescence, and carbon stable isotope (δ13C-DOC) values enriched by 2‰ relative to the coastal group. DOC-specific absorbance (SUVA254) and DOC-specific soil-like fluorescence (SUVFC1) revealed seasonal and climatic gradients across which DOM exhibited a dynamic we term "pulse-process": Pulses of DOM exported from soils to lakes during snow and ice melt were followed by pulses of autochthonous DOM inputs (possibly from macrophytes), and their subsequent photochemical and microbial processing. These effects regulated the dynamics of DOM in the inland lakes and suggested that if circumpolar lakes currently situated in cool wetter climatic regimes with strong hydrological connectivity have reduced connectivity under a drier future climate, they may evolve toward an end-point of large stocks of highly degraded DOC, equivalent to the inland lakes in the present study. The regional climatic gradient across SW Greenland and its influence on DOM properties in these lakes provide a model of possible future changes to lake C cycling in high-latitude systems where climatic changes are most pronounced.
Mental models of safety: do managers and employees see eye to eye?
Prussia, Gregory E; Brown, Karen A; Willis, P Geoff
2003-01-01
Disagreements between managers and employees about the causes of accidents and unsafe work behaviors can lead to serious workplace conflicts and distract organizations from the important work of establishing positive safety climate and reducing the incidence of accidents. In this study, the authors examine a model for predicting safe work behaviors and establish the model's consistency across managers and employees in a steel plant setting. Using the model previously described by Brown, Willis, and Prussia (2000), the authors found that when variables influencing safety are considered within a framework of safe work behaviors, managers and employees share a similar mental model. The study then contrasts employees' and managers' specific attributional perceptions. Findings from these more fine-grained analyses suggest the two groups differ in several respects about individual constructs. Most notable were contrasts in attributions based on their perceptions of safety climate. When perceived climate is poor, managers believe employees are responsible and employees believe managers are responsible for workplace safety. However, as perceived safety climate improves, managers and employees converge in their perceptions of who is responsible for safety. It can be concluded from this study that in a highly interdependent work environment, such as a steel mill, where high system reliability is essential and members possess substantial experience working together, managers and employees will share general mental models about the factors that contribute to unsafe behaviors, and, ultimately, to workplace accidents. It is possible that organizations not as tightly coupled as steel mills can use such organizations as benchmarks, seeking ways to create a shared understanding of factors that contribute to a safe work environment. Part of this improvement effort should focus on advancing organizational safety climate. As climate improves, managers and employees are likely to agree more about the causes of safe/unsafe behaviors and workplace accidents, ultimately increasing their ability to work in unison to prevent accidents and to respond appropriately when they do occur. Finally, the survey items included in this study may be useful to organizations wishing to conduct self-assessments.
Temperature-induced mismatches between consumption and metabolism reduce consumer fitness.
Lemoine, Nathan P; Burkepile, Deron E
2012-11-01
As physiological processes of ectotherms are coupled to environmental temperature, climate change will likely alter their fundamental biological rates, including metabolism, consumption, growth, and reproduction. Here we combine the metabolic theory of ecology (MTE) with metabolism and consumption measurements of a model organism, the urchin Lytechinus variegatus, to test how climate change will affect consumer fitness. Unexpectedly, we found that metabolism and consumption exhibit different scaling relationships with temperature and are mismatched at high temperatures. This led to a dramatic reduction in ingestion efficiency and potentially in consumer fitness. Using metaanalysis, we showed that such temperature-driven mismatches between consumption and metabolism are common across taxa and frequently lead to reduced consumer fitness. Our empirical and synthetic analyses identify a mechanism by which climate change reduces the fitness of ectotherm consumers that may be applied to a broad array of taxonomic groups. Moreover, we showed that the assumptions of MTE do not hold at temperatures near the upper range of species' thermal tolerances for a wide array of taxa. Models using MTE to predict the effects of climate change on consumer-resource dynamics may therefore be underestimating the consequences of rising temperatures on population and community dynamics.
NASA Astrophysics Data System (ADS)
Bostrom, A.; Lashof, D.
2004-12-01
For almost two decades both national polls and in-depth studies of global warming perceptions have shown that people commonly conflate weather and global climate change. Not only are current weather events such as anecdotal heat waves, droughts or cold spells treated as evidence for or against global warming, but weather changes such as warmer weather and increased storm intensity and frequency are the consequences most likely to come to mind. Distinguishing weather from climate remains a challenge for many. This weather 'framing' of global warming may inhibit behavioral and policy change in several ways. Weather is understood as natural, on an immense scale that makes controlling it difficult to conceive. Further, these attributes contribute to perceptions that global warming, like weather, is uncontrollable. This talk presents an analysis of data from public opinion polls, focus groups, and cognitive studies regarding people's mental models of and 'frames' for global warming and climate change, and the role weather plays in these. This research suggests that priming people with a model of global warming as being caused by a "thickening blanket of carbon dioxide" that "traps heat" in the atmosphere solves some of these communications problems and makes it more likely that people will support policies to address global warming.
Group climate and empathy in a sample of incarcerated boys.
van der Helm, G H P; Stams, G J J M; van der Stel, J C; van Langen, M A M; van der Laan, P H
2012-12-01
This study examined the influence of group climate on empathy in a Dutch youth correctional facility in a sample of 59 incarcerated delinquent boys. Higher levels of empathy have been shown to be associated with less delinquent and more prosocial behaviour and may therefore be vital for successful rehabilitation and recidivism reduction. Although empathy was originally considered to be a trait, recent neurobiological research has shown that empathy has state-like properties in that levels of empathy change in response to the social environment. This study showed that differences in group climate were associated with cognitive empathy in juvenile delinquents but not with affective empathy. It is speculated that inmates' state-depressive feelings and anxiety could diminish the effects of prison group climate on affective empathy. The discussion focuses on group dynamics in youth correctional facilities. A positive prison group climate in a youth correctional facility could turn out to be a major factor contributing to effectiveness of secure institutional treatment.
NASA Astrophysics Data System (ADS)
Kato, E.; Kawamiya, M.
2011-12-01
In CMIP5 experiments, new emissions scenarios for GCMs and Earth System Models (ESMs) have been constructed as Representative Concentration Pathways (RCPs) by a community effort of Integrated Assessment Modeling (IAM) groups. In RCP scenarios, regional land-use scenarios have been depicted based on the socio-economic assumption of IAMs, and also downscaled spatially explicit land-use maps from the regional scenarios are prepared. In the land-use harmonization project, integrated gridded land-use transition data for the past and future time period has been developed from the reconstruction based on HYDE 3 agricultural data and FAO wood harvest data, and the future land-use scenarios from IAMs. These gridded land-use dataset are used as a forcing of some ESMs participating to the CMIP5 experiments, to assess the biogeochemical and biogeophysical effects of land-use and land cover change in the climate change simulation. In this study, global net CO2 emissions from land-use change for RCP scenarios are evaluated with an offline terrestrial biogeochemical model, VISIT (Vegetation Integrative SImulation Tool). Also the emissions are evaluated with coupled ESM, MIROC-ESM following the LUCID-CMIP5 protocol to see the effect of land-use and land cover change on climate response. Using the model output, consistency of the land-use change CO2 emission scenarios provided by RCPs are evaluated in terms of effect of CO2 fertilization, climate change, and land-use transition itself including the effect of biomass crops production with CCS. We find that a land-use scenario with decreased agricultural land-use intensity such as RCP 6.0 shows possibility of further absorption of CO2 through the climate-carbon feedback, and cooling effect through both biogeochemical and biogeophysical effects.
CLIMANDES climate science e-learning course
NASA Astrophysics Data System (ADS)
Hunziker, Stefan; Giesche, Alena; Jacques-Coper, Martín; Brönnimann, Stefan
2016-04-01
Over the past three years, members of the Oeschger Centre for Climate Change Research (OCCR) and the Climatology group at the Institute of Geography at the University of Bern, have developed a new climate science e-learning course as part of the CLIMANDES project. This project is a collaboration between Peruvian and Swiss government, research, and education institutions. The aim of this e-learning material is to strengthen education in climate sciences at the higher education and professional level. The course was recently published in 2015 by Geographica Bernensia, and is hosted online by the Peruvian Servicio Nacional de Meteorología e Hidrología (SENAMHI): http://surmx.com/chamilo/climandes/e-learning/. The course is furthermore available for offline use through USB sticks, and a number of these are currently being distributed to regional training centers around the world by the WMO (World Meteorological Organization). There are eight individual modules of the course that each offer approximately 2 hours of individual learning material, featuring several additional learning activities, such as the online game "The Great Climate Poker" (http://www.climatepoker.unibe.ch/). Overall, over 50 hours of learning material are provided by this course. The modules can be integrated into university lectures, used as single units in workshops, or be combined to serve as a full course. This e-learning course presents a broad spectrum of topics in climate science, including an introduction to climatology, atmospheric and ocean circulation, climate forcings, climate observations and data, working with data products, and climate models. This e-learning course offers a novel approach to teaching climate science to students around the world, particularly through three important features. Firstly, the course is unique in its diverse range of learning strategies, which include individual reading material, video lectures, interactive graphics, responsive quizzes, as well as group activities and discussions that are led by a tutor. This combination of self-learning and group-based learning presents a new and more interactive style of online education. Secondly, the course provides links to many existing e-learning and other online learning resources for specific climate science topics. This makes the course a starting point for students looking to deepen their knowledge in specific areas. Lastly, the existing course template is available upon request, for teachers to add modules that they would like to offer in addition to the CLIMANDES course. This gives instructors an easy way to adapt the course to their needs and learn about the software needed to make more e-learning material.
Exploratory Long-Range Models to Estimate Summer Climate Variability over Southern Africa.
NASA Astrophysics Data System (ADS)
Jury, Mark R.; Mulenga, Henry M.; Mason, Simon J.
1999-07-01
Teleconnection predictors are explored using multivariate regression models in an effort to estimate southern African summer rainfall and climate impacts one season in advance. The preliminary statistical formulations include many variables influenced by the El Niño-Southern Oscillation (ENSO) such as tropical sea surface temperatures (SST) in the Indian and Atlantic Oceans. Atmospheric circulation responses to ENSO include the alternation of tropical zonal winds over Africa and changes in convective activity within oceanic monsoon troughs. Numerous hemispheric-scale datasets are employed to extract predictors and include global indexes (Southern Oscillation index and quasi-biennial oscillation), SST principal component scores for the global oceans, indexes of tropical convection (outgoing longwave radiation), air pressure, and surface and upper winds over the Indian and Atlantic Oceans. Climatic targets include subseasonal, area-averaged rainfall over South Africa and the Zambezi river basin, and South Africa's annual maize yield. Predictors and targets overlap in the years 1971-93, the defined training period. Each target time series is fitted by an optimum group of predictors from the preceding spring, in a linear multivariate formulation. To limit artificial skill, predictors are restricted to three, providing 17 degrees of freedom. Models with colinear predictors are screened out, and persistence of the target time series is considered. The late summer rainfall models achieve a mean r2 fit of 72%, contributed largely through ENSO modulation. Early summer rainfall cross validation correlations are lower (61%). A conceptual understanding of the climate dynamics and ocean-atmosphere coupling processes inherent in the exploratory models is outlined.Seasonal outlooks based on the exploratory models could help mitigate the impacts of southern Africa's fluctuating climate. It is believed that an advance warning of drought risk and seasonal rainfall prospects will improve the economic growth potential of southern Africa and provide additional security for food and water supplies.
Hajat, Shakoor; Vardoulakis, Sotiris; Heaviside, Clare; Eggen, Bernd
2014-07-01
The most direct way in which climate change is expected to affect public health relates to changes in mortality rates associated with exposure to ambient temperature. Many countries worldwide experience annual heat-related and cold-related deaths associated with current weather patterns. Future changes in climate may alter such risks. Estimates of the likely future health impacts of such changes are needed to inform public health policy on climate change in the UK and elsewhere. Time-series regression analysis was used to characterise current temperature-mortality relationships by region and age group. These were then applied to the local climate and population projections to estimate temperature-related deaths for the UK by the 2020s, 2050s and 2080s. Greater variability in future temperatures as well as changes in mean levels was modelled. A significantly raised risk of heat-related and cold-related mortality was observed in all regions. The elderly were most at risk. In the absence of any adaptation of the population, heat-related deaths would be expected to rise by around 257% by the 2050s from a current annual baseline of around 2000 deaths, and cold-related mortality would decline by 2% from a baseline of around 41 000 deaths. The cold burden remained higher than the heat burden in all periods. The increased number of future temperature-related deaths was partly driven by projected population growth and ageing. Health protection from hot weather will become increasingly necessary, and measures to reduce cold impacts will also remain important in the UK. The demographic changes expected this century mean that the health protection of the elderly will be vital. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Solar-terrestrial Predictions Proceedings. Volume 2: Working Group Reports and Reviews
NASA Technical Reports Server (NTRS)
Donnelly, R. F. (Editor)
1979-01-01
Accurate models are needed to support research in the following areas: spacecraft charging, radiation dosage, transionospheric radio propagation, long and short term solar activity, magnetospheric disturbances, ionospheric interactions, solar weather/climate effects, and geomagnetic applications such as electric power transmission and oil and gas pipeline problems.
NASA Astrophysics Data System (ADS)
Beers, A.
2016-12-01
As a response to ongoing climate change, many species have started to shift their ranges poleward and toward higher elevations and mountain environments are predicted to experience especially rapid climatic changes. Because of this, there is likely a greater risk of habitat loss and local extinctions for species at high elevations compared to species at lower elevations. Among those potentially threatened habitat specialists is the American pika (Ochotona princeps), a climate sensitive indicator of climate change effects which may already be experiencing climate driven extirpations. Pikas are considered sentinels, indicators of greater ecosystem change. Changes in their distribution speaks to changes in availability of resources they require and shifts in the environment. Pika presence is closely tied to sub-surface ice features that act as a temperature buffer and water source. Those sub-surface ice features are critical in water cycling and long-term water storage and drive downstream hydrological and ecological processes. Understanding how this species responds to climate change therefore provides a model to inform landscape level conservation and management decisions. Pikas may be particularly vulnerable in parts of Colorado, including Rocky Mountain National Park (ROMO) and the Niwot Ridge LTER (NWT), where they may face population collapse as habitat suitability and connectivity both decline in response to various possible climate change scenarios, in large part because of cold stress and declining functional connectivity. Because of their potential role as an ecosystem indicator, their risk for decline, and how limitations to their survival likely vary across their range, management groups can use place based models of habitat suitability for pikas or other sentinel species in designing long term monitoring protocols to detect ecosystem responses to climate change. In this project we used remotely sensed data, occupancy surveys, and a random tessellation stratification to design a protocol for ROMO and NWT that best suits those environments. We also demonstrate the efficacy of habitat models based on remote sensing and their potential application toward tracking ecosystem change and species range shifts.
NASA Astrophysics Data System (ADS)
Carothers, R. A.; Sangireddy, H.; Passalacqua, P.
2013-12-01
In his expansive 1957 study of over 80 basins in Arizona, Colorado, New Mexico, and Utah, Mark Melton measured key morphometric, soil, land cover, and climatic parameters [Melton, 1957]. He identified correlations between morphological parameters and climatic regimes in an attempt to characterize the geomorphology of the basin as a function of climate and vegetation. Using modern techniques such as high resolution digital terrain models in combination with high spatial resolution weather station records, vector soil maps, seamless raster geological data, and land cover vector maps, we revisit Melton's 1957 dataset with the following hypotheses: (1) Patterns of channelization carry strong, codependent signatures in the form of statistical correlations of rainfall variability, soil type, and vegetation patterns. (2) Channelization patterns reflect the erosion processes on sub-catchment scale and the subsequent processes of vegetation recovery and gullying. In order to characterize various topographic and climatic parameters, we obtain elevation and land cover data from the USGS National Elevation dataset, climate data from the Western Regional Climate Center and PRISM climate group database, and soil type from the USDA STATSGO soil database. We generate a correlative high resolution database on vegetation, soil cover, lithology, and climatology for the basins identified by Melton in his 1957 study. Using the GeoNet framework developed by Passalacqua et al. [2010], we extract various morphological parameters such as slope, drainage density, and stream frequency. We also calculate metrics for patterns of channelization such as number of channelized pixels in a basin and channel head density. In order to understand the correlation structure between climate and morphological variables, we compute the Pearson's correlation coefficient similar to Melton's analysis and also explore other statistical procedures to characterize the feedbacks between these variables. By identifying the differences in Melton's and our results, we address the influence of climate over the degree of channel dissection in the landscape. References: Melton, M. A. (1957). An analysis of the relations among elements of climate, surface properties, and geomorphology (No. CU-TR-11). COLUMBIA UNIV NEW YORK Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface (2003-2012), 115(F1). PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 4 Feb 2004 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. U.S. General Soil Map (STATSGO2). Available online at http://soildatamart.nrcs.usda.gov USGS National Map Viewer, United States Geological Survey. Web. 10 June 2013. http://viewer.nationalmap.gov/viewer/ Western U.S. Historical Climate Summaries, Western Regional Climate Group, 2013. Web. 10 June 2013. http://www.wrcc.dri.edu/Climsum.html
Social Climate Science: A New Vista for Psychological Science.
Pearson, Adam R; Schuldt, Jonathon P; Romero-Canyas, Rainer
2016-09-01
The recent Paris Agreement to limit greenhouse gas emissions, adopted by 195 nations at the 2015 United Nations Climate Change Conference, signaled unprecedented commitment by world leaders to address the human social aspects of climate change. Indeed, climate change increasingly is recognized by scientists and policymakers as a social issue requiring social solutions. However, whereas psychological research on intrapersonal and some group-level processes (e.g., political polarization of climate beliefs) has flourished, research into other social processes-such as an understanding of how nonpartisan social identities, cultural ideologies, and group hierarchies shape public engagement on climate change-has received substantially less attention. In this article, we take stock of current psychological approaches to the study of climate change to explore what is "social" about climate change from the perspective of psychology. Drawing from current interdisciplinary perspectives and emerging empirical findings within psychology, we identify four distinct features of climate change and three sets of psychological processes evoked by these features that are fundamentally social and shape both individual and group responses to climate change. Finally, we consider how a more nuanced understanding of the social underpinnings of climate change can stimulate new questions and advance theory within psychology. © The Author(s) 2016.
The Dynamical Core Model Intercomparison Project (DCMIP-2016): Results of the Supercell Test Case
NASA Astrophysics Data System (ADS)
Zarzycki, C. M.; Reed, K. A.; Jablonowski, C.; Ullrich, P. A.; Kent, J.; Lauritzen, P. H.; Nair, R. D.
2016-12-01
The 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) assesses the modeling techniques for global climate and weather models and was recently held at the National Center for Atmospheric Research (NCAR) in conjunction with a two-week summer school. Over 12 different international modeling groups participated in DCMIP-2016 and focused on the evaluation of the newest non-hydrostatic dynamical core designs for future high-resolution weather and climate models. The paper highlights the results of the third DCMIP-2016 test case, which is an idealized supercell storm on a reduced-radius Earth. The supercell storm test permits the study of a non-hydrostatic moist flow field with strong vertical velocities and associated precipitation. This test assesses the behavior of global modeling systems at extremely high spatial resolution and is used in the development of next-generation numerical weather prediction capabilities. In this regime the effective grid spacing is very similar to the horizontal scale of convective plumes, emphasizing resolved non-hydrostatic dynamics. The supercell test case sheds light on the physics-dynamics interplay and highlights the impact of diffusion on model solutions.
Multiple Stressors and the Functioning of Coral Reefs.
Harborne, Alastair R; Rogers, Alice; Bozec, Yves-Marie; Mumby, Peter J
2017-01-03
Coral reefs provide critical services to coastal communities, and these services rely on ecosystem functions threatened by stressors. By summarizing the threats to the functioning of reefs from fishing, climate change, and decreasing water quality, we highlight that these stressors have multiple, conflicting effects on functionally similar groups of species and their interactions, and that the overall effects are often uncertain because of a lack of data or variability among taxa. The direct effects of stressors on links among functional groups, such as predator-prey interactions, are particularly uncertain. Using qualitative modeling, we demonstrate that this uncertainty of stressor impacts on functional groups (whether they are positive, negative, or neutral) can have significant effects on models of ecosystem stability, and reducing uncertainty is vital for understanding changes to reef functioning. This review also provides guidance for future models of reef functioning, which should include interactions among functional groups and the cumulative effect of stressors.
Multiple Stressors and the Functioning of Coral Reefs
NASA Astrophysics Data System (ADS)
Harborne, Alastair R.; Rogers, Alice; Bozec, Yves-Marie; Mumby, Peter J.
2017-01-01
Coral reefs provide critical services to coastal communities, and these services rely on ecosystem functions threatened by stressors. By summarizing the threats to the functioning of reefs from fishing, climate change, and decreasing water quality, we highlight that these stressors have multiple, conflicting effects on functionally similar groups of species and their interactions, and that the overall effects are often uncertain because of a lack of data or variability among taxa. The direct effects of stressors on links among functional groups, such as predator-prey interactions, are particularly uncertain. Using qualitative modeling, we demonstrate that this uncertainty of stressor impacts on functional groups (whether they are positive, negative, or neutral) can have significant effects on models of ecosystem stability, and reducing uncertainty is vital for understanding changes to reef functioning. This review also provides guidance for future models of reef functioning, which should include interactions among functional groups and the cumulative effect of stressors.
PIMMS tools for capturing metadata about simulations
NASA Astrophysics Data System (ADS)
Pascoe, Charlotte; Devine, Gerard; Tourte, Gregory; Pascoe, Stephen; Lawrence, Bryan; Barjat, Hannah
2013-04-01
PIMMS (Portable Infrastructure for the Metafor Metadata System) provides a method for consistent and comprehensive documentation of modelling activities that enables the sharing of simulation data and model configuration information. The aim of PIMMS is to package the metadata infrastructure developed by Metafor for CMIP5 so that it can be used by climate modelling groups in UK Universities. PIMMS tools capture information about simulations from the design of experiments to the implementation of experiments via simulations that run models. PIMMS uses the Metafor methodology which consists of a Common Information Model (CIM), Controlled Vocabularies (CV) and software tools. PIMMS software tools provide for the creation and consumption of CIM content via a web services infrastructure and portal developed by the ES-DOC community. PIMMS metadata integrates with the ESGF data infrastructure via the mapping of vocabularies onto ESGF facets. There are three paradigms of PIMMS metadata collection: Model Intercomparision Projects (MIPs) where a standard set of questions is asked of all models which perform standard sets of experiments. Disciplinary level metadata collection where a standard set of questions is asked of all models but experiments are specified by users. Bespoke metadata creation where the users define questions about both models and experiments. Examples will be shown of how PIMMS has been configured to suit each of these three paradigms. In each case PIMMS allows users to provide additional metadata beyond that which is asked for in an initial deployment. The primary target for PIMMS is the UK climate modelling community where it is common practice to reuse model configurations from other researchers. This culture of collaboration exists in part because climate models are very complex with many variables that can be modified. Therefore it has become common practice to begin a series of experiments by using another climate model configuration as a starting point. Usually this other configuration is provided by a researcher in the same research group or by a previous collaborator with whom there is an existing scientific relationship. Some efforts have been made at the university department level to create documentation but there is a wide diversity in the scope and purpose of this information. The consistent and comprehensive documentation enabled by PIMMS will enable the wider sharing of climate model data and configuration information. The PIMMS methodology assumes an initial effort to document standard model configurations. Once these descriptions have been created users need only describe the specific way in which their model configuration is different from the standard. Thus the documentation burden on the user is specific to the experiment they are performing and fits easily into the workflow of doing their science. PIMMS metadata is independent of data and as such is ideally suited for documenting model development. PIMMS provides a framework for sharing information about failed model configurations for which data are not kept, the negative results that don't appear in scientific literature. PIMMS is a UK project funded by JISC, The University of Reading, The University of Bristol and STFC.
Mascherek, Anna C; Schwappach, David L B
2017-01-01
Safety Climate has been acknowledged as an unspecific factor influencing patient safety. However, studies rarely provide in-depth analysis of climate data. As a helpful approach, the concept of "climate strength" has been proposed. In the present study we tested the hypotheses that even if safety climate remains stable on mean-level across time, differences might be evident in strength or shape. The data of two hospitals participating in a large national quality improvement program were analysed for differences in climate profiles at two measurement occasions. We analysed differences on mean-level, differences in percent problematic response, agreement within groups, and frequency histograms in two large hospitals in Switzerland at two measurement occasions (2013 and 2015) applying the Safety Climate Survey. In total, survey responses of 1193 individuals were included in the analyses. Overall, small but significant differences on mean-level of safety climate emerged for some subgroups. Also, although agreement was strong at both time-points within groups, tendencies of divergence or consensus were present in both hospitals. Depending on subgroup and analyses chosen, differences were more or less pronounced. The present study illustrated that taking several measures into account and describing safety climate from different perspectives is necessary in order to fully understand differences and trends within groups and to develop interventions addressing the needs of different groups more precisely.
Advances of NOAA Training Program in Climate Services
NASA Astrophysics Data System (ADS)
Timofeyeva, M. M.
2012-12-01
Since 2002, NOAA's National Weather Service (NWS) Climate Services Division (CSD) has offered numerous training opportunities to NWS staff. After eight-years of development, the training program offers three instructor-led courses and roughly 25 online (distance learning) modules covering various climate topics, such as: climate data and observations, climate variability and change, and NWS national / local climate products (tools, skill, and interpretation). Leveraging climate information and expertise available at all NOAA line offices and partners allows for the delivery of the most advanced knowledge and is a very critical aspect of the training program. The emerging NOAA Climate Service (NCS) requires a well-trained, climate-literate workforce at the local level capable of delivering NOAA's climate products and services as well as providing climate-sensitive decision support. NWS Weather Forecast Offices and River Forecast Centers presently serve as local outlets for the NCS climate services. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-sound messages and amiable communication techniques are important in developing an engaged dialog between the climate service providers and users. Several pilot projects have been conducted by the NWS CSD this past year that apply the program's training lessons and expertise to specialized external user group training. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring instructions to the potential applications for each group of users. Training technical users identified the following critical issues: (1) knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) leveraging partnership with climate services providers; and, (3) applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).
Training NOAA Staff on Effective Communication Methods with Local Climate Users
NASA Astrophysics Data System (ADS)
Timofeyeva, M. M.; Mayes, B.
2011-12-01
Since 2002 NOAA National Weather Service (NWS) Climate Services Division (CSD) offered training opportunities to NWS staff. As a result of eight-year-long development of the training program, NWS offers three training courses and about 25 online distance learning modules covering various climate topics: climate data and observations, climate variability and change, NWS national and local climate products, their tools, skill, and interpretation. Leveraging climate information and expertise available at all NOAA line offices and partners allows delivery of the most advanced knowledge and is a very critical aspect of the training program. NWS challenges in providing local climate services includes effective communication techniques on provide highly technical scientific information to local users. Addressing this challenge requires well trained, climate-literate workforce at local level capable of communicating the NOAA climate products and services as well as provide climate-sensitive decision support. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-unimpaired messages and amiable communication techniques such as story telling approach are important in developing an engaged dialog between the climate service providers and users. Several pilot projects NWS CSD conducted in the past year applied the NWS climate services training program to training events for NOAA technical user groups. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring the instructions to the potential applications of each group of users. Training technical user identified the following critical issues: (1) Knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) Leveraging partnership with climate services providers; and, (3) Applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change. PMID:24658097
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change.
Schmidt, Megan R; Lisco, Claire G; Parrott, Dominic J; Tharp, Andra T
2016-03-01
The present study sought to examine the interactive effects of an external locus of control and interaction in a negative peer group climate on men's perpetration of physical aggression and infliction of injury toward their female intimate partners. Participants were 206 heterosexual males recruited from the metro-Atlanta community who completed self-report measures of external locus of control, involvement in a negative peer group climate, and physical aggression and infliction of injury against intimate partners during the past 12 months. Negative peer group climate was conceptualized as a peer group that displays behavior which may instigate aggressive norms, attitudes, and behaviors. Results indicated that men with an external locus of control were more likely to perpetrate physical aggression toward and inflict injury on their intimate partners if they reported high, but not low, involvement in a negative peer group climate. These results extend current research suggesting external locus of control as a risk factor for intimate partner aggression by highlighting the impact of negative peer groups. Implications and future intervention research are discussed. © The Author(s) 2014.
Mosher, G A; Keren, N; Freeman, S A; Hurburgh, C R
2013-04-01
The safety climate of an agricultural workplace may be affected by several things, including the level of trust that workers have in their work group supervisor and organizational management. Safety climate has been used by previous safety researchers as a measure of worker perceptions of the relative importance of safety as compared with other operational goals. Trust has been linked to several positive safety outcomes, particularly in hazardous work environments, but has not been examined relative to safety climate in the perennially hazardous work environment of a commercial grain elevator. In this study, 177 workers at three Midwest grain elevator companies completed online surveys measuring their perceptions of trust and safety at two administrative levels: organizational management and work group supervisors. Positive and significant relationships were noted between trust and safety climate perceptions for organizational managers and for work group supervisors. Results from this research suggest that worker trust in organizational management and work group supervisors has a positive influence on the employees' perceptions of safety climate at the organizational and work group levels in an agricultural workplace.
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.
Downscaling climate information for local disease mapping.
Bernardi, M; Gommes, R; Grieser, J
2006-06-01
The study of the impacts of climate on human health requires the interdisciplinary efforts of health professionals, climatologists, biologists, and social scientists to analyze the relationships among physical, biological, ecological, and social systems. As the disease dynamics respond to variations in regional and local climate, climate variability affects every region of the world and the diseases are not necessarily limited to specific regions, so that vectors may become endemic in other regions. Climate data at local level are thus essential to evaluate the dynamics of vector-borne disease through health-climate models and most of the times the climatological databases are not adequate. Climate data at high spatial resolution can be derived by statistical downscaling using historical observations but the method is limited by the availability of historical data at local level. Since the 90s', the statistical interpolation of climate data has been an important priority of the Agrometeorology Group of the Food and Agriculture Organization of the United Nations (FAO), as they are required for agricultural planning and operational activities at the local level. Since 1995, date of the first FAO spatial interpolation software for climate data, more advanced applications have been developed such as SEDI (Satellite Enhanced Data Interpolation) for the downscaling of climate data, LOCCLIM (Local Climate Estimator) and the NEW_LOCCLIM in collaboration with the Deutscher Wetterdienst (German Weather Service) to estimate climatic conditions at locations for which no observations are available. In parallel, an important effort has been made to improve the FAO climate database including at present more than 30,000 stations worldwide and expanding the database from developing countries coverage to global coverage.
Process evaluation of sea salt aerosol concentrations at remote marine locations
NASA Astrophysics Data System (ADS)
Struthers, H.; Ekman, A. M.; Nilsson, E. D.
2011-12-01
Sea salt, an important natural aerosol, is generated by bubbles bursting at the surface of the ocean. Sea salt aerosol contributes significantly to the global aerosol burden and radiative budget and are a significant source of cloud condensation nuclei in remote marine areas (Monahan et al., 1986). Consequently, changes in marine aerosol abundance is expected to impact on climate forcing. Estimates of the atmospheric burden of sea salt aerosol mass derived from chemical transport and global climate models vary greatly both in the global total and the spatial distribution (Texor et al. 2006). This large uncertainty in the sea salt aerosol distribution in turn contributes to the large uncertainty in the current estimates of anthropogenic aerosol climate forcing (IPCC, 2007). To correctly attribute anthropogenic climate change and to veraciously project future climate, natural aerosols including sea salt must be understood and accurately modelled. In addition, the physical processes that determine the sea salt aerosol concentration are susceptible to modification due to climate change (Carslaw et al., 2010) which means there is the potential for feedbacks within the climate/aerosol system. Given the large uncertainties in sea salt aerosol modelling, there is an urgent need to evaluate the process description of sea salt aerosols in global models. An extremely valuable source of data for model evaluation is the long term measurements of PM10 sea salt aerosol mass available from a number of remote marine observation sites around the globe (including the GAW network). Sea salt aerosol concentrations at remote marine locations depend strongly on the surface exchange (emission and deposition) as well as entrainment or detrainment to the free troposphere. This suggests that the key parameters to consider in any analysis include the sea surface water temperature, wind speed, precipitation rate and the atmospheric stability. In this study, the sea salt aerosol observations are analysed to quantify the key sensitivities of the processes connecting the physical drivers of sea salt aerosol to the mass tendency. The analysis employs a semi-empirical model based on the time-tendency of the aerosol mass. This approach of focusing on the time-tendency of the sea salt aerosol concentration provides a framework for the process evaluation of sea salt aerosol concentrations in global models. The same analysis methodology can be applied to output from global models. A process of comparing the sensitivity parameters derived from observations and models will reveal model inadequacies and thus guide model improvements. Carslaw, K. S., Boucher, O., Spracklen, D. V., Mann G. W., Rae, J. G. L, Woodward, S., Kulmala, M. (2010). Atmos. Chem. Phys., 10, 1701-1737 IPCC (2007). Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S., D. Monahan, E. C., Spiel, D. E., Davidson, K. L. (1986) Oceanic Whitecaps ed. Monahan E. C. & MacNiochaill, D. Reidel, Norwell, Mass. Texor, C., et al. (2006) Atmos. Chem. Phys., 6, 1777-1813.
Tournebize, Rémi; Manel, Stéphanie; Vigouroux, Yves; Munoz, François; de Kochko, Alexandre
2017-01-01
Past climate fluctuations shaped the population dynamics of organisms in space and time, and have impacted their present intra-specific genetic structure. Demo-genetic modelling allows inferring the way past demographic and migration dynamics have determined this structure. Amborella trichopoda is an emblematic relict plant endemic to New Caledonia, widely distributed in the understory of non-ultramafic rainforests. We assessed the influence of the last glacial climates on the demographic history and the paleo-distribution of 12 Amborella populations covering the whole current distribution. We performed coalescent genetic modelling of these dynamics, based on both whole-genome resequencing and microsatellite genotyping data. We found that the two main genetic groups of Amborella were shaped by the divergence of two ancestral populations during the last glacial maximum. From 12,800 years BP, the South ancestral population has expanded 6.3-fold while the size of the North population has remained stable. Recent asymmetric gene flow between the groups further contributed to the phylogeographical pattern. Spatially explicit coalescent modelling allowed us to estimate the location of ancestral populations with good accuracy (< 22 km) and provided indications regarding the mid-elevation pathways that facilitated post-glacial expansion. PMID:28820899