Network structure and influence of the climate change counter-movement

NASA Astrophysics Data System (ADS)

Farrell, Justin

2016-04-01

Anthropogenic climate change represents a global threat to human well-being and ecosystem functioning. Yet despite its importance for science and policy, our understanding of the causes of widespread uncertainty and doubt found among the general public remains limited. The political and social processes driving such doubt and uncertainty are difficult to rigorously analyse, and research has tended to focus on the individual-level, rather than the larger institutions and social networks that produce and disseminate contrarian information. This study presents a new approach by using network science to uncover the institutional and corporate structure of the climate change counter-movement, and machine-learning text analysis to show its influence in the news media and bureaucratic politics. The data include a new social network of all known organizations and individuals promoting contrarian viewpoints, as well as the entirety of all written and verbal texts about climate change from 1993-2013 from every organization, three major news outlets, all US presidents, and every occurrence on the floor of the US Congress. Using network and computational text analysis, I find that the organizational power within the contrarian network, and the magnitude of semantic similarity, are both predicted by ties to elite corporate benefactors.

Reference hydrologic networks II. Using reference hydrologic networks to assess climate-driven changes in streamflow

USGS Publications Warehouse

Burn, Donald H.; Hannaford, Jamie; Hodgkins, Glenn A.; Whitfield, Paul H.; Thorne, Robin; Marsh, Terry

2012-01-01

Reference hydrologic networks (RHNs) can play an important role in monitoring for changes in the hydrological regime related to climate variation and change. Currently, the literature concerning hydrological response to climate variations is complex and confounded by the combinations of many methods of analysis, wide variations in hydrology, and the inclusion of data series that include changes in land use, storage regulation and water use in addition to those of climate. Three case studies that illustrate a variety of approaches to the analysis of data from RHNs are presented and used, together with a summary of studies from the literature, to develop approaches for the investigation of changes in the hydrological regime at a continental or global scale, particularly for international comparison. We present recommendations for an analysis framework and the next steps to advance such an initiative. There is a particular focus on the desirability of establishing standardized procedures and methodologies for both the creation of new national RHNs and the systematic analysis of data derived from a collection of RHNs.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B. J.; van Beek, R. P. H.; Meeks, E.; Klein Goldewijk, K.; Scheidel, W.; van der Velde, Y.; Bierkens, M. F. P.; Wassen, M. J.; Dekker, S. C.

2014-12-01

The Romans were perhaps the most impressive exponents of water resource management in preindustrial times with irrigation and virtual water trade facilitating unprecedented urbanization and socioeconomic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanization and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we find that irrigation and virtual water trade increased Roman resilience to interannual climate variability. However, urbanization arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and eroded its resilience to climate variability in the long term. In addition to improving our understanding of Roman water resource management, our cost-distance-based analysis illuminates how increases in import costs arising from climatic and population pressures are likely to be distributed in the future global virtual water network.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B. J.; van Beek, R. P. H.; Meeks, E.; Klein Goldewijk, K.; Scheidel, W.; van der Velde, Y.; Bierkens, M. F. P.; Wassen, M. J.; Dekker, S. C.

2014-06-01

The Romans were perhaps the most impressive exponents of water resource management in preindustrial times with irrigation and virtual water trade facilitating unprecedented urbanisation and socioeconomic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanisation and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we find that irrigation and virtual water trade increased Roman resilience to climate variability in the short term. However, urbanisation arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and reduced its resilience to climate variability in the long-term. In addition to improving our understanding of Roman water resource management, our cost-distance based analysis illuminates how increases in import costs arising from climatic and population pressures are likely to be distributed in the future global virtual water network.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network.

PubMed

Batllori, Enric; Parisien, Marc-André; Parks, Sean A; Moritz, Max A; Miller, Carol

2017-08-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent-wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México-NAM) to the projected end-of-century climate (2071-2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land-cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (<10%) could be critical for future conservation plans, as they will host climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land-cover types outside the current network of NAM protected areas. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

("un")Doing the Next Generation Science Standards: Climate Change Education Actor-Networks in Oklahoma

ERIC Educational Resources Information Center

Colston, Nicole M.; Ivey, Toni A.

2015-01-01

This exploratory research investigated how science education communities of practice in Oklahoma engage in translations of climate change education (CCE). Applications of actor-network theory to educational policymaking facilitate this analysis of the spaces of prescription and spaces of negotiation that characterize CCE in Oklahoma. Informed by…

Geospatial Analysis Tool Kit for Regional Climate Datasets (GATOR) : An Open-source Tool to Compute Climate Statistic GIS Layers from Argonne Climate Modeling Results

DTIC Science & Technology

2017-08-01

This large repository of climate model results for North America (Wang and Kotamarthi 2013, 2014, 2015) is stored in Network Common Data Form (NetCDF...Network Common Data Form (NetCDF). UCAR/Unidata Program Center, Boulder, CO. Available at: http://www.unidata.ucar.edu/software/netcdf. Accessed on 6/20...emissions diverge from each other regarding fossil fuel use, technology, and other socioeconomic factors. As a result, the estimated emissions for each of

Influence of social ties to environmentalists on public climate change perceptions

NASA Astrophysics Data System (ADS)

Tindall, D. B.; Piggot, Georgia

2015-06-01

An emerging body of research proposes that climate change concern is shaped by one's social ties and cultural milieu. This work aligns with findings in the well-established field of social network analysis, whereby individuals are understood as being embedded in social networks, and network position can be used to predict attitudes. Here we examine whether having ties to environmental movement organization members is correlated with climate change attitudes amongst the general public. We use data from a nationwide survey of the Canadian public to demonstrate that having social ties to environmental organization members increases the likelihood that an individual member of the public has a plan to deal with climate change. These findings reinforce the value of focusing on social context when examining climate change attitudes, and highlight the role that environmental organization members play in mobilizing climate change responses.

Network Connectedness, Sense of Community, and Risk Perception of Climate Change Professionals in the Pacific Islands Region

NASA Astrophysics Data System (ADS)

Corlew, L. K.; Keener, V. W.; Finucane, M.

2013-12-01

The Pacific Regional Integrated Sciences and Assessments (Pacific RISA) Program conducted social network analysis research of climate change professionals (broadly defined) who are from or work in Hawaii and the U.S.-Affiliated Pacific Islands (USAPI) region. This study is supported by the National Oceanic and Atmospheric Administration (NOAA) and the Pacific Islands Climate Science Center (PICSC) to address an identified need for a resource that quantifies the region's collaborative network of climate change professionals, and that supports the further development of cross-regional and inter-sectoral collaborations for future research and adaptation activities. A survey was distributed to nearly 1,200 people who are from and/or work in climate change related fields in the region. The Part One Survey questions (not confidential) created a preferential attachment network by listing major players in Hawaii and the USAPI, with additional open fields to identify important contacts in the greater professional network. Participants (n=340) identified 975 network contacts and frequency of communications (weekly, monthly, seasonally, yearly, at least once ever). Part Two Survey questions (confidential, n=302) explored climate change risk perceptions, Psychological Sense of Community (PSOC), sense of control over climate change impacts, sense of responsibility to act, policy beliefs and preferences regarding climate change actions, concern and optimism scales about specific impacts, and demographic information. Graphical representations of the professional network are being developed for release in September 2013 as a free online tool to promote and assist collaboration building among climate professionals in the region. The graphs are partitioned according to network 'hubs' (high centrality), participant location, and profession to clearly identify network strengths and opportunities for future collaborations across spatial and professional boundaries. For additional analyses, scores are assigned for participant degree centrality, betweenness centrality, and Eigenvector centrality from the Part One Survey, as well as PSOC, control, responsibility, risk perceptions, concern, optimism, and policy preferences from the Part Two Survey. Statistical interaction analyses explore factors motivating connectedness within the network, as well as climate change research and adaptation needs and priorities of participants.

Collaboration and co-production of climate knowledge: lessons from a network on the front-line

NASA Astrophysics Data System (ADS)

Kettle, N.

2016-12-01

The science-practice gap is broadly considered a major barrier to the production and application of decision-relevant science. This study uses a social network analysis, based on 126 interviews, to analyze the roles and network ties among climate scientists, service providers, and decision makers in Alaska. Our research highlights the importance of key actors and significant differences in bonding and bridging ties across roles - structural characteristics that provide a basis for informing recommendations to build adaptive capacity and support the co-production of knowledge. Our findings also illustrate that some individuals in the network engage in multiple roles, suggesting that conceptualizing the science-practice interface as consisting of "producers" and "consumers" oversimplifies how individuals engage in climate science, services, and decision making. This research supports the notion that the development and use of climate information is a networked phenomenon. It also emphasizes the importance of centralized individuals who are capable of engaging in multiple roles for the transition of knowledge action.

Network-based approaches to climate knowledge discovery

NASA Astrophysics Data System (ADS)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

Robustness and Recovery of Lifeline Infrastructure and Ecosystem Networks

NASA Astrophysics Data System (ADS)

Bhatia, U.; Ganguly, A. R.

2015-12-01

Disruptive events, both natural and man-made, can have widespread impacts on both natural systems and lifeline infrastructure networks leading to the loss of biodiversity and essential functionality, respectively. Projected sea-level rise and climate change can further increase the frequency and severity of large-scale floods on urban-coastal megacities. Nevertheless, Failure in infrastructure systems can trigger cascading impacts on dependent ecosystems, and vice-versa. An important consideration in the behavior of the isolated networks and inter-connected networks following disruptive events is their resilience, or the ability of the network to "bounce back" to a pre-disaster state. Conventional risk analysis and subsequent risk management frameworks have focused on identifying the components' vulnerability and strengthening of the isolated components to withstand these disruptions. But high interconnectedness of these systems, and evolving nature of hazards, particularly in the context of climate extremes, make the component level analysis unrealistic. In this study, we discuss the complex network-based resilience framework to understand fragility and recovery strategies for infrastructure systems impacted by climate-related hazards. We extend the proposed framework to assess the response of ecological networks to multiple species loss and design the restoration management framework to identify the most efficient restoration sequence of species, which can potentially lead to disproportionate gains in biodiversity.

Mapping of interconnection of climate risks

NASA Astrophysics Data System (ADS)

Yokohata, Tokuta; Tanaka, Katsumasa; Nishina, Kazuya; Takanashi, Kiyoshi; Emori, Seita; Kiguchi, Masashi; Iseri, Yoshihiko; Honda, Yasushi; Okada, Masashi; Masaki, Yoshimitsu; Yamamoto, Akitomo; Shigemitsu, Masahito; Yoshimori, Masakazu; Sueyoshi, Tetsuo; Iwase, Kenta; Hanasaki, Naota; Ito, Akihiko; Sakurai, Gen; Iizumi, Toshichika; Oki, Taikan

2015-04-01

Anthropogenic climate change possibly causes various impacts on human society and ecosystem. Here, we call possible damages or benefits caused by the future climate change as "climate risks". Many climate risks are closely interconnected with each other by direct cause-effect relationship. In this study, the major climate risks are comprehensively summarized based on the survey of studies in the literature using IPCC AR5 etc, and their cause-effect relationship are visualized by a "network diagram". This research is conducted by the collaboration between the experts of various fields, such as water, energy, agriculture, health, society, and eco-system under the project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). First, the climate risks are classified into 9 categories (water, energy, food, health, disaster, industry, society, ecosystem, and tipping elements). Second, researchers of these fields in our project survey the research articles, and pick up items of climate risks, and possible cause-effect relationship between the risk items. A long list of the climate risks is summarized into ~130, and that of possible cause-effect relationship between the risk items is summarized into ~300, because the network diagram would be illegible if the number of the risk items and cause-effect relationship is too large. Here, we only consider the risks that could occur if climate mitigation policies are not conducted. Finally, the chain of climate risks is visualized by creating a "network diagram" based on a network graph theory (Fruchtman & Reingold algorithm). Through the analysis of network diagram, we find that climate risks at various sectors are closely related. For example, the decrease in the precipitation under the global climate change possibly causes the decrease in river runoff and the decrease in soil moisture, which causes the changes in crop production. The changes in crop production can have an impact on society by changing the food price or food supply. Changes in river runoff can also make an impact on the hydropower efficiency. Comprehensive pictures of climate risks and their interconnections are clearly shown in a straightforward manner by the network diagram. We will have a discussion how our results can be helpful for our society to recognize the climate risk.

Visualization of the chains of risks under global climate change

NASA Astrophysics Data System (ADS)

Yokohata, T.; Nishina, K.; Takahashi, K.; Kiguchi, M.; Iseri, Y.; Sueyoshi, T.; Yoshimori, M.; Iwase, K.; Yamamoto, A.; Shigemitsu, M.; Honda, Y.; Hanasaki, N.; Masaki, Y.; Ito, A.; Iizumi, T.; Sakurai, G.; Okada, M.; Emori, S.; Oki, T.

2014-12-01

Anthropogenic climate change possibly causes various impacts on human society and ecosystem. Here, we call possible damages or benefits caused by the future climate change as "climate risks". Many climate risks are closely interconnected with each other by direct cause-effect relationship. In this study, the major climate risks are comprehensively summarized based on the survey of studies in the literature using IPCC AR5 etc, and their cause-effect relationship are visualized by a "network diagram". This research is conducted by the collaboration between the experts of various fields, such as water, energy, agriculture, health, society, and eco-system under the project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). First, the climate risks are classified into 9 categories (water, energy, food, health, disaster, industry, society, ecosystem, and tipping elements). Second, researchers of these fields in our project survey the research articles, and pick up items of climate risks, and possible cause-effect relationship between the risk items. A long list of the climate risks is summarized into ~130, and that of possible cause-effect relationship between the risk items is summarized into ~300, because the network diagram would be illegible if the number of the risk items and cause-effect relationship is too large. Here, we only consider the risks that could occur if climate mitigation policies are not conducted. Finally, the chain of climate risks is visualized by creating a "network diagram" based on a network graph theory (Fruchtman & Reingold algorithm). Through the analysis of network diagram, we find that climate risks at various sectors are closely related. For example, the decrease in the precipitation under the global climate change possibly causes the decrease in river runoff and the decrease in soil moisture, which causes the changes in crop production. The changes in crop production can have an impact on society by changing the food price or food supply. Changes in river runoff can also make an impact on the hydropower efficiency. Comprehensive pictures of climate risks and their interconnections are clearly shown in a straightforward manner by the network diagram. We will have a discussion how our results can be helpful for our society to recognize the climate risk.

Using social network analysis to evaluate health-related adaptation decision-making in Cambodia.

PubMed

Bowen, Kathryn J; Alexander, Damon; Miller, Fiona; Dany, Va

2014-01-30

Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or 'shadow networks') in the context of climate change adaptation policy and activities. The health governance 'map' in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes.

Corporate funding and ideological polarization about climate change

PubMed Central

Farrell, Justin

2016-01-01

Drawing on large-scale computational data and methods, this research demonstrates how polarization efforts are influenced by a patterned network of political and financial actors. These dynamics, which have been notoriously difficult to quantify, are illustrated here with a computational analysis of climate change politics in the United States. The comprehensive data include all individual and organizational actors in the climate change countermovement (164 organizations), as well as all written and verbal texts produced by this network between 1993–2013 (40,785 texts, more than 39 million words). Two main findings emerge. First, that organizations with corporate funding were more likely to have written and disseminated texts meant to polarize the climate change issue. Second, and more importantly, that corporate funding influences the actual thematic content of these polarization efforts, and the discursive prevalence of that thematic content over time. These findings provide new, and comprehensive, confirmation of dynamics long thought to be at the root of climate change politics and discourse. Beyond the specifics of climate change, this paper has important implications for understanding ideological polarization more generally, and the increasing role of private funding in determining why certain polarizing themes are created and amplified. Lastly, the paper suggests that future studies build on the novel approach taken here that integrates large-scale textual analysis with social networks. PMID:26598653

Corporate funding and ideological polarization about climate change.

PubMed

Farrell, Justin

2016-01-05

Drawing on large-scale computational data and methods, this research demonstrates how polarization efforts are influenced by a patterned network of political and financial actors. These dynamics, which have been notoriously difficult to quantify, are illustrated here with a computational analysis of climate change politics in the United States. The comprehensive data include all individual and organizational actors in the climate change countermovement (164 organizations), as well as all written and verbal texts produced by this network between 1993-2013 (40,785 texts, more than 39 million words). Two main findings emerge. First, that organizations with corporate funding were more likely to have written and disseminated texts meant to polarize the climate change issue. Second, and more importantly, that corporate funding influences the actual thematic content of these polarization efforts, and the discursive prevalence of that thematic content over time. These findings provide new, and comprehensive, confirmation of dynamics long thought to be at the root of climate change politics and discourse. Beyond the specifics of climate change, this paper has important implications for understanding ideological polarization more generally, and the increasing role of private funding in determining why certain polarizing themes are created and amplified. Lastly, the paper suggests that future studies build on the novel approach taken here that integrates large-scale textual analysis with social networks.

Specialization in Plant-Hummingbird Networks Is Associated with Species Richness, Contemporary Precipitation and Quaternary Climate-Change Velocity

PubMed Central

Dalsgaard, Bo; Magård, Else; Fjeldså, Jon; Martín González, Ana M.; Rahbek, Carsten; Olesen, Jens M.; Ollerton, Jeff; Alarcón, Ruben; Cardoso Araujo, Andrea; Cotton, Peter A.; Lara, Carlos; Machado, Caio Graco; Sazima, Ivan; Sazima, Marlies; Timmermann, Allan; Watts, Stella; Sandel, Brody; Sutherland, William J.; Svenning, Jens-Christian

2011-01-01

Large-scale geographical patterns of biotic specialization and the underlying drivers are poorly understood, but it is widely believed that climate plays an important role in determining specialization. As climate-driven range dynamics should diminish local adaptations and favor generalization, one hypothesis is that contemporary biotic specialization is determined by the degree of past climatic instability, primarily Quaternary climate-change velocity. Other prominent hypotheses predict that either contemporary climate or species richness affect biotic specialization. To gain insight into geographical patterns of contemporary biotic specialization and its drivers, we use network analysis to determine the degree of specialization in plant-hummingbird mutualistic networks sampled at 31 localities, spanning a wide range of climate regimes across the Americas. We found greater biotic specialization at lower latitudes, with latitude explaining 20–22% of the spatial variation in plant-hummingbird specialization. Potential drivers of specialization - contemporary climate, Quaternary climate-change velocity, and species richness - had superior explanatory power, together explaining 53–64% of the variation in specialization. Notably, our data provides empirical evidence for the hypothesized roles of species richness, contemporary precipitation and Quaternary climate-change velocity as key predictors of biotic specialization, whereas contemporary temperature and seasonality seem unimportant in determining specialization. These results suggest that both ecological and evolutionary processes at Quaternary time scales can be important in driving large-scale geographical patterns of contemporary biotic specialization, at least for co-evolved systems such as plant-hummingbird networks. PMID:21998716

Inference of directed climate networks: role of instability of causality estimation methods

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Vejmelka, Martin; Paluš, Milan

2013-04-01

Climate data are increasingly analyzed by complex network analysis methods, including graph-theoretical approaches [1]. For such analysis, links between localized nodes of climate network are typically quantified by some statistical measures of dependence (connectivity) between measured variables of interest. To obtain information on the directionality of the interactions in the networks, a wide range of methods exists. These can be broadly divided into linear and nonlinear methods, with some of the latter having the theoretical advantage of being model-free, and principally a generalization of the former [2]. However, as a trade-off, this generality comes together with lower accuracy - in particular if the system was close to linear. In an overall stationary system, this may potentially lead to higher variability in the nonlinear network estimates. Therefore, with the same control of false alarms, this may lead to lower sensitivity for detection of real changes in the network structure. These problems are discussed on the example of daily SAT and SLP data from the NCEP/NCAR reanalysis dataset. We first reduce the dimensionality of data using PCA with VARIMAX rotation to detect several dozens of components that together explain most of the data variability. We further construct directed climate networks applying a selection of most widely used methods - variants of linear Granger causality and conditional mutual information. Finally, we assess the stability of the detected directed climate networks by computing them in sliding time windows. To understand the origin of the observed instabilities and their range, we also apply the same procedure to two types of surrogate data: either with non-stationarity in network structure removed, or imposed in a controlled way. In general, the linear methods show stable results in terms of overall similarity of directed climate networks inferred. For instance, for different decades of SAT data, the Spearman correlation of edge weights in the networks is ~ 0.6. The networks constructed using nonlinear measures were in general less stable both in real data and stationarized surrogates. Interestingly, when the nonlinear method parameters are optimized with respect to temporal stability of the networks, the networks seem to converge close to those detected by linear Granger causality. This provides further evidence for the hypothesis of overall sparsity and weakness of nonlinear coupling in climate networks on this spatial and temporal scale [3] and sufficient support for the use of linear methods in this context, unless specific clearly detectable nonlinear phenomena are targeted. Acknowledgement: This study is supported by the Czech Science Foundation, Project No. P103/11/J068. [1] Boccaletti, S.; Latora, V.; Moreno, Y.; Chavez, M. & Hwang, D. U.: Complex networks: Structure and dynamics, Physics Reports, 2006, 424, 175-308 [2] Barnett, L.; Barrett, A. B. & Seth, A. K.: Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables, Physical Review Letters, 2009, 103, 238701 [3] Hlinka, J.; Hartman, D.; Vejmelka, M.; Novotná, D.; Paluš, M.: Non-linear dependence and teleconnections in climate data: sources, relevance, nonstationarity, submitted preprint (http://arxiv.org/abs/1211.6688)

Smooth information flow in temperature climate network reflects mass transport

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Jajcay, Nikola; Hartman, David; Paluš, Milan

2017-03-01

A directed climate network is constructed by Granger causality analysis of air temperature time series from a regular grid covering the whole Earth. Using winner-takes-all network thresholding approach, a structure of a smooth information flow is revealed, hidden to previous studies. The relevance of this observation is confirmed by comparison with the air mass transfer defined by the wind field. Their close relation illustrates that although the information transferred due to the causal influence is not a physical quantity, the information transfer is tied to the transfer of mass and energy.

A Framework for Bridging Scientists, Knowledge Brokers and Local Decision Makers in State-level Climate Assessments

NASA Astrophysics Data System (ADS)

Galford, G. L.; Nash, J. L.

2016-12-01

Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now develop assessments (SCAs) to provide relevant, actionable information to state and local authorities. These assessments generate new or additional primary information, build networks and inform stakeholders. Based on our experience in the Vermont Climate Assessment (VCA), we present a SCA framework to engage local decision makers, using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis, and writing. Knowledge brokers bridged the scientific and stakeholder communities, providing a two-way flow of information by capitalizing on their existing networks. Rich citizen records of climate and climate change impacts associated a human voice, a memorable story, or personal observation with a climate record, improving climate information salience. This engagement process that created salient climate information perceived as credible and legitimate by local and state decision makers. We present this framework as an effective structure for SCAs to foster interaction among scientists, knowledge brokers and stakeholders. We include a qualitative impact evaluation and lessons learned for future SCAs.

Using Social Network Analysis to Evaluate Health-Related Adaptation Decision-Making in Cambodia

PubMed Central

Bowen, Kathryn J.; Alexander, Damon; Miller, Fiona; Dany, Va

2014-01-01

Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or ‘shadow networks’) in the context of climate change adaptation policy and activities. The health governance ‘map’ in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes. PMID:24487452

Paleoclimate networks: a concept meeting central challenges in the reconstruction of paleoclimate dynamics

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Goswami, Bedartha; Marwan, Norbert; Breitenbach, Sebastian; Kurths, Jürgen

2013-04-01

Statistical analysis of dependencies amongst paleoclimate data helps to infer on the climatic processes they reflect. Three key challenges have to be addressed, however: the datasets are heterogeneous in time (i) and space (ii), and furthermore time itself is a variable that needs to be reconstructed, which (iii) introduces additional uncertainties. To address these issues in a flexible way we developed the paleoclimate network framework, inspired by the increasing application of complex networks in climate research. Nodes in the paleoclimate network represent a paleoclimate archive, and an associated time series. Links between these nodes are assigned, if these time series are significantly similar. Therefore, the base of the paleoclimate network is formed by linear and nonlinear estimators for Pearson correlation, mutual information and event synchronization, which quantify similarity from irregularly sampled time series. Age uncertainties are propagated into the final network analysis using time series ensembles which reflect the uncertainty. We discuss how spatial heterogeneity influences the results obtained from network measures, and demonstrate the power of the approach by inferring teleconnection variability of the Asian summer monsoon for the past 1000 years.

2014 Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Conference Report

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

Williams, Dean N.

2015-01-27

The climate and weather data science community met December 9–11, 2014, in Livermore, California, for the fourth annual Earth System Grid Federation (ESGF) and Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Conference, hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UVCDATremain global collaborations committed to developing a new generation of open-source software infrastructure that provides distributed access and analysis to simulated and observed data from the climate and weather communities.more » The tools and infrastructure created under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change. In addition, the F2F conference fosters a stronger climate and weather data science community and facilitates a stronger federated software infrastructure. The 2014 F2F conference detailed the progress of ESGF, UV-CDAT, and other community efforts over the year and sets new priorities and requirements for existing and impending national and international community projects, such as the Coupled Model Intercomparison Project Phase Six. Specifically discussed at the conference were project capabilities and enhancements needs for data distribution, analysis, visualization, hardware and network infrastructure, standards, and resources.« less

Identification of tipping elements of the Indian Summer Monsoon using climate network approach

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Surovyatkina, Elena; Kurths, Jurgen

2015-04-01

Spatial and temporal variability of the rainfall is a vital question for more than one billion of people inhabiting the Indian subcontinent. Indian Summer Monsoon (ISM) rainfall is crucial for India's economy, social welfare, and environment and large efforts are being put into predicting the Indian Summer Monsoon. For predictability of the ISM, it is crucial to identify tipping elements - regions over the Indian subcontinent which play a key role in the spatial organization of the Indian monsoon system. Here, we use climate network approach for identification of such tipping elements of the ISM. First, we build climate networks of the extreme rainfall, surface air temperature and pressure over the Indian subcontinent for pre-monsoon, monsoon and post-monsoon seasons. We construct network of extreme rainfall event using observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). For the network of surface air temperature and pressure fields, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). Second, we filter out data by coarse-graining the network through network measures, and identify tipping regions of the ISM. Finally, we compare obtained results of the network analysis with surface wind fields and show that occurrence of the tipping elements is mostly caused by monsoonal wind circulation, migration of the Intertropical Convergence Zone (ITCZ) and Westerlies. We conclude that climate network approach enables to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to identify tipping regions of the ISM. Obtained tipping elements deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Robust nonlinear canonical correlation analysis: application to seasonal climate forecasting

NASA Astrophysics Data System (ADS)

Cannon, A. J.; Hsieh, W. W.

2008-02-01

Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pearson product-moment correlation in the double-barreled network is replaced by the biweight midcorrelation, and the mean squared error (mse) in the inverse mapping networks can be replaced by the mean absolute error (mae). Robust variants of NLCCA are demonstrated on a synthetic dataset and are used to forecast sea surface temperatures in the tropical Pacific Ocean based on the sea level pressure field. Results suggest that adoption of the biweight midcorrelation can lead to improved performance, especially when a strong, common event exists in both predictor/predictand datasets. Replacing the mse by the mae leads to improved performance on the synthetic dataset, but not on the climate dataset except at the longest lead time, which suggests that the appropriate cost function for the inverse mapping networks is more problem dependent.

Evaluating a European knowledge hub on climate change in agriculture: Are we building a better connected community?

PubMed

Saetnan, Eli Rudinow; Kipling, Richard Philip

In order to maintain food security and sustainability of production under climate change, interdisciplinary and international collaboration in research is essential. In the EU, knowledge hubs are important funding instruments for the development of an interconnected European Research Area. Here, network analysis was used to assess whether the pilot knowledge hub MACSUR has affected interdisciplinary collaboration, using co-authorship of peer reviewed articles as a measure of collaboration. The broad community of all authors identified as active in the field of agriculture and climate change was increasingly well connected over the period studied. Between knowledge hub members, changes in network parameters suggest an increase in collaborative interaction beyond that expected due to network growth, and greater than that found in the broader community. Given that interdisciplinary networks often take several years to have an impact on research outputs, these changes within the relatively new MACSUR community provide evidence that the knowledge hub structure has been effective in stimulating collaboration. However, analysis showed that knowledge hub partners were initially well-connected, suggesting that the initiative may have gathered together researchers with particular resources or inclinations towards collaborative working. Long term, consistent funding and ongoing reflection to improve networking structures may be necessary to sustain the early positive signs from MACSUR, to extend its success to a wider community of researchers, or to repeat it in less connected fields of science. Tackling complex challenges such as climate change will require research structures that can effectively support and utilise the diversity of talents beyond the already well-connected core of scientists at major research institutes. But network research shows that this core, well-connected group are vital brokers in achieving wider integration.

Network access to PCDS (SPAN, ESN, SESNET, ARPANET)

NASA Technical Reports Server (NTRS)

Green, J.

1986-01-01

One of the major goals of the National Space Science Data Center is to increase access to NASA data systems by enhancing networking activities. The activities are centered around three basic networking systems: the Space Physics Analysis Network (SPAN); the Earth Science Network (ESN); and the NASA Packet Switched System (NPSS). Each system is described, linkages among systems are explained, and future plans are announced. The inclusion of several new climate nodes on SPAN or ESN are also mentioned. Presently, the Pilot Climate Data System is accessible through SPAN and will be accessible through NPSS by summer and ESN by the end of 1986. Ambitious plans for implementation are underway. The implementation of these plans will represent a major advance in the utilization and accessibility of data worldwide.

Climate impact on spreading of airborne infectious diseases. Complex network based modeling of climate influences on influenza like illnesses

NASA Astrophysics Data System (ADS)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-06-01

In this study we combined a wide range of data sets to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human. The basis is a complex network whose structures are inspired by global air traffic data (from openflights.org) containing information about airports, airport locations, direct flight connections and airplane types. Disease spreading inside every node is realized with a Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. Disease transmission rates in our model are depending on the climate environment and therefore vary in time and from node to node. To implement the correlation between water vapor pressure and influenza transmission rate [J. Shaman, M. Kohn, Proc. Natl. Acad. Sci. 106, 3243 (2009)], we use global available climate reanalysis data (WATCH-Forcing-Data-ERA-Interim, WFDEI). During our sensitivity analysis we found that disease spreading dynamics are strongly depending on network properties, the climatic environment of the epidemic outbreak location, and the season during the year in which the outbreak is happening.

Climate and change: simulating flooding impacts on urban transport network

NASA Astrophysics Data System (ADS)

Pregnolato, Maria; Ford, Alistair; Dawson, Richard

2015-04-01

National-scale climate projections indicate that in the future there will be hotter and drier summers, warmer and wetter winters, together with rising sea levels. The frequency of extreme weather events is expected to increase, causing severe damage to the built environment and disruption of infrastructures (Dawson, 2007), whilst population growth and changed demographics are placing new demands on urban infrastructure. It is therefore essential to ensure infrastructure networks are robust to these changes. This research addresses these challenges by focussing on the development of probabilistic tools for managing risk by modelling urban transport networks within the context of extreme weather events. This paper presents a methodology to investigate the impacts of extreme weather events on urban environment, in particular infrastructure networks, through a combination of climate simulations and spatial representations. By overlaying spatial data on hazard thresholds from a flood model and a flood safety function, mitigated by potential adaptation strategies, different levels of disruption to commuting journeys on road networks are evaluated. The method follows the Catastrophe Modelling approach and it consists of a spatial model, combining deterministic loss models and probabilistic risk assessment techniques. It can be applied to present conditions as well as future uncertain scenarios, allowing the examination of the impacts alongside socio-economic and climate changes. The hazard is determined by simulating free surface water flooding, with the software CityCAT (Glenis et al., 2013). The outputs are overlapped to the spatial locations of a simple network model in GIS, which uses journey-to-work (JTW) observations, supplemented with speed and capacity information. To calculate the disruptive effect of flooding on transport networks, a function relating water depth to safe driving car speed has been developed by combining data from experimental reports (Morris et al., 2011) safety literature (Great Britain Department for Transport, 1999), analysis of videos of cars driving through floodwater, and expert judgement. A preliminary analysis has been run in the Tyne & Wear (in North-East England) region to demonstrate how the analysis can be used to assess the disruptions for commuter journeys due to flooding and will be demonstrated in this paper. The research will also investigate the effectiveness of adaptation strategies for extreme rainfall events, such as permeable surfaces and roof storages for buildings. Multiple scenarios (from the every-day-rainfall to the extreme weather phenomena) will be modelled, with different rainfall rates, rainfall durations and return periods. The comparison between the scenarios in which no interventions are adopted and those improved by one of the adaptation option will be compared to determine the cost-effectiveness of the solution considered. Integrating spatial analysis of transport use with an urban flood model and flood safety function enables the investigation of the impacts of extreme weather on infrastructure networks. Further work will develop the analysis in a number of ways (i) testing a range of flood events with different severity and frequency, (ii) exploration of the influence of climate and socio-economic change (iii) analysis of multiple hazard events and (iv) consideration of cascading disruption across different infrastructure networks.

Vulnerability of dynamic genetic conservation units of forest trees in Europe to climate change.

PubMed

Schueler, Silvio; Falk, Wolfgang; Koskela, Jarkko; Lefèvre, François; Bozzano, Michele; Hubert, Jason; Kraigher, Hojka; Longauer, Roman; Olrik, Ditte C

2014-05-01

A transnational network of genetic conservation units for forest trees was recently documented in Europe aiming at the conservation of evolutionary processes and the adaptive potential of natural or man-made tree populations. In this study, we quantified the vulnerability of individual conservation units and the whole network to climate change using climate favourability models and the estimated velocity of climate change. Compared to the overall climate niche of the analysed target species populations at the warm and dry end of the species niche are underrepresented in the network. However, by 2100, target species in 33-65 % of conservation units, mostly located in southern Europe, will be at the limit or outside the species' current climatic niche as demonstrated by favourabilities below required model sensitivities of 95%. The highest average decrease in favourabilities throughout the network can be expected for coniferous trees although they are mainly occurring within units in mountainous landscapes for which we estimated lower velocities of change. Generally, the species-specific estimates of favourabilities showed only low correlations to the velocity of climate change in individual units, indicating that both vulnerability measures should be considered for climate risk analysis. The variation in favourabilities among target species within the same conservation units is expected to increase with climate change and will likely require a prioritization among co-occurring species. The present results suggest that there is a strong need to intensify monitoring efforts and to develop additional conservation measures for populations in the most vulnerable units. Also, our results call for continued transnational actions for genetic conservation of European forest trees, including the establishment of dynamic conservation populations outside the current species distribution ranges within European assisted migration schemes. © 2013 John Wiley & Sons Ltd.

Network approach to patterns in stratocumulus clouds

NASA Astrophysics Data System (ADS)

Glassmeier, Franziska; Feingold, Graham

2017-10-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds.

PubMed

Glassmeier, Franziska; Feingold, Graham

2017-10-03

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.

Network approach to patterns in stratocumulus clouds

PubMed Central

Feingold, Graham

2017-01-01

Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth’s climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis’s Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav–Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes. PMID:28904097

Is U.S. climatic diversity well represented within the existing federal protection network?

PubMed

Batllori, Enric; Miller, Carol; Parisien, Marc-Andre; Parks, Sean A; Moritz, Max A

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans. The conterminous United States of America (CONUS) has an extensive system of protected areas managed by federal agencies, but a comprehensive assessment of how this network represents CONUS climate is lacking. We present a quantitative classification of the climate space that is independent from the geographic locations to evaluate the climatic representation of the existing protected area network. We use this classification to evaluate the coverage of each agency's jurisdiction and to identify current conservation deficits. Our findings reveal that the existing network poorly represents CONUS climatic diversity. Although rare climates are generally well represented by the network, the most common climates are particularly underrepresented. Overall, 83% of the area of the CONUS corresponds to climates underrepresented by the network. The addition of some currently unprotected federal lands to the network would enhance the coverage of CONUS climates. However, to fully palliate current conservation deficits, large-scale private-land conservation initiatives will be critical.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen

2015-11-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.

Macroecology of Australian Tall Eucalypt Forests: Baseline Data from a Continental-Scale Permanent Plot Network

PubMed Central

Wood, Sam W.; Prior, Lynda D.; Stephens, Helen C.; Bowman, David M. J. S.

2015-01-01

Tracking the response of forest ecosystems to climate change demands large (≥1 ha) monitoring plots that are repeatedly measured over long time frames and arranged across macro-ecological gradients. Continental scale networks of permanent forest plots have identified links between climate and carbon fluxes by monitoring trends in tree growth, mortality and recruitment. The relationship between tree growth and climate in Australia has been recently articulated through analysis of data from smaller forest plots, but conclusions were limited by (a) absence of data on recruitment and mortality, (b) exclusion of non-eucalypt species, and (c) lack of knowledge of stand age or disturbance histories. To remedy these gaps we established the Ausplots Forest Monitoring Network: a continental scale network of 48 1 ha permanent plots in highly productive tall eucalypt forests in the mature growth stage. These plots are distributed across cool temperate, Mediterranean, subtropical and tropical climates (mean annual precipitation 850 to 1900 mm per year; mean annual temperature 6 to 21°C). Aboveground carbon stocks (AGC) in these forests are dominated by eucalypts (90% of AGC) whilst non-eucalypts in the understorey dominated species diversity and tree abundance (84% of species; 60% of stems). Aboveground carbon stocks were negatively related to mean annual temperature, with forests at the warm end of the temperature range storing approximately half the amount of carbon as forests at the cool end of the temperature range. This may reflect thermal constraints on tree growth detected through other plot networks and physiological studies. Through common protocols and careful sampling design, the Ausplots Forest Monitoring Network will facilitate the integration of tall eucalypt forests into established global forest monitoring initiatives. In the context of projections of rapidly warming and drying climates in Australia, this plot network will enable detection of links between climate and growth, mortality and carbon dynamics of eucalypt forests. PMID:26368919

A climate trend analysis of Uganda

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies observed changes in rainfall and temperature in Uganda, based on an analysis of a quality-controlled, long time series of station observations throughout Uganda. Extending recent trends forward, it also provides a current and near-future context for understanding the actual nature of climate change impacts in the country, and a basis for identifying climate adaptations that may protect and improve the country's food security.

Multi-profile analysis of soil moisture within the U.S. Climate Reference Network

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are crucial for hydrologic modeling and agricultural decision-support efforts. These measurements are also pivotal for long-term inquiries regarding the impacts of climate change and the resulting droughts over large spatial and temporal scales. However, it has only been t...

Toward a Continental-Scale Mesonet: USDA National Resources Conservation Service SCAN and SNOTEL System

NASA Astrophysics Data System (ADS)

Schaffer, G.; Marks, D.

2004-12-01

Since 1978 snow deposition and SWE in the inter-mountain western US have been monitored by the NRCS SNOTEL (SNOwpack TELemetry) system. This revolutionary network utilizes Meteorburst technology to telemeter data back to a central location in near real-time. With a pilot program starting in 1991, NRCS introduced SCAN (Soil Climate and Analysis Network) adding a focus on soil moisture and climate in regions outside the intermountain west. In the mid-1990's SNOTEL sites began to be augmented to match the full climate instrumentation (air temperature, humidity, solar radiation, wind, and soil moisture and temperature in addition to precipitation, snow depth and SWE) of the SCAN system. At present there are nearly 700 SNOTEL sites in 12 states in the western US and Alaska, and over 100 SCAN sites in 40 states, Puerto Rico, and several foreign countries. Though SNOTEL was originally a western snow-monitoring network, differences between SCAN and SNOTEL have largely disappeared. The combined SNOTEL/SCAN system provides a continental-scale mesonet to support river basin to continental scale hydro-climatic analysis. The system is flexible and based on off-the-shelf data recording technology, allowing instrumentation, sampling and averaging intervals to be specified by site conditions, issues, or scientific questions. Because of the NRCS data management structure, all sites have active telemetery and provide near real-time access to data through the internet. An ongoing research program is directed to improved instrumentation for measuring precipitation, snow depth and SWE, and soil moisture and temperature. Future directions include expansion of the network to be more comprehensive, and to develop focused monitoring efforts to more effectively observe elevational and regional gradients, and to capture high intensity hydro-climatic events such as potential flooding from convective storms and rain-on-snow.

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

PubMed

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

2017-11-01

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

Climate Observing Systems: Where are we and where do we need to be in the future

NASA Astrophysics Data System (ADS)

Baker, B.; Diamond, H. J.

2017-12-01

Climate research and monitoring requires an observational strategy that blends long-term, carefully calibrated measurements as well as short-term, focused process studies. The operation and implementation of operational climate observing networks and the provision of related climate services, both have a significant role to play in assisting the development of national climate adaptation policies and in facilitating national economic development. Climate observing systems will require a strong research element for a long time to come. This requires improved observations of the state variables and the ability to set them in a coherent physical (as well as a chemical and biological) framework with models. Climate research and monitoring requires an integrated strategy of land/ocean/atmosphere observations, including both in situ and remote sensing platforms, and modeling and analysis. It is clear that we still need more research and analysis on climate processes, sampling strategies, and processing algorithms.

Optimal Interpolation scheme to generate reference crop evapotranspiration

NASA Astrophysics Data System (ADS)

Tomas-Burguera, Miquel; Beguería, Santiago; Vicente-Serrano, Sergio; Maneta, Marco

2018-05-01

We used an Optimal Interpolation (OI) scheme to generate a reference crop evapotranspiration (ETo) grid, forcing meteorological variables, and their respective error variance in the Iberian Peninsula for the period 1989-2011. To perform the OI we used observational data from the Spanish Meteorological Agency (AEMET) and outputs from a physically-based climate model. To compute ETo we used five OI schemes to generate grids for the five observed climate variables necessary to compute ETo using the FAO-recommended form of the Penman-Monteith equation (FAO-PM). The granularity of the resulting grids are less sensitive to variations in the density and distribution of the observational network than those generated by other interpolation methods. This is because our implementation of the OI method uses a physically-based climate model as prior background information about the spatial distribution of the climatic variables, which is critical for under-observed regions. This provides temporal consistency in the spatial variability of the climatic fields. We also show that increases in the density and improvements in the distribution of the observational network reduces substantially the uncertainty of the climatic and ETo estimates. Finally, a sensitivity analysis of observational uncertainties and network densification suggests the existence of a trade-off between quantity and quality of observations.

Constructing regional climate networks in the Amazonia during recent drought events.

PubMed

Guo, Heng; Ramos, Antônio M T; Macau, Elbert E N; Zou, Yong; Guan, Shuguang

2017-01-01

Climate networks are powerful approaches to disclose tele-connections in climate systems and to predict severe climate events. Here we construct regional climate networks from precipitation data in the Amazonian region and focus on network properties under the recent drought events in 2005 and 2010. Both the networks of the entire Amazon region and the extreme networks resulted from locations severely affected by drought events suggest that network characteristics show slight difference between the two drought events. Based on network degrees of extreme drought events and that without drought conditions, we identify regions of interest that are correlated to longer expected drought period length. Moreover, we show that the spatial correlation length to the regions of interest decayed much faster in 2010 than in 2005, which is because of the dual roles played by both the Pacific and Atlantic oceans. The results suggest that hub nodes in the regional climate network of Amazonia have fewer long-range connections when more severe drought conditions appeared in 2010 than that in 2005.

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.

Analysis of the structure of climate networks under El Niño and La Niña conditions

NASA Astrophysics Data System (ADS)

Graciosa, Juan Carlos; Pastor, Marissa

The El Niño-Southern Oscillation (ENSO) is the most important driver of natural climate variability and is characterized by anomalies in the sea surface temperatures (SST) over the tropical Pacific ocean. It has three phases: neutral, a warming phase or El Niño, and a cooling phase called La Niña. In this research, we modeled the climate under the three phases as a network and characterized its properties. We utilized the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) daily surface temperature reanalysis data from January 1950 to December 2016. A network associated to a month was created using the temperature spanning from the previous month to the succeeding month, for a total of three months worth of data for each network. Each site of the included data was a potential node in the network and the existence of links were determined by the strength of their relationship, which was based on mutual information. Interestingly, we found that climate networks exhibit small-world properties and these are found to be more prominent from October to April, coinciding with observations that El Niño occurrences peak from December to March. During these months, the temperature of a relatively large part of the Pacific ocean and its surrounding areas increase and the anomaly values become synchronized. This synchronization in the temperature anomalies forms links around the Pacific, increasing the clustering in the region and in effect, that of the entire network.

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

USDA-ARS?s Scientific Manuscript database

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

On the Role of Hyper-arid Regions within the Virtual Water Trade Network

NASA Astrophysics Data System (ADS)

Aggrey, James; Alshamsi, Aamena; Molini, Annalisa

2016-04-01

Climate change, economic development, and population growth are bound to increasingly impact global water resources, posing a significant threat to the sustainable development of arid regions, where water consumption highly exceeds the natural carrying capacity, population growth rate is high, and climate variability is going to impact both water consumption and availability. Virtual Water Trade (VWT) - i.e. the international trade network of water-intensive products - has been proposed as a possible solution to optimize the allocation of water resources on the global scale. By increasing food availability and lowering food prices it may in fact help the rapid development of water-scarce regions. The structure of the VWT network has been analyzed by a number of authors both in connection with trade policies, socioeconomic constrains and agricultural efficiency. However a systematic analysis of the structure and the dynamics of the VWT network conditional to aridity, climatic forcing and energy availability, is still missing. Our goal is hence to analyze the role of arid and hyper-arid regions within the VWN under diverse climatic, demographic, and energy constraints with an aim to contribute to the ongoing Energy-Water-Food nexus discussion. In particular, we focus on the hyper-arid lands of the Arabian Peninsula, the role they play in the global network and the assessment of their specific criticalities, as reflected in the VWN resilience.

Missing Rings in Pinus halepensis – The Missing Link to Relate the Tree-Ring Record to Extreme Climatic Events

PubMed Central

Novak, Klemen; de Luis, Martin; Saz, Miguel A.; Longares, Luis A.; Serrano-Notivoli, Roberto; Raventós, Josep; Čufar, Katarina; Gričar, Jožica; Di Filippo, Alfredo; Piovesan, Gianluca; Rathgeber, Cyrille B. K.; Papadopoulos, Andreas; Smith, Kevin T.

2016-01-01

Climate predictions for the Mediterranean Basin include increased temperatures, decreased precipitation, and increased frequency of extreme climatic events (ECE). These conditions are associated with decreased tree growth and increased vulnerability to pests and diseases. The anatomy of tree rings responds to these environmental conditions. Quantitatively, the width of a tree ring is largely determined by the rate and duration of cell division by the vascular cambium. In the Mediterranean climate, this division may occur throughout almost the entire year. Alternatively, cell division may cease during relatively cool and dry winters, only to resume in the same calendar year with milder temperatures and increased availability of water. Under particularly adverse conditions, no xylem may be produced in parts of the stem, resulting in a missing ring (MR). A dendrochronological network of Pinus halepensis was used to determine the relationship of MR to ECE. The network consisted of 113 sites, 1,509 trees, 2,593 cores, and 225,428 tree rings throughout the distribution range of the species. A total of 4,150 MR were identified. Binomial logistic regression analysis determined that MR frequency increased with increased cambial age. Spatial analysis indicated that the geographic areas of south-eastern Spain and northern Algeria contained the greatest frequency of MR. Dendroclimatic regression analysis indicated a non-linear relationship of MR to total monthly precipitation and mean temperature. MR are strongly associated with the combination of monthly mean temperature from previous October till current February and total precipitation from previous September till current May. They are likely to occur with total precipitation lower than 50 mm and temperatures higher than 5°C. This conclusion is global and can be applied to every site across the distribution area. Rather than simply being a complication for dendrochronology, MR formation is a fundamental response of trees to adverse environmental conditions. The demonstrated relationship of MR formation to ECE across this dendrochronological network in the Mediterranean basin shows the potential of MR analysis to reconstruct the history of past climatic extremes and to predict future forest dynamics in a changing climate. PMID:27303421

Missing Rings in Pinus halepensis - The Missing Link to Relate the Tree-Ring Record to Extreme Climatic Events.

PubMed

Novak, Klemen; de Luis, Martin; Saz, Miguel A; Longares, Luis A; Serrano-Notivoli, Roberto; Raventós, Josep; Čufar, Katarina; Gričar, Jožica; Di Filippo, Alfredo; Piovesan, Gianluca; Rathgeber, Cyrille B K; Papadopoulos, Andreas; Smith, Kevin T

2016-01-01

Climate predictions for the Mediterranean Basin include increased temperatures, decreased precipitation, and increased frequency of extreme climatic events (ECE). These conditions are associated with decreased tree growth and increased vulnerability to pests and diseases. The anatomy of tree rings responds to these environmental conditions. Quantitatively, the width of a tree ring is largely determined by the rate and duration of cell division by the vascular cambium. In the Mediterranean climate, this division may occur throughout almost the entire year. Alternatively, cell division may cease during relatively cool and dry winters, only to resume in the same calendar year with milder temperatures and increased availability of water. Under particularly adverse conditions, no xylem may be produced in parts of the stem, resulting in a missing ring (MR). A dendrochronological network of Pinus halepensis was used to determine the relationship of MR to ECE. The network consisted of 113 sites, 1,509 trees, 2,593 cores, and 225,428 tree rings throughout the distribution range of the species. A total of 4,150 MR were identified. Binomial logistic regression analysis determined that MR frequency increased with increased cambial age. Spatial analysis indicated that the geographic areas of south-eastern Spain and northern Algeria contained the greatest frequency of MR. Dendroclimatic regression analysis indicated a non-linear relationship of MR to total monthly precipitation and mean temperature. MR are strongly associated with the combination of monthly mean temperature from previous October till current February and total precipitation from previous September till current May. They are likely to occur with total precipitation lower than 50 mm and temperatures higher than 5°C. This conclusion is global and can be applied to every site across the distribution area. Rather than simply being a complication for dendrochronology, MR formation is a fundamental response of trees to adverse environmental conditions. The demonstrated relationship of MR formation to ECE across this dendrochronological network in the Mediterranean basin shows the potential of MR analysis to reconstruct the history of past climatic extremes and to predict future forest dynamics in a changing climate.

Climate network analysis of regional precipitation extremes: The true story told by event synchronization

NASA Astrophysics Data System (ADS)

Odenweller, Adrian; Donner, Reik V.

2017-04-01

Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two events to be considered potentially related. Both measures are then used to generate climate networks from parts of the satellite-based TRMM precipitation data set at daily resolution covering the Indian and East Asian monsoon domains, respectively, thereby reanalysing previously published results. The obtained spatial patterns of degree densities and local clustering coefficients exhibit marked differences between both similarity measures. Specifically, we demonstrate that there exists a strong relationship between the fraction of extremes occurring at subsequent days and the degree density in the event synchronization based networks, suggesting that the spatial patterns obtained using this approach are strongly affected by the presence of serial dependencies between events. Given that a manual selection of the maximally tolerable delay between two events can be guided by a priori climatological knowledge and even used for systematic testing of different hypotheses on climatic processes underlying the emergence of spatio-temporal patterns of extreme precipitation, our results provide evidence that event coincidence rates are a more appropriate statistical characteristic for similarity assessment and network construction for climate extremes, while results based on event synchronization need to be interpreted with great caution.

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

USGS Publications Warehouse

Kittel, T.G.F.; Rosenbloom, N.A.; Royle, J. Andrew; Daly, Christopher; Gibson, W.P.; Fisher, H.H.; Thornton, P.; Yates, D.N.; Aulenbach, S.; Kaufman, C.; McKeown, R.; Bachelet, D.; Schimel, D.S.; Neilson, R.; Lenihan, J.; Drapek, R.; Ojima, D.S.; Parton, W.J.; Melillo, J.M.; Kicklighter, D.W.; Tian, H.; McGuire, A.D.; Sykes, M.T.; Smith, B.; Cowling, S.; Hickler, T.; Prentice, I.C.; Running, S.; Hibbard, K.A.; Post, W.M.; King, A.W.; Smith, T.; Rizzo, B.; Woodward, F.I.

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895-1993 on a 0.5?? latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers. ?? Inter-Research 2004.

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

From brain to earth and climate systems: small-world interaction networks or not?

PubMed

Bialonski, Stephan; Horstmann, Marie-Therese; Lehnertz, Klaus

2010-03-01

We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.

Landscape Conservation Cooperatives: Creating a Collaborative Conservation Vision in the Face of Climate Change Uncertainty

NASA Astrophysics Data System (ADS)

Athearn, N.; Schlafmann, D.

2015-12-01

The 22 Landscape Conservation Cooperatives (LCCs) form a "network of networks," each defined by the characteristics of its ecoregion and its unique community of conservation managers, practitioners, and scientists. As self-directed partnerships, LCCs are strongly influenced not only by the landscape but by the evolving cultures and values that define the multi-faceted relationships between people and place. LCCs maintain an ecologically connected network across these diverse landscapes by transcending borders and leveraging resources. Natural resource managers are challenged to make decisions in the face of multiple uncertainties, and several partners across the network have recognized that climate change is one important uncertainty that spans boundaries - both across the conservation community and beyond. The impacts of climate change across the LCC Network are likely to be as diverse as the network itself - manifesting as, for example, sea level rise, ocean acidification, loss of sea ice, and shifts in climate patterns and timing - but synergies are being leveraged within and between LCCs and national climate-focused programs to systematically address the needs of the network to support a collaborative conservation vision that addresses multiple landscape-scale stressors in the face of climate uncertainties. This vision is being achieved by leveraging the convening power of the LCCs and collaborating with DOI Climate Science Centers and others. Selected case studies will demonstrate how the network finds strength in its differences, but also reveals powerful collaborative opportunities through integrated science, shared conservation strategies, and strategic approaches for translating targeted science to conservation action. These examples exemplify past successes as well as ongoing efforts as the network continues to bring about effective application of climate science to achieve conservation outcomes across the LCC Network in an uncertain future climate.

Percolation Features on Climate Network under Attacks of El Niño Events

NASA Astrophysics Data System (ADS)

Lu, Z.

2015-12-01

Percolation theory under different attacks is one of the main research areas in complex networks but never be applied to investigate climate network. In this study, for the first time we construct a climate network of surface air temperature field to analyze its percolation features. Here, we regard El Niño event as a kind of naturally attacks generated from Pacific Ocean to attack its upper climate network. We find that El Niño event leads an abrupt percolation phase transition to the climate network which makes it splitting and unstable suddenly. Comparing the results of the climate network under three different forms of attacks, including most connected attack (MA), localized attack (LA) and random attack (RA) respectively, it is found that both MA and LA lead first-order transition and RA leads second-order transition to the climate network. Furthermore, we find that most real attacks consist of all these three forms of attacks. With El Niño event emerging, the ratios of LA and MA increase and dominate the style of attack while RA decreasing. It means the percolation phase transition due to El Niño events is close to first-order transition mostly affected by LA and MA. Our research may help us further understand two questions from perspective of percolation on network: (1) Why not all warming in Pacific Ocean but El Niño events could affect the climate. (2) Why the climate affected by El Niño events changes abruptly.

New solutions for climate network visualization

NASA Astrophysics Data System (ADS)

Nocke, Thomas; Buschmann, Stefan; Donges, Jonathan F.; Marwan, Norbert

2016-04-01

An increasing amount of climate and climate impact research methods deals with geo-referenced networks, including energy, trade, supply-chain, disease dissemination and climatic tele-connection networks. At the same time, the size and complexity of these networks increases, resulting in networks of more than hundred thousand or even millions of edges, which are often temporally evolving, have additional data at nodes and edges, and can consist of multiple layers even in real 3D. This gives challenges to both the static representation and the interactive exploration of these networks, first of all avoiding edge clutter ("edge spagetti") and allowing interactivity even for unfiltered networks. Within this presentation, we illustrate potential solutions to these challenges. Therefore, we give a glimpse on a questionnaire performed with climate and complex system scientists with respect to their network visualization requirements, and on a review of available state-of-the-art visualization techniques and tools for this purpose (see as well Nocke et al., 2015). In the main part, we present alternative visualization solutions for several use cases (global, regional, and multi-layered climate networks) including alternative geographic projections, edge bundling, and 3-D network support (based on CGV and GTX tools), and implementation details to reach interactive frame rates. References: Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, and C. Tominski: Review: Visual analytics of climate networks, Nonlinear Processes in Geophysics, 22, 545-570, doi:10.5194/npg-22-545-2015, 2015

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Stakeholders' participatory diagnosis of climate change impacts on subsistence agriculture in Sikkim, India, for identifying adaptation strategies

NASA Astrophysics Data System (ADS)

Azhoni, A.; Goyal, M. K.

2017-12-01

Narrowing the gap between research, policy making and implementing adaptation remains a challenge in many parts of the world where climate change is likely to severely impact subsistence agriculture. This research aims to narrow this gap by matching the adaptation strategies being framed by policy makers and perspectives of consultants and researchers which are expected to be implemented by development agencies farmers in the state of Sikkim in India. Our case study examined the framing and implementation of State Action Plan on Climate Change through semi-structured interviews carried out with decision makers in the State Government, Scientific Organisations, consultants, local academia, implementing and development agencies, and farmers for whom the adaptation strategies are targeted. Using Social Network and Stakeholder Analysis approach, this research unravels the complexities of perceiving climate change impacts, identifying adaptation strategies, and implementing climate change adaptation strategies. While farmers are less aware about the global phenomenon of climate change impacts for their subsistence livelihood, their knowledge of the local conditions and their close interaction with the State Government Agriculture Department provides them an access to new and high value crops. Although important steps are initiated through the Sikkim State Action Plan on Climate Change it is yet to deliver effective means of adaptation implementation and identifying the networks of close coordination between the various implementing agencies will likely to pay rich dividends. While Sikkim being a small and hilly state with specific contextual challenges of climate change impacts, the results from this study highlights how the internal and external networks between various types of stakeholders informs decision makers in identifying local impacts of climate change and plan adaptation strategies.

Plasticity in dendroclimatic response across the distribution range of Aleppo Pine (Pinus halepensis)

Treesearch

Martin de Luis; Katarina Cufar; Alfredo Di Filippo; Klemen Novak; Andreas Papadopoulos; Gianluca Piovesan; Cyrille B. K. Rathgeber; José Raventós; Miguel Angel Saz; Kevin T. Smith

2013-01-01

We investigated the variability of the climate-growth relationship of Aleppo pine across its distribution range in the Mediterranean Basin. We constructed a network of tree-ring index chronologies from 63 sites across the region. Correlation function analysis identified the relationships of tree-ring index to climate factors for each site. We also estimated the...

Network analysis reveals strongly localized impacts of El Niño

NASA Astrophysics Data System (ADS)

Fan, Jingfang; Meng, Jun; Ashkenazy, Yosef; Havlin, Shlomo; Schellnhuber, Hans Joachim

2017-07-01

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network “in”-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger in-weighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables.

Network analysis reveals strongly localized impacts of El Niño.

PubMed

Fan, Jingfang; Meng, Jun; Ashkenazy, Yosef; Havlin, Shlomo; Schellnhuber, Hans Joachim

2017-07-18

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network "in"-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger in-weighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables.

Tracing the flow: Climate change actor-networks in Oklahoma secondary science education

NASA Astrophysics Data System (ADS)

Colston, Nicole Marie

This dissertation reports research about the translation of climate change in science education. Public controversies about climate change education raises questions about the lived experiences of teachers in Oklahoma and the role of science education in increasing public understanding. A mixed methods research design included rhetorical analysis of climate change denial media, key informant interviews with science education stakeholders, and a survey questionnaire of secondary science teachers. Final analysis was further informed by archival research and supplemented by participant observation in state-wide meetings and science teacher workshops. The results are organized into three distinct manuscripts intended for publication across the fields of communication, science education, and climate science. As a whole the dissertation answers the research question, how does manufactured scientific controversy about climate change present specific challenges and characterize negotiations in secondary science education in Oklahoma? Taken together, the findings suggest that manufactured controversy about climate change introduces a logic of non-problematicity, challenges science education policy making, and undermines scientific consensus about global warming.

The Power of Cooperation in International Paleoclimate Science: Examples from the PAGES 2k Network and the Ocean2k Working Group

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.

Ecological networks are more sensitive to plant than to animal extinction under climate change

PubMed Central

Schleuning, Matthias; Fründ, Jochen; Schweiger, Oliver; Welk, Erik; Albrecht, Jörg; Albrecht, Matthias; Beil, Marion; Benadi, Gita; Blüthgen, Nico; Bruelheide, Helge; Böhning-Gaese, Katrin; Dehling, D. Matthias; Dormann, Carsten F.; Exeler, Nina; Farwig, Nina; Harpke, Alexander; Hickler, Thomas; Kratochwil, Anselm; Kuhlmann, Michael; Kühn, Ingolf; Michez, Denis; Mudri-Stojnić, Sonja; Plein, Michaela; Rasmont, Pierre; Schwabe, Angelika; Settele, Josef; Vujić, Ante; Weiner, Christiane N.; Wiemers, Martin; Hof, Christian

2016-01-01

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks. PMID:28008919

Ecological networks are more sensitive to plant than to animal extinction under climate change.

PubMed

Schleuning, Matthias; Fründ, Jochen; Schweiger, Oliver; Welk, Erik; Albrecht, Jörg; Albrecht, Matthias; Beil, Marion; Benadi, Gita; Blüthgen, Nico; Bruelheide, Helge; Böhning-Gaese, Katrin; Dehling, D Matthias; Dormann, Carsten F; Exeler, Nina; Farwig, Nina; Harpke, Alexander; Hickler, Thomas; Kratochwil, Anselm; Kuhlmann, Michael; Kühn, Ingolf; Michez, Denis; Mudri-Stojnić, Sonja; Plein, Michaela; Rasmont, Pierre; Schwabe, Angelika; Settele, Josef; Vujić, Ante; Weiner, Christiane N; Wiemers, Martin; Hof, Christian

2016-12-23

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.

Simulated Tree Growth across the Northern Hemisphere and the Seasonality of Climate Signals Encoded within Tree-ring Widths

NASA Astrophysics Data System (ADS)

Li, X.; St George, S.

2013-12-01

Both dendrochronological theory and regional and global networks of tree-ring width measurements indicate that trees can respond to climate variations quite differently from one location to another. To explain these geographical differences at hemispheric scale, we used a process-based model of tree-ring formation (the Vaganov-Shashkin model) to simulate tree growth at over 6000 locations across the Northern Hemisphere. We compared the seasonality and strength of climate signals in the simulated tree-ring records against parallel analysis conducted on a hemispheric network of real tree-ring observations, tested the ability of the model to reproduce behaviors that emerge from large networks of tree-ring widths and used the model outputs to explain why the network exhibits these behaviors. The simulated tree-ring records are consistent with observations with respect to the seasonality and relative strength of the encoded climate signals, and time-related changes in these climate signals can be predicted using the modeled relative growth rate due to temperature or soil moisture. The positive imprint of winter (DJF) precipitation is strongest in simulations from the American Southwest and northern Mexico as well as selected locations in the Mediterranean and central Asia. Summer (JJA) precipitation has higher positive correlations with simulations in the mid-latitudes, but some high-latitude coastal sites exhibit a negative association. The influence of summer temperature is mainly positive at high-latitude or high-altitude sites and negative in the mid-latitudes. The absolute magnitude of climate correlations are generally higher in simulations than in observations, but the pattern and geographical differences remain the same, demonstrating that the model has skill in reproducing tree-ring growth response to climate variability in the Northern Hemisphere. Because the model uses only temperature, precipitation and latitude as input and is not adjusted for species or other biological factors, the fact that the climate response of the simulations largely agrees with the observations may imply that climate, rather than biology, is the main factor that influences large-scale patterns of the climate information recorded by tree rings. Our results also suggest that the Vaganov-Shashkin model could be used to estimate the likely climate response of trees in ';frontier' areas that have not been sampled extensively. Seasonal Climate Correlations of Simulated Tree-ring Records

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

The worldwide airline network and the dispersal of exotic species: 2007–2010

PubMed Central

Tatem, Andrew J

2009-01-01

International air travel has played a significant role in driving recent increases in the rates of biological invasion and spread of infectious diseases. By providing high speed, busy transport links between spatially distant, but climatically similar regions of the world, the worldwide airline network (WAN) increases the risks of deliberate or accidental movements and establishment of climatically sensitive exotic organisms. With traffic levels continuing to rise and climates changing regionally, these risks will vary, both seasonally and year-by-year. Here, detailed estimates of air traffic trends and climate changes for the period 2007–2010 are used to examine the likely directions and magnitudes of changes in climatically sensitive organism invasion risk across the WAN. Analysis of over 144 million flights from 2007–2010 shows that by 2010, the WAN is likely to change little overall in terms of connecting regions with similar climates, but anticipated increases in traffic and local variations in climatic changes should increase the risks of exotic species movement on the WAN and establishment in new areas. These overall shifts mask spatially and temporally heterogenous changes across the WAN, where, for example, traffic increases and climatic convergence by July 2010 between parts of China and northern Europe and North America raise the likelihood of exotic species invasions, whereas anticipated climatic shifts may actually reduce invasion risks into much of eastern Europe. PMID:20300170

Teacher Networks in the Climate of Comprehensive Education Reform: A Network Analysis of District-Wide Social Capital Flow

ERIC Educational Resources Information Center

Cavanagh, Andrew J.

2015-01-01

The present study investigated the district-wide characteristics of relational ties among a sample of K-12 teachers implementing the Common Core comprehensive education reform. This study addressed deficits in current scholarly understanding of the social influences in schools that impact delivery of educational reform efforts such as the Common…

Analysis of the Diurnal Cycle and Cloud Effects on the Surface Radiation Budget of the SURFRAD Network

NASA Astrophysics Data System (ADS)

Long, C. N.; Augustine, J. A.; McComiskey, A. C.

2017-12-01

The NOAA Earth Systems Research Laboratory (ESRL) Global Monitoring Division (GMD) operates a network of seven surface radiation budget sites (SURFRAD) across the continental United States. The SURFRAD network was established in 1993 with the primary objective to support climate research with accurate, continuous, long-term measurements of the surface radiation budget over the United States and is a major contributor to the WMO international Baseline Surface Radiation Network. The data from the SURFRAD sites have been used in many studies including trend analyses of surface solar brightening (Long et al, 2009; Augustine and Dutton, 2013; Gan et al., 2015). These studies have focused mostly on long term aggregate trends. Here we will present results of studies that take a closer look across the years of the cloud influence on the surface radiation budget components partitioned by seasonal and diurnal analyses, and using derived quantities now available from the SURFRAD data archive produced by the Radiative Flux Analysis value added processing. The results show distinct differences between the sites surface radiative energy budgets and cloud radiative effects due to their differing climates and latitudinal locations.

Assessing the Climate Resilience of Transport Infrastructure Investments in Tanzania

NASA Astrophysics Data System (ADS)

Hall, J. W.; Pant, R.; Koks, E.; Thacker, S.; Russell, T.

2017-12-01

Whilst there is an urgent need for infrastructure investment in developing countries, there is a risk that poorly planned and built infrastructure will introduce new vulnerabilities. As climate change increases the magnitudes and frequency of natural hazard events, incidence of disruptive infrastructure failures are likely to become more frequent. Therefore, it is important that infrastructure planning and investment is underpinned by climate risk assessment that can inform adaptation planning. Tanzania's rapid economic growth is placing considerable strain on the country's transportation infrastructure (roads, railways, shipping and aviation); especially at the port of Dar es Salaam and its linking transport corridors. A growing number of natural hazard events, in particular flooding, are impacting the reliability of this already over-used network. Here we report on new methodology to analyse vulnerabilities and risks due to failures of key locations in the intermodal transport network of Tanzania, including strategic connectivity to neighboring countries. To perform the national-scale risk analysis we will utilize a system-of-systems methodology. The main components of this general risk assessment, when applied to transportation systems, include: (1) Assembling data on: spatially coherent extreme hazards and intermodal transportation networks; (2) Intersecting hazards with transport network models to initiate failure conditions that trigger failure propagation across interdependent networks; (3) Quantifying failure outcomes in terms of social impacts (customers/passengers disrupted) and/or macroeconomic consequences (across multiple sectors); and (4) Simulating, testing and collecting multiple failure scenarios to perform an exhaustive risk assessment in terms of probabilities and consequences. The methodology is being used to pinpoint vulnerability and reduce climate risks to transport infrastructure investments.

Developing convolutional neural networks for measuring climate change opinions from social media data

NASA Astrophysics Data System (ADS)

Mao, H.; Bhaduri, B. L.

2016-12-01

Understanding public opinions on climate change is important for policy making. Public opinion, however, is typically measured with national surveys, which are often too expensive and thus being updated at a low frequency. Twitter has become a major platform for people to express their opinions on social and political issues. Our work attempts to understand if Twitter data can provide complimentary insights about climate change perceptions. Since the nature of social media is real-time, this data source can especially help us understand how public opinion changes over time in response to climate events and hazards, which though is very difficult to be captured by manual surveys. We use the Twitter Streaming API to collect tweets that contain keywords, "climate change" or "#climatechange". Traditional machine-learning based opinion mining algorithms require a significant amount of labeled data. Data labeling is notoriously time consuming. To address this problem, we use hashtags (a significant feature used to mark topics of tweets) to annotate tweets automatically. For example, hashtags, #climatedenial and #climatescam, are negative opinion labels, while #actonclimate and #climateaction are positive. Following this method, we can obtain a large amount of training data without human labor. This labeled dataset is used to train a deep convolutional neural network that classifies tweets into positive (i.e. believe in climate change) and negative (i.e. do not believe). Based on the positive/negative tweets obtained, we will further analyze risk perceptions and opinions towards policy support. In addition, we analyze twitter user profiles to understand the demographics of proponents and opponents of climate change. Deep learning techniques, especially convolutional deep neural networks, have achieved much success in computer vision. In this work, we propose a convolutional neural network architecture for understanding opinions within text. This method is compared with lexicon-based opinion analysis approaches. Results and the advantages/limitations of this method are to be discussed.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Assessment of climate change effects on mountain ecosystems through a cross-site analysis in the Alps and Apennines.

PubMed

Rogora, M; Frate, L; Carranza, M L; Freppaz, M; Stanisci, A; Bertani, I; Bottarin, R; Brambilla, A; Canullo, R; Carbognani, M; Cerrato, C; Chelli, S; Cremonese, E; Cutini, M; Di Musciano, M; Erschbamer, B; Godone, D; Iocchi, M; Isabellon, M; Magnani, A; Mazzola, L; Morra di Cella, U; Pauli, H; Petey, M; Petriccione, B; Porro, F; Psenner, R; Rossetti, G; Scotti, A; Sommaruga, R; Tappeiner, U; Theurillat, J-P; Tomaselli, M; Viglietti, D; Viterbi, R; Vittoz, P; Winkler, M; Matteucci, G

2018-05-15

Mountain ecosystems are sensitive and reliable indicators of climate change. Long-term studies may be extremely useful in assessing the responses of high-elevation ecosystems to climate change and other anthropogenic drivers from a broad ecological perspective. Mountain research sites within the LTER (Long-Term Ecological Research) network are representative of various types of ecosystems and span a wide bioclimatic and elevational range. Here, we present a synthesis and a review of the main results from ecological studies in mountain ecosystems at 20 LTER sites in Italy, Switzerland and Austria covering in most cases more than two decades of observations. We analyzed a set of key climate parameters, such as temperature and snow cover duration, in relation to vascular plant species composition, plant traits, abundance patterns, pedoclimate, nutrient dynamics in soils and water, phenology and composition of freshwater biota. The overall results highlight the rapid response of mountain ecosystems to climate change, with site-specific characteristics and rates. As temperatures increased, vegetation cover in alpine and subalpine summits increased as well. Years with limited snow cover duration caused an increase in soil temperature and microbial biomass during the growing season. Effects on freshwater ecosystems were also observed, in terms of increases in solutes, decreases in nitrates and changes in plankton phenology and benthos communities. This work highlights the importance of comparing and integrating long-term ecological data collected in different ecosystems for a more comprehensive overview of the ecological effects of climate change. Nevertheless, there is a need for (i) adopting co-located monitoring site networks to improve our ability to obtain sound results from cross-site analysis, (ii) carrying out further studies, in particular short-term analyses with fine spatial and temporal resolutions to improve our understanding of responses to extreme events, and (iii) increasing comparability and standardizing protocols across networks to distinguish local patterns from global patterns. Copyright © 2017 Elsevier B.V. All rights reserved.

Knowledge Discovery from Climate Data using Graph-Based Methods

NASA Astrophysics Data System (ADS)

Steinhaeuser, K.

2012-04-01

Climate and Earth sciences have recently experienced a rapid transformation from a historically data-poor to a data-rich environment, thus bringing them into the realm of the Fourth Paradigm of scientific discovery - a term coined by the late Jim Gray (Hey et al. 2009), the other three being theory, experimentation and computer simulation. In particular, climate-related observations from remote sensors on satellites and weather radars, in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale simulations, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer a significant opportunity for advancing climate science and our understanding of the global climate system, yet current analysis techniques are not able to fully realize their potential benefits. We describe a class of computational approaches, specifically from the data mining and machine learning domains, which may be novel to the climate science domain and can assist in the analysis process. Computer scientists have developed spatial and spatio-temporal analysis techniques for a number of years now, and many of them may be applicable and/or adaptable to problems in climate science. We describe a large-scale, NSF-funded project aimed at addressing climate science question using computational analysis methods; team members include computer scientists, statisticians, and climate scientists from various backgrounds. One of the major thrusts is in the development of graph-based methods, and several illustrative examples of recent work in this area will be presented.

Bringing New Ph.D.s Together for Interdisciplinary Climate Change Research

NASA Astrophysics Data System (ADS)

Phelan, Liam; Jones, Holly; Marlon, Jennifer R.

2013-01-01

Climate change is complex and thus requires interdisciplinary research, and new scholars are rising to that challenge. The Dissertations Initiative for the Advancement of Climate Change Research (DISCCRS (pronounced "discourse"); see http://www.disccrs.org) brings together select groups of recent PhD graduates to encourage interdisciplinary work on climate change. The DISCCRS Symposium VII held just outside of Colorado Springs, Colo., brought together 33 graduates from fields as diverse as climatology, ecology, anthropology, and political science for an intensive week of cross-disciplinary engagement in activities like facilitation and leadership training, collaborative research development, peer networking, communication training, and analysis of working group processes.

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

2014-01-01

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

The Climate Literacy and Energy Awareness Network (CLEAN) - Enabling Collective Impact on Climate and Energy Literacy

NASA Astrophysics Data System (ADS)

Ledley, T. S.; Gold, A. U.; Niepold, F., III

2015-12-01

Numerous climate change education efforts exist that aim to enable citizens and society to make informed decisions addressing environmental and societal issues arising from climate change. To extend the reach and impact of these efforts, it is necessary to coordinate them in order to reach a greater collective impact. The Collective Impact model, as described by Kania & Kramer (2011), requires five elements: 1) a common agenda; 2) shared measurement systems; 3) mutually reinforcing activities; 4) continuous communication; and 5) a well-funded backbone support organization. The CLEAN Network, as an example of a rudimentary form of such an organization, engages in continuous communication through weekly teleconferences, an active listserv and other activities to share resources, activities, and ideas that is moving the network to develop common understandings that will likely lead to the development of effective collective impact on increasing climate and energy literacy. A Spring 2013 survey of the CLEAN Network provided insight as to how the CLEAN Network was addressing member needs and identified what other support was needed to increase its collective impact. In addition, community discussions identified the components needed for an effective overarching backbone support organization. A Fall 2015 survey of the CLEAN Network and the broader climate change education community is being conducted to examine 1) how the CLEAN Network make up and needs have evolved and how they compare to the broader community, and 2) to gather further input into the shaping of the elements of collective impact on climate and energy literacy. This presentation will describe the results from the 2015 survey and compare them to the 2013 survey and the community discussions. This will include describing the CLEAN Network's evolving professional make up, engagement of its members network activities, the importance of the network to members; how the findings compare with the broader climate change education community, and how the collective impact can be increased.

Recent Naval Postgraduate School Publications.

DTIC Science & Technology

1980-04-01

Numerical models of ocean circulation and Climate interaction Revs, of Geophis,.and Space Phys., vol. 17, no. 7, p. 1494-1507, (1 979) Haney, R 1...POSTGRADUATE SCHOOL Monterey, California DEPARTMENT OF COMPUTER SCIENCE C06FEBENCE PRESENTATIONS Bradley, G H Enerqy modelling with network optimization...Systems Analysis, Sept., 97 Bradley, G H; Brown, G G Network optimization and defense modeling Center for Nay. Analyses, Arlington, Va., Aug., 1976

Assessment of Climate Change Adaptation Costs for the U.S. Road Network

EPA Science Inventory

The U.S. road network is one of the nation’s most important capital assets and is vital to the functioning of the U.S. economy. Climate change may represent a risk or an opportunity to this network, as changes in climate stress will affect the resources necessary for both road m...

Flow networks for Ocean currents

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkenthin, Nora; Marwan, Norbert; Kurths, Jürgen

2014-05-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e., by its high computational complexity, we here introduce a new, discrete construction of flow-networks, which is then applied to static and dynamic velocity fields. Analyzing the flow-networks of prototypical flows we find that our approach can highlight the zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. We also apply the method to time series data of the Equatorial Pacific Ocean Current and the Gulf Stream ocean current for the changing velocity fields, which could not been done before, and analyse the properties of the dynamical system. Flow-networks can be powerful tools to theoretically understand the step from system's dynamics to network's topology that can be analyzed using network measures and is used for shading light on different climatic phenomena.

Reconstructing the leading mode of multi-decadal North Atlantic variability over the last two millenia using functional paleoclimate networks

NASA Astrophysics Data System (ADS)

Franke, Jasper G.; Werner, Johannes; Donner, Reik V.

2017-04-01

The increasing availability of high-resolution North Atlantic paleoclimate proxies allows to not only study local climate variations in time, but also temporal changes in spatial variability patterns across the entire region possibly controlled by large-scale coherent variability modes such as the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation. In this study, we use functional paleoclimate network analysis [1,2] to investigate changes in the statistical similarity patterns among an ensemble of high-resolution terrestrial paleoclimate records from Northern Europe included in the Arctic 2k data base. Specifically, we construct complex networks capturing the mutual statistical similarity of inter-annual temperature variability recorded in tree ring records, ice cores and lake sediments for multidecadal time windows covering the last two millenia. The observed patterns of co-variability are ultimately connected to the North Atlantic atmospheric circulation and most prominently to multidecadal variations of the NAO. Based on the inferred networks, we study the dynamical similarity between regional clusters of archives defined according to present-day inter-annual temperature variations across the study region. This analysis identifies those time-dependent inter-regional linkages that are most informative about the leading-order North Atlantic climate variability according to a recent NAO reconstruction for the last millenium [3]. Based on these linkages, we extend the existing reconstruction to obtain qualitative information on multidecadal to centennial scale North Atlantic climate variability over the last two millenia. In general, we find a tendency towards a dominating positive NAO phase interrupted by pronounced and extended intervals of negative NAO. Relatively rapid transitions between both types of behaviour are present during distinct periods including the Little Ice Age, the Medieval Climate Anomaly and for the Dark Ages Little Ice Age. [1] K. Rehfeld, N. Marwan, S.F.M. Breitenbach, J. Kurths: Late Holocene Asian summer monsoon dynamics from small but complex networks of paleoclimate data. Climate Dynamics 41, 3-19, 2013 [2] J.L. Oster, N.P. Kelley: Tracking regional and global teleconnections recorded by western North American speleothem records. Quaternary Science Reviews 149, 18-33, 2016 [3] P. Ortega, F. Lehner, D. Swingedouw, V. Masson-Delmotte, C.C. Raible, M. Casado, P. Yiou: A model-tested North Atlantic Oscillation reconstruction for the past millenium. Nature 523, 71-74, 2015

Virtual water management in the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B.; Van Beek, L. P.; Meeks, E.; Klein Goldewijk, K.; Bierkens, M. F.; Scheidel, W.; Wassen, M. J.; Van der Velde, Y.; Dekker, S. C.

2013-12-01

Climate change can have extreme societal impacts particularly in regions that are water-limited for agriculture. A society's ability to manage its water resources in such environments is critical to its long-term viability. Water management can involve improving agricultural yields through in-situ irrigation or the redistribution of virtual water resources through trade in food. Here, we explore how such water management strategies improve societal resilience by examining virtual water management during the Roman Empire in the water-limited region of the Mediterranean. Climate was prescribed based on previously published reconstructions which show that during the Roman Empire when the Central Mediterranean was wetter, the West and Southeastern Mediterranean became drier and vice-versa. Evidence indicates that these shifts in the climatic seesaw may have occurred relatively rapidly. Using the Global hydrological model PCR GLOBWB and estimates of landcover based on the HYDE dataset we generate potential agricultural yield maps under two extremes of this climatic seesaw. HYDE estimates of population in conjunction with potential yield estimates are used to identify regions of Mediterranean with a yield surplus or deficit. The surplus and deficit regions form nodes on a virtual water redistribution network with transport costs taken from the Stanford Geospatial Network Model of the Roman World (ORBIS). Our demand-driven, virtual water redistribution network allows us to quantitatively explore the importance of water management strategies such as irrigation and food trade for the Romans. By examining virtual water transport cost anomalies between climate scenarios our analysis highlights regions of the Mediterranean that were most vulnerable to climate change during the Roman Period.

Microclimate Exposures of Surface-Based Weather Stations: Implications For The Assessment of Long-Term Temperature Trends.

NASA Astrophysics Data System (ADS)

Davey, Christopher A.; Pielke, Roger A., Sr.

2005-04-01

The U.S. Historical Climate Network is a subset of surface weather observation stations selected from the National Weather Service cooperative station network. The criteria used to select these stations do not sufficiently address station exposure characteristics. In addition, the current metadata available for cooperative network stations generally do not describe site exposure characteristics in sufficient detail. This paper focuses on site exposures with respect to air temperature measurements. A total of 57 stations were photographically surveyed in eastern Colorado, comparing existing exposures to the standards endorsed by the World Meteorological Organization. The exposures of most sites surveyed, including U.S. Historical Climate Network sites, were observed to fall short of these standards. This raises a critical question about the use of many Historical Climate Network sites in the development of long-term climate records and the detection of climate trends. Some of these sites clearly have poor exposures and therefore should be considered for removal from the Historical Climate Network. Candidate replacement sites do exist and should be considered for addition into the network to replace the removed sites. Documentation as performed for this study should be conducted worldwide in order to determine the extent of spatially nonrepresentative exposures and possible temperature biases.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network

Treesearch

Enric Batllori; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz; Carol Miller

2017-01-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform...

"Time-dependent flow-networks"

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkentin, Nora; Lopez, Cristobal; Hernandez-Garcia, Emilio; Marwan, Norbert; Kurths, Jürgen

2015-04-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply information or heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e. high computational complexity and fixed variety of the flows in the underlying system, we introduce a new, method of flow-networks for changing in time velocity fields including external forcing in the system, noise and temperature-decay. Method of the flow-network construction can be divided into several steps: first we obtain the linear recursive equation for the temperature time-series. Then we compute the correlation matrix for time-series averaging the tensor product over all realizations of the noise, which we interpret as a weighted adjacency matrix of the flow-network and analyze using network measures. We apply the method to different types of moving flows with geographical relevance such as meandering flow. Analyzing the flow-networks using network measures we find that our approach can highlight zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. Flow-networks can be powerful tool to understand the connection between system's dynamics and network's topology analyzed using network measures in order to shed light on different climatic phenomena.

Societal resilience to hydroclimatic change in the Roman World

NASA Astrophysics Data System (ADS)

Dermody, Brian; van Beek, Rens; Bierkens, Marc; Dekker, Stefan

2016-04-01

The Romans were masters of water resource management. They employed sophisticated irrigation techniques alongside a highly integrated food redistribution system that provided stable food supplies under the variable hydroclimatic regime within the Roman World. However, a number of paleoclimate studies have demonstrated hydroclimatic changes during the Roman Period that exceeded the amplitude and persistence of normal climate variability. In particular, there was a shift from warmer and more stable hydroclimatic conditions in the Roman Warm Period (c.250 BC - 250 AD) to cooler and more variable conditions in Late Roman Period (after c.250 AD). In this study we use a socio-hydrological model of the Roman world to explore the impact of hydroclimatic changes between the Roman Warm Period and Late Roman Period on the Roman food production and redistribution system. We calculate crop yields based on temperature and water resource availability using PC Raster Global Water Balance model (PCR-GLOBWB). PCR-GLOBWB is forced with reanalysis climate fields reflecting reconstructions of Roman Warm Period to the Late Roman climate patterns. Cropland areas and settlement patterns are derived from a database of 14,700 Roman settlement sites and crop suitability maps. We simulate food redistribution using a multi-agent food redistribution network with link weights based on Orbis: The Stanford Geospatial Network of the Roman World. Our analysis indicates a reduction in crop yields during the Late Roman Period compared with the Roman Warm Period owing to cooler temperatures. In addition, our simulations indicate that increased hydroclimatic variability decreased the stability of yields in the Late Roman period. Crop yields in the Western Empire are simulated to have been impacted most by the change in climate owing to cooler average temperatures and greater hydroclimatic variability compared with the Eastern part of the Empire. The food redistribution network was essential to buffer against lower and less stable yields in the Late Roman Period. However, the Late Roman Period coincided with a breakdown in the food redistribution network, making the Western Roman Empire particularly vulnerable to changing climate conditions. Our analysis demonstrates a number of important processes that have general implications for water resource management in food production and redistribution systems.

Spatial relationship between climatic diversity and biodiversity conservation value.

PubMed

Wang, Junjun; Wu, Ruidong; He, Daming; Yang, Feiling; Hu, Peijun; Lin, Shiwei; Wu, Wei; Diao, Yixin; Guo, Yang

2018-06-04

Capturing the full range of climatic diversity in a reserve network is expected to improve the resilience of biodiversity to climate change. Therefore, a study on systematic conservation planning for climatic diversity that explicitly or implicitly hypothesizes that regions with higher climatic diversity will support greater biodiversity is needed. However, little is known about the extent and generality of this hypothesis. This study utilized the case of Yunnan, southwest China, to quantitatively classify climatic units and modeled 4 climatic diversity indicators, including the variety of climatic units (VCU), rarity of climatic units (RCU), endemism of climatic units (ECU) and a composite index of climatic units (CICD). We used 5 reliable priority conservation area (PCA) schemes to represent the areas with high biodiversity conservation value. We then investigated the spatial relationships between the 4 climatic diversity indicators and the 5 PCA schemes and assessed the representation of climatic diversity within the existing nature reserves. The CICD exhibited the best performance for indicating high conservation value areas, followed by the ECU and RCU. However, contrary to conventional knowledge, VCU did not show a positive association with biodiversity conservation value. The rarer or more endemic climatic units tended to have higher reserve coverage than the more common units. However, only 28 units covering 10.5% of the land in Yunnan had more than 17% of their areas protected. In addition to climatic factors, topography and human disturbances also significantly affected the relationship between climatic diversity and biodiversity conservation value. This analysis suggests that climatic diversity can be an effective surrogate for establishing a more robust reserve network under climate change in Yunnan. Our study improves the understanding of the relationship between climatic diversity and biodiversity and helps build an evidence-based foundation for systematic conservation planning that targets climatic diversity in response to climate change. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

An assessment of climate change impacts on micro-hydropower energy recovery in water supply networks

NASA Astrophysics Data System (ADS)

Brady, Jennifer; Patil, Sopan; McNabola, Aonghus; Gallagher, John; Coughlan, Paul; Harris, Ian; Packwood, Andrew; Williams, Prysor

2015-04-01

Continuity of service of a high quality water supply is vital in sustaining economic and social development. However, water supply and wastewater treatment are highly energy intensive processes and the overall cost of water provision is rising rapidly due to increased energy costs, higher capital investment requirements, and more stringent regulatory compliance in terms of both national and EU legislation. Under the EU Directive 2009/28/EC, both Ireland and the UK are required to have 16% and 15% respectively of their electricity generated by renewable sources by 2020. The projected impacts of climate change, population growth and urbanisation will place additional pressures on resources, further increasing future water demand which in turn will lead to higher energy consumption. Therefore, there is a need to achieve greater efficiencies across the water industry. The implementation of micro-hydropower turbines within the water supply network has shown considerable viability for energy recovery. This is achieved by harnessing energy at points of high flow or pressure along the network which can then be utilised on site or alternatively sold to the national grid. Micro-hydropower can provide greater energy security for utilities together with a reduction in greenhouse gas emissions. However, potential climate change impacts on water resources in the medium-to-long term currently act as a key barrier to industry confidence as changes in flow and pressure within the network can significantly alter the available energy for recovery. The present study aims to address these uncertainties and quantify the regional and local impacts of climate change on the viability of energy recovery across water infrastructure in Ireland and the UK. Specifically, the research focuses on assessing the potential future effects of climate change on flow rates at multiple pressure reducing valve sites along the water supply network and also in terms of flow at a number of wastewater treatment works. This analysis is achieved through development of an empirical model utilising historical climatic data in conjunction with low, medium and high emission IPCC climate scenarios using the HADCM3 global climate model across a baseline condition and two further time steps. Results highlight projected alterations in flow rates together with the potential for increases in the frequency and persistence of drought/flooding events and the resulting impacts on future energy recovery. Critical climate change limits are also identified indicating the tolerable ranges within which hydropower recovery is financially viable, thus allowing for more informed decision making across potential sites.

Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape.

PubMed

Bähner, K W; Zweig, K A; Leal, I R; Wirth, R

2017-10-01

Forest fragmentation and climate change are among the most severe and pervasive forms of human impact. Yet, their combined effects on plant-insect herbivore interaction networks, essential components of forest ecosystems with respect to biodiversity and functioning, are still poorly investigated, particularly in temperate forests. We addressed this issue by analysing plant-insect herbivore networks (PIHNs) from understories of three managed beech forest habitats: small forest fragments (2.2-145 ha), forest edges and forest interior areas within three continuous control forests (1050-5600 ha) in an old hyper-fragmented forest landscape in SW Germany. We assessed the impact of forest fragmentation, particularly edge effects, on PIHNs and the resulting differences in robustness against climate change by habitat-wise comparison of network topology and biologically realistic extinction cascades of networks following scores of vulnerability to climate change for the food plant species involved. Both the topological network metrics (complexity, nestedness, trophic niche redundancy) and robustness to climate change strongly increased in forest edges and fragments as opposed to the managed forest interior. The nature of the changes indicates that human impacts modify network structure mainly via host plant availability to insect herbivores. Improved robustness of PIHNs in forest edges/small fragments to climate-driven extinction cascades was attributable to an overall higher thermotolerance across plant communities, along with positive effects of network structure. The impoverishment of PIHNs in managed forest interiors and the suggested loss of insect diversity from climate-induced co-extinction highlight the need for further research efforts focusing on adequate silvicultural and conservation approaches.

3rd Annual Earth System Grid Federation and 3rd Annual Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Face-to-Face Meeting Report December 2013

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

Williams, Dean N.

The climate and weather data science community gathered December 3–5, 2013, at Lawrence Livermore National Laboratory, in Livermore, California, for the third annual Earth System Grid Federation (ESGF) and Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Meeting, which was hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UV-CDAT are global collaborations designed to develop a new generation of open-source software infrastructure that provides distributed access and analysis to observed andmore » simulated data from the climate and weather communities. The tools and infrastructure developed under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change, while the F2F meetings help to build a stronger climate and weather data science community and stronger federated software infrastructure. The 2013 F2F meeting determined requirements for existing and impending national and international community projects; enhancements needed for data distribution, analysis, and visualization infrastructure; and standards and resources needed for better collaborations.« less

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

Amplification or suppression: Social networks and the climate change-migration association in rural Mexico.

PubMed

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

2015-11-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks - the ties connecting an origin and destination - may operate as "migration corridors" with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying , social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.

The MedCLIVAR Network

NASA Astrophysics Data System (ADS)

Lionello, Piero; Medclivar sg, The

2013-04-01

The MedCLIVAR initiative was first proposed at the 2003 European Geosciences Union assembly in Nice, France. In 2005, it was endorsed by the International Climate Variability and Predictability (CLIVAR) office. Subsequently, the MedCLIVAR Research Network Project was formally approved by the European Science Foundation and launched in May 2006 with the support of funding agencies from 12 countries. Since then, MedCLIVAR has served as a scientific network to promote interaction among different scientific disciplines and to develop a multidisciplinary vision of the evolution of the Mediterranean climate through studies that integrate atmospheric, marine, and terrestrial climate components at time scales ranging from paleoreconstructions to future climate scenarios. Presently, the network continues dealing with scientific issues including past climate variability; connections between the Mediterranean and global climate; the Mediterranean Sea circulation and sea level; feedbacks on the global climate system; and regional responses to greenhouse gas, air pollution, and aerosols. Its present activities include the publication of a newsletter, the organization of the next MedCLIVAR conference in 2014 and the publication of a special issue of Regional Environmental Change devoted to the climate of the Mediterranean region.

Climate Change Education in Informal Settings: Using Boundary Objects to Frame Network Dissemination

ERIC Educational Resources Information Center

Steiner, Mary Ann

2016-01-01

This study of climate change education dissemination takes place in the context of a larger project where institutions in four cities worked together to develop a linked set of informal learning experiences about climate change. Each city developed an organizational network to explore new ways to connect urban audiences with climate change…

From Theory to Practice: How Mass Audubon Is Incorporating Strategic Framing about Climate Change

ERIC Educational Resources Information Center

Fleischer, Amy

2013-01-01

Mass Audubon recognized that climate change was significantly impacting bird species distribution and seasonality. Unsure of how and when to engage visitors to their network of wildlife sanctuaries on the topic of climate change, its educators turned to the National Network of Ocean and Climate Change Interpreters' Study Circle (NNOCCI). Through…

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

PubMed Central

Lange, Stefan; Donges, Jonathan F.; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation. Building on a recent study by Feldhoff et al. [1] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system. Three types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed. PMID:25856374

Local difference measures between complex networks for dynamical system model evaluation.

PubMed

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed.

Considering Climate Change in Road and Building Design

NASA Astrophysics Data System (ADS)

Jacobs, Jennifer M.; Kirshen, Paul H.; Daniel, Jo Sias

2013-07-01

What is the role of climate in infrastructure design? How can engineers design for a changing climate? How can climate scientists better inform the design process? These were the questions posed at the first Infrastructure and Climate Network (ICNet) Steering Committee Workshop, which was sponsored by a U.S. National Science Foundation research grant (CBET-1231326) from the Research Coordination Networks-Science, Engineering and Education for Sustainability (RCN-SEES) program.

Drinking-water treatment, climate change, and childhood gastrointestinal illness projections for northern Wisconsin (USA) communities drinking untreated groundwater

NASA Astrophysics Data System (ADS)

Uejio, Christopher K.; Christenson, Megan; Moran, Colleen; Gorelick, Mark

2017-06-01

This study examined the relative importance of climate change and drinking-water treatment for gastrointestinal illness incidence in children (age <5 years) from period 2046-2065 compared to 1991-2010. The northern Wisconsin (USA) study focused on municipalities distributing untreated groundwater. A time-series analysis first quantified the observed (1991-2010) precipitation and gastrointestinal illness associations after controlling for seasonality and temporal trends. Precipitation likely transported pathogens into drinking-water sources or into leaking water-distribution networks. Building on observed relationships, the second analysis projected how climate change and drinking-water treatment installation may alter gastrointestinal illness incidence. Future precipitation values were modeled by 13 global climate models and three greenhouse-gas emissions levels. The second analysis was rerun using three pathways: (1) only climate change, (2) climate change and the same slow pace of treatment installation observed over 1991-2010, and (3) climate change and the rapid rate of installation observed over 2011-2016. The results illustrate the risks that climate change presents to small rural groundwater municipalities without drinking water treatment. Climate-change-related seasonal precipitation changes will marginally increase the gastrointestinal illness incidence rate (mean: ˜1.5%, range: -3.6-4.3%). A slow pace of treatment installation somewhat decreased precipitation-associated gastrointestinal illness incidence (mean: ˜3.0%, range: 0.2-7.8%) in spite of climate change. The rapid treatment installation rate largely decreases the gastrointestinal illness incidence (mean: ˜82.0%, range: 82.0-83.0%).

Review of complex networks application in hydroclimatic extremes with an implementation to characterize spatio-temporal drought propagation in continental USA

NASA Astrophysics Data System (ADS)

Konapala, Goutam; Mishra, Ashok

2017-12-01

The quantification of spatio-temporal hydroclimatic extreme events is a key variable in water resources planning, disaster mitigation, and preparing climate resilient society. However, quantification of these extreme events has always been a great challenge, which is further compounded by climate variability and change. Recently complex network theory was applied in earth science community to investigate spatial connections among hydrologic fluxes (e.g., rainfall and streamflow) in water cycle. However, there are limited applications of complex network theory for investigating hydroclimatic extreme events. This article attempts to provide an overview of complex networks and extreme events, event synchronization method, construction of networks, their statistical significance and the associated network evaluation metrics. For illustration purpose, we apply the complex network approach to study the spatio-temporal evolution of droughts in Continental USA (CONUS). A different drought threshold leads to a new drought event as well as different socio-economic implications. Therefore, it would be interesting to explore the role of thresholds on spatio-temporal evolution of drought through network analysis. In this study, long term (1900-2016) Palmer drought severity index (PDSI) was selected for spatio-temporal drought analysis using three network-based metrics (i.e., strength, direction and distance). The results indicate that the drought events propagate differently at different thresholds associated with initiation of drought events. The direction metrics indicated that onset of mild drought events usually propagate in a more spatially clustered and uniform approach compared to onsets of moderate droughts. The distance metric shows that the drought events propagate for longer distance in western part compared to eastern part of CONUS. We believe that the network-aided metrics utilized in this study can be an important tool in advancing our knowledge on drought propagation as well as other hydroclimatic extreme events. Although the propagation of droughts is investigated using the network approach, however process (physics) based approaches is essential to further understand the dynamics of hydroclimatic extreme events.

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

PubMed Central

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

2015-01-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks – the ties connecting an origin and destination – may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place. PMID:26692656

Characterizing the evolution of climate networks

NASA Astrophysics Data System (ADS)

Tupikina, L.; Rehfeld, K.; Molkenthin, N.; Stolbova, V.; Marwan, N.; Kurths, J.

2014-06-01

Complex network theory has been successfully applied to understand the structural and functional topology of many dynamical systems from nature, society and technology. Many properties of these systems change over time, and, consequently, networks reconstructed from them will, too. However, although static and temporally changing networks have been studied extensively, methods to quantify their robustness as they evolve in time are lacking. In this paper we develop a theory to investigate how networks are changing within time based on the quantitative analysis of dissimilarities in the network structure. Our main result is the common component evolution function (CCEF) which characterizes network development over time. To test our approach we apply it to several model systems, Erdős-Rényi networks, analytically derived flow-based networks, and transient simulations from the START model for which we control the change of single parameters over time. Then we construct annual climate networks from NCEP/NCAR reanalysis data for the Asian monsoon domain for the time period of 1970-2011 CE and use the CCEF to characterize the temporal evolution in this region. While this real-world CCEF displays a high degree of network persistence over large time lags, there are distinct time periods when common links break down. This phasing of these events coincides with years of strong El Niño/Southern Oscillation phenomena, confirming previous studies. The proposed method can be applied for any type of evolving network where the link but not the node set is changing, and may be particularly useful to characterize nonstationary evolving systems using complex networks.

U.S. Geological Survey Ground-Water Climate Response Network

USGS Publications Warehouse

,

2007-01-01

The U.S. Geological Survey serves the Nation by providing reliable hydrologic information used by others to manage the Nation's water resources. The U.S. Geological Survey (USGS) measures more than 20,000 wells each year for a variety of objectives as part of Federal programs and in cooperation with State and local agencies. Water-level data are collected using consistent data-collection and quality-control methods. A small subset of these wells meets the criteria necessary to be included in a 'Climate Response Network' of wells designed to illustrate the response of the ground-water system to climate variations nationwide. The primary purpose of the Climate Response Network is to portray the effect of climate on ground-water levels in unconfined aquifers or near-surface confined aquifers that are minimally affected by pumping or other anthropogenic stresses. The Climate Response Network Web site (http://groundwaterwatch.usgs.gov/) is the official USGS Web site for illustrating current ground-water conditions in the United States and Puerto Rico. The Climate Response Network Web pages provide information on ground-water conditions at a variety of scales. A national map provides a broad overview of water-table conditions across the Nation. State maps provide a more local picture of ground-water conditions. Site pages provide the details about a specific well.

Collaborating for Climate Education - A Look at Strategic Partnerships

NASA Astrophysics Data System (ADS)

Bozuwa, J.; Lewis, C.

2015-12-01

Collaborating for Climate Education WeekEarth Day Network (EDN) developed Climate Education Week toolkit, a turnkey online resource for grades K-12 that provided teachers with everything they needed to deliver lessons, activities, contests, and service learning projects that related to climate science during Climate Education Week (April 18-25). EDN assembled an Advisory Group to develop the survey, lesson plans and activities, and resources. The Advisory Group consisted of experts and partners in environmental education, including representatives from other government and non-governmental organizations working with the White House on Climate Education, as well as educators in our Educator's Network. EDN's Climate Education Week Advisory Board brought together top academics and major stakeholders in climate education throughout the development and outreach processes. The Advisory Board included representatives from the Alliance for Climate Education (ACE), The CLEAN Network, NOAA, The Department of Energy, and NASA. The representatives from the board helped to identify and streamline the most effective and necessary lesson plans, strategic themes to maintain throughout the toolkit, and avenues for increased outreach. EDN also partnered with Connect4Climate, PBS's Plum Landing, Young Voices of Climate Change, FEMA, and The Wild Center to develop content and to broaden the reach of the toolkit. Each of the seven days had a different theme that addressed a specific climate education topic, with highlighted activities and resources for elementary, middle and high school levels. The toolkit provided educators with a comprehensive view of climate change—beginning with the science, the anthropogenic causes, and societal impacts and then providing solutions, ways to take action, and the green economy transition. This online resource connected educators to a network of effective resources from our partners, all of which saw a significant uptick in their online viewership. Using the highly recognized Earth Day platform, the high level of involvement from partners and Advisory Board members, and EDN's ever-growing network, EDN had the ability to reach thousands of educators and students, and further the climate conversation.

Climate state: Science-state struggles and the formation of climate science in the US from the 1930s to 1960s.

PubMed

Baker, Zeke

2017-12-01

This article has two aims: first, to understand the co-production of climate science and the state, and second, to provide a test case for Pierre Bourdieu's field theory. To these ends, the article reconstructs the historical formation of a US climate science field, with an analytic focus on inter-field dynamics and heterogeneous networking practices. Drawing from primary- and secondary-source materials, the historical analysis focuses on relations between scientists and state actors from the 1930s to the 1960s. The account shows how actors with positions linking scientific and bureaucratic fields constructed critical nodes and 'hinges' that co-produced war-making and state expansion on the one hand, and a relatively autonomous climate science field on the other. The analysis explains the emergence of climate science by focusing on the WWII-era transformation of meteorology and oceanography into distinct disciplines, the emergence of 'basic' research as a central principle of post-war government, and the formation of a climate science field by the 1960s centered on computerized modeling and populated by an interdisciplinary scientific elite. The article concludes by indicating how these processes led to the subsequent development of climate change as a science-state conundrum that has reorganized the climate science field in recent decades.

The Multiplex Network of EU Lobby Organizations.

PubMed

Zeng, An; Battiston, Stefano

2016-01-01

The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. While no data is available at this stage to examine the success of lobbies in exerting influence on specific policy issues, we perform a first systematic multi-layer network analysis of a large lobby registry. Here we focus on the domains of finance and climate and we combine information on affiliation and client relations from the EU transparency register with information about shareholding and interlocking directorates of firms. We find that the network centrality of lobby organizations has no simple relation with their lobbying budget. Moreover, different layers of the multiplex network provide complementary information to characterize organizations' potential influence. At the aggregate level, it appears that while the domains of finance and climate are separated on the layer of affiliation relations, they become intertwined when economic relations are considered. Because groups of interest differ not only in their budget and network centrality but also in terms of their internal cohesiveness, drawing a map of both connections across and within groups is a precondition to better understand the dynamics of influence on policy making and the forces at play.

The Multiplex Network of EU Lobby Organizations

PubMed Central

Zeng, An; Battiston, Stefano

2016-01-01

The practice of lobbying in the interest of economic or social groups plays an important role in the policy making process of most economies. While no data is available at this stage to examine the success of lobbies in exerting influence on specific policy issues, we perform a first systematic multi-layer network analysis of a large lobby registry. Here we focus on the domains of finance and climate and we combine information on affiliation and client relations from the EU transparency register with information about shareholding and interlocking directorates of firms. We find that the network centrality of lobby organizations has no simple relation with their lobbying budget. Moreover, different layers of the multiplex network provide complementary information to characterize organizations’ potential influence. At the aggregate level, it appears that while the domains of finance and climate are separated on the layer of affiliation relations, they become intertwined when economic relations are considered. Because groups of interest differ not only in their budget and network centrality but also in terms of their internal cohesiveness, drawing a map of both connections across and within groups is a precondition to better understand the dynamics of influence on policy making and the forces at play. PMID:27792734

PAVICS: A Platform for the Analysis and Visualization of Climate Science

NASA Astrophysics Data System (ADS)

Gauvin St-Denis, B.; Landry, T.; Huard, D. B.; Byrns, D.; Chaumont, D.; Foucher, S.

2016-12-01

Climate service providers are boundary organizations working at the interface of climate science research and users of climate information. Users include academics in other disciplines looking for credible, customized future climate scenarios, government planners, resource managers, asset owners, as well as service utilities. These users are looking for relevant information regarding the impacts of climate change as well as informing decisions regarding adaptation options. As climate change concerns become mainstream, the pressure on climate service providers to deliver tailored, high quality information in a timely manner increases rapidly. To meet this growing demand, Ouranos, a climate service center located in Montreal, is collaborating with the Centre de recherche informatique de Montreal (CRIM) to develop a climate data analysis web-based platform interacting with RESTful services covering data access and retrieval, geospatial analysis, bias correction, distributed climate indicator computing and results visualization. The project, financed by CANARIE, relies on the experience of the UV-CDAT and ESGF-CWT teams, as well as on the Birdhouse framework developed by the German Climate Research Center (DKRZ) and French IPSL. Climate data is accessed through OPEnDAP, while computations are carried through WPS. Regions such as watersheds or user-defined polygons, used as spatial selections for computations, are managed by GeoServer, also providing WMS, WFS and WPS capabilities. The services are hosted on independent servers communicating by high throughput network. Deployment, maintenance and collaboration with other development teams are eased by the use of Docker and OpenStack VMs. Web-based tools are developed with modern web frameworks such as React-Redux, OpenLayers 3, Cesium and Plotly. Although the main objective of the project is to build a functioning, usable data analysis pipeline within two years, time is also devoted to explore emerging technologies and assess their potential. For instance, sandbox environments will store climate data in HDFS, process it with Apache Spark and allow interaction through Jupyter Notebooks. Data streaming of observational data with OpenGL and Cesium is also considered.

Improving the interpretability of climate landscape metrics: An ecological risk analysis of Japan's Marine Protected Areas.

PubMed

García Molinos, Jorge; Takao, Shintaro; Kumagai, Naoki H; Poloczanska, Elvira S; Burrows, Michael T; Fujii, Masahiko; Yamano, Hiroya

2017-10-01

Conservation efforts strive to protect significant swaths of terrestrial, freshwater and marine ecosystems from a range of threats. As climate change becomes an increasing concern, these efforts must take into account how resilient-protected spaces will be in the face of future drivers of change such as warming temperatures. Climate landscape metrics, which signal the spatial magnitude and direction of climate change, support a convenient initial assessment of potential threats to and opportunities within ecosystems to inform conservation and policy efforts where biological data are not available. However, inference of risk from purely physical climatic changes is difficult unless set in a meaningful ecological context. Here, we aim to establish this context using historical climatic variability, as a proxy for local adaptation by resident biota, to identify areas where current local climate conditions will remain extant and future regional climate analogues will emerge. This information is then related to the processes governing species' climate-driven range edge dynamics, differentiating changes in local climate conditions as promoters of species range contractions from those in neighbouring locations facilitating range expansions. We applied this approach to assess the future climatic stability and connectivity of Japanese waters and its network of marine protected areas (MPAs). We find 88% of Japanese waters transitioning to climates outside their historical variability bounds by 2035, resulting in large reductions in the amount of available climatic space potentially promoting widespread range contractions and expansions. Areas of high connectivity, where shifting climates converge, are present along sections of the coast facilitated by the strong latitudinal gradient of the Japanese archipelago and its ocean current system. While these areas overlap significantly with areas currently under significant anthropogenic pressures, they also include much of the MPA network that may provide stepping-stone protection for species that must shift their distribution because of climate change. © 2017 John Wiley & Sons Ltd.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

Soares dos Santos, T.; Mendes, D.; Rodrigues Torres, R.

2016-01-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANNs) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon; northeastern Brazil; and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model output and observed monthly precipitation. We used general circulation model (GCM) experiments for the 20th century (RCP historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANNs significantly outperform the MLR downscaling of monthly precipitation variability.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

dos Santos, T. S.; Mendes, D.; Torres, R. R.

2015-08-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANN) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon, Northeastern Brazil and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model out- put and observed monthly precipitation. We used GCMs experiments for the 20th century (RCP Historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANN significantly outperforms the MLR downscaling of monthly precipitation variability.

Development of climate data storage and processing model

NASA Astrophysics Data System (ADS)

Okladnikov, I. G.; Gordov, E. P.; Titov, A. G.

2016-11-01

We present a storage and processing model for climate datasets elaborated in the framework of a virtual research environment (VRE) for climate and environmental monitoring and analysis of the impact of climate change on the socio-economic processes on local and regional scales. The model is based on a «shared nothings» distributed computing architecture and assumes using a computing network where each computing node is independent and selfsufficient. Each node holds a dedicated software for the processing and visualization of geospatial data providing programming interfaces to communicate with the other nodes. The nodes are interconnected by a local network or the Internet and exchange data and control instructions via SSH connections and web services. Geospatial data is represented by collections of netCDF files stored in a hierarchy of directories in the framework of a file system. To speed up data reading and processing, three approaches are proposed: a precalculation of intermediate products, a distribution of data across multiple storage systems (with or without redundancy), and caching and reuse of the previously obtained products. For a fast search and retrieval of the required data, according to the data storage and processing model, a metadata database is developed. It contains descriptions of the space-time features of the datasets available for processing, their locations, as well as descriptions and run options of the software components for data analysis and visualization. The model and the metadata database together will provide a reliable technological basis for development of a high- performance virtual research environment for climatic and environmental monitoring.

A Meta-Analysis of Urban Climate Change Adaptation ...

EPA Pesticide Factsheets

The concentration of people, infrastructure, and ecosystem services in urban areas make them prime sites for climate change adaptation. While advances have been made in developing frameworks for adaptation planning and identifying both real and potential barriers to action, empirical work evaluating urban adaptation planning processes has been relatively piecemeal. Existing assessments of current experience with urban adaptation provide necessarily broad generalizations based on the available peer-reviewed literature. This paper uses a meta-analysis of U.S. cities’ current experience with urban adaptation planning drawing from 54 sources that include peer-reviewed literature, government reports, white papers, and reports published by non-governmental organizations. The analysis specifically evaluates the institutional support structures being developed for urban climate change adaptation. The results demonstrate that adaptation planning is driven by a desire to reduce vulnerability and often catalyzes new collaborations and coordination mechanisms in urban governance. As a result, building capacity for urban climate change adaptation planning requires a focus not only on city governments themselves but also on the complex horizontal and vertical networks that have arisen around such efforts. Existing adaptation planning often lacks attention to equity issues, social vulnerability, and the influence of non-climatic factors on vulnerability. Engaging city govern

Late Noachian Icy Highlands climate model: Exploring the possibility of transient melting and fluvial/lacustrine activity through peak annual and seasonal temperatures

NASA Astrophysics Data System (ADS)

Palumbo, Ashley M.; Head, James W.; Wordsworth, Robin D.

2018-01-01

The nature of the Late Noachian climate of Mars remains one of the outstanding questions in the study of the evolution of martian geology and climate. Despite abundant evidence for flowing water (valley networks and open/closed basin lakes), climate models have had difficulties reproducing mean annual surface temperatures (MAT) > 273 K in order to generate the ;warm and wet; climate conditions presumed to be necessary to explain the observed fluvial and lacustrine features. Here, we consider a ;cold and icy; climate scenario, characterized by MAT ∼225 K and snow and ice distributed in the southern highlands, and ask: Does the formation of the fluvial and lacustrine features require continuous ;warm and wet; conditions, or could seasonal temperature variation in a ;cold and icy; climate produce sufficient summertime ice melting and surface runoff to account for the observed features? To address this question, we employ the 3D Laboratoire de Météorologie Dynamique global climate model (LMD GCM) for early Mars and (1) analyze peak annual temperature (PAT) maps to determine where on Mars temperatures exceed freezing in the summer season, (2) produce temperature time series at three valley network systems and compare the duration of the time during which temperatures exceed freezing with seasonal temperature variations in the Antarctic McMurdo Dry Valleys (MDV) where similar fluvial and lacustrine features are observed, and (3) perform a positive-degree-day analysis to determine the annual volume of meltwater produced through this mechanism, estimate the necessary duration that this process must repeat to produce sufficient meltwater for valley network formation, and estimate whether runoff rates predicted by this mechanism are comparable to those required to form the observed geomorphology of the valley networks. When considering an ambient CO2 atmosphere, characterized by MAT ∼225 K, we find that: (1) PAT can exceed the melting point of water (>273 K) in topographic lows, such as the northern lowlands and basin floors, and small regions near the equator during peak summer season conditions, despite the much lower MAT; (2) Correlation of PAT > 273 K with the predicted distribution of surface snow and ice shows that melting could occur near the edges of the ice sheet in near-equatorial regions where valley networks are abundant; (3) For the case of a circular orbit, the duration of temperatures >273 K at specific valley network locations suggests that yearly meltwater generation is insufficient to carve the observed fluvial and lacustrine features when compared with the percentage of the year required to sustain similar features in the MDV; (4) For the case of a more eccentric orbit (eccentricity of 0.17), the duration of temperatures >273 K at specific valley network locations suggests that annual meltwater generation may be capable of producing sufficient meltwater for valley network formation when repeated for many years; (5) When considering a slightly warmer climate scenario and a circular orbit, characterized by MAT ∼243 K, we find that this small amount of additional greenhouse warming (∼18 K MAT increase) produces time durations of temperatures >273 K that are similar to those observed in the MDV. Thus, we suggest that peak daytime and seasonal temperatures exceeding 273 K could form the valley networks and lakes with either a relatively high eccentricity condition or a small amount of additional atmospheric warming, rather than the need for a sustained MAT at or above 273 K. The results from our positive-degree-day analysis suggest that: (1) For the conditions of 25° obliquity, 600 mbar atmosphere, and eccentricity of 0.17, this seasonal melting process would be required to continue for ∼(33-1083) × 103 years to produce a sufficient volume of meltwater to form the valley networks and lakes; (2) Similarly, for the conditions of 25° obliquity, 1000 mbar atmosphere, circular orbit, and ∼18 K additional greenhouse warming, the process would be required to continue for ∼(21-550) × 103 years. Therefore, peak seasonal melting of snow and ice could induce the generation of meltwater and fluvial and lacustrine activity in a ;cold and icy; Late Noachian climate in a manner similar to that observed in the MDV. A potential shortcoming of this mechanism is that independent estimates of the required runoff rates for valley network formation are much higher than those predicted by this mechanism when considering a circular orbit, even when accounting for additional atmospheric warming. However, we consider that a relatively higher eccentricity condition (0.17) may produce the necessary runoff rates: for the perihelion scenario in which perihelion occurs during southern hemispheric summer, intense melting will occur in the near-equatorial regions and in the southern hemisphere, producing runoff rates comparable to those required for valley network formation (∼mm/day). In the opposite perihelion scenario, the southern hemisphere will experience very little summertime melting. Thus, this seasonal melting mechanism is a strong candidate for formation of the valley networks when considering a relatively high eccentricity (0.17) because this mechanism is capable of (1) producing meltwater in the equatorial region where valley networks are abundant, (2) continuously producing seasonal meltwater for the estimated time duration of valley network formation, (3) yielding the amount of meltwater necessary to incise the valley networks within this time period, and (4) by considering a perihelion scenario in which half of the duration of valley network formation is spent with peak summertime conditions during perihelion in each hemisphere, higher runoff rates are produced than in a circular orbit and the rates may be comparable to those required for valley network formation.

The Characteristics of Earth System Thinking of Science Gifted Students in relation to Climate Changes

NASA Astrophysics Data System (ADS)

Chung, Duk Ho; Cho, Kyu Seong; Hong, Deok Pyo; Park, Kyeong Jin

2016-04-01

This study aimed to investigate the perception of earth system thinking of science gifted students in future problem solving (FPS) in relation to climate changes. In order to this study, the research problem associated with climate changes was developed through a literature review. The thirty seven science gifted students participated in lessons. The ideas in problem solving process of science gifted students were analyzed using the semantic network analysis method. The results are as follows. In the problem solving processes, science gifted students are ''changes of the sunlight by water layer'', ''changes of the Earth''s temperature'', ''changes of the air pressure'', '' change of the wind and weather''were represented in order. On other hand, regard to earth system thinking for climate changes, while science gifted students were used sub components related to atmospheres frequently, they were used sub components related to biosphere, geosphere, and hydrosphere a little. But, the analytical results of the structural relationship between the sub components related to earth system, they were recognised that biosphere, geosphere, and hydrosphere used very important in network structures. In conclusion, science gifted students were understood well that components of the earth system are influencing each other. Keywords : Science gifted students, Future problem solving, Climate change, Earth system thinking

Climate Change Literacy across the Critical Zone Observatory Network

NASA Astrophysics Data System (ADS)

Moore, A.; Derry, L. A.; Zabel, I.; Duggan-Haas, D.; Ross, R. M.

2017-12-01

Earth's Critical Zone extends from the top of the tree canopy to the base of the groundwater lens. Thus the Critical Zone is examined as a suite of interconnected systems and study of the CZ is inherently interdisciplinary. Climate change is an important driver of CZ processes. The US Critical Zone Observatory Network comprises nine observatories and a coordinating National Office. Educational programs and materials developed at each CZO and the National Office have been collected, reviewed, and presented on-line at the CZONO (criticalzone.org/national/education-outreach/resources). Because the CZOs are designed to observe and measure a suite of common parameters on varying geological substrates and within different ecological contexts, educational resources reflect the diversity of processes represented across the network. As climate change has a network-wide impact, the fundamental building blocks of climate change literacy are key elements in many activities within the CZONO resource collection. Carbon-cycle and hydrologic cycle processes are well-represented, with emphasis on human interactions with these resources, as well as the impact of extreme events and the changing climate. Current work on the resource collection focuses on connecting individual resources to "Teach Climate Science" project and the Teacher-Friendly Guide to Climate Change (teachclimatescience.wordpress.com). The Teacher-Friendly Guide is a manual for K-12 teachers that presents both the fundamentals of climate science alongside resources for effective teaching of this controversial topic. Using the reach of the CZO network we hope to disseminate effective climate literacy resources and support to the K-12 community.

The USA National Phenology Network; taking the pulse of our planet

USGS Publications Warehouse

Weltzin, Jake F.

2011-01-01

People have tracked phenology for centuries and for the most practical reasons: it helped them know when to hunt and fish, when to plant and harvest crops, and when to navigate waterways. Now phenology is being used as a tool to assess climate change and its effects on both natural and modified ecosystems. How is the timing of events in plant and animal life cycles, like flowering or migration, responding to climate change? And how are those responses, in turn, affecting people and ecosystems? The USA National Phenology Network (the Network) is working to answer these questions for science and society by promoting a broad understanding of plant and animal phenology and their relationship to environmental change. The Network is a consortium of organizations and individuals that collect, share, and use phenology data, models, and related information to enable scientists, resource managers, and the public to adapt in response to changing climates and environments. In addition, the Network encourages people of all ages and backgrounds to observe and record phenology as a way to discover and explore the nature and pace of our dynamic world. The National Coordinating Office (NCO) of the Network is a resource center that facilitates and encourages widespread collection, integration, and sharing of phenology data and related information (for example, meteorological and hydrological data). The NCO develops and promotes standardized methods for field data collection and maintains several online user interfaces for data upload and download, as well as data exploration, visualization, and analysis. The NCO also facilitates basic and applied research related to phenology, the development of decision-support tools for resource managers and planners, and the design of educational and outreach materials

Analysis of the streamflow-gaging station network in Ohio for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Straub, D.E.

1998-01-01

The streamflow-gaging station network in Ohio was evaluated for its effectiveness in providing regional streamflow information. The analysis involved application of the principles of generalized least squares regression between streamflow and climatic and basin characteristics. Regression equations were developed for three flow characteristics: (1) the instantaneous peak flow with a 100-year recurrence interval (P100), (2) the mean annual flow (Qa), and (3) the 7-day, 10-year low flow (7Q10). All active and discontinued gaging stations with 5 or more years of unregulated-streamflow data with respect to each flow characteristic were used to develop the regression equations. The gaging-station network was evaluated for the current (1996) condition of the network and estimated conditions of various network strategies if an additional 5 and 20 years of streamflow data were collected. Any active or discontinued gaging station with (1) less than 5 years of unregulated-streamflow record, (2) previously defined basin and climatic characteristics, and (3) the potential for collection of more unregulated-streamflow record were included in the network strategies involving the additional 5 and 20 years of data. The network analysis involved use of the regression equations, in combination with location, period of record, and cost of operation, to determine the contribution of the data for each gaging station to regional streamflow information. The contribution of each gaging station was based on a cost-weighted reduction of the mean square error (average sampling-error variance) associated with each regional estimating equation. All gaging stations included in the network analysis were then ranked according to their contribution to the regional information for each flow characteristic. The predictive ability of the regression equations developed from the gaging station network could be improved for all three flow characteristics with the collection of additional streamflow data. The addition of new gaging stations to the network would result in an even greater improvement of the accuracy of the regional regression equations. Typically, continued data collection at stations with unregulated streamflow for all flow conditions that had less than 11 years of record with drainage areas smaller than 200 square miles contributed the largest cost-weighted reduction to the average sampling-error variance of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active gaging stations or the reactivation of discontinued gaging stations if the objective is to maximize the regional information content in the streamflow-gaging station network.

Identifying and attributing common data quality problems: temperature and precipitation observations in Bolivia and Peru

NASA Astrophysics Data System (ADS)

Hunziker, Stefan; Gubler, Stefanie; Calle, Juan; Moreno, Isabel; Andrade, Marcos; Velarde, Fernando; Ticona, Laura; Carrasco, Gualberto; Castellón, Yaruska; Oria Rojas, Clara; Brönnimann, Stefan; Croci-Maspoli, Mischa; Konzelmann, Thomas; Rohrer, Mario

2016-04-01

Assessing climatological trends and extreme events requires high-quality data. However, for many regions of the world, observational data of the desired quality is not available. In order to eliminate errors in the data, quality control (QC) should be applied before data analysis. If the data still contains undetected errors and quality problems after QC, a consequence may be misleading and erroneous results. A region which is seriously affected by observational data quality problems is the Central Andes. At the same time, climatological information on ongoing climate change and climate risks are of utmost importance in this area due to its vulnerability to meteorological extreme events and climatic changes. Beside data quality issues, the lack of metadata and the low station network density complicate quality control and assessment, and hence, appropriate application of the data. Errors and data problems may occur at any point of the data generation chain, e.g. due to unsuitable station configuration or siting, poor station maintenance, erroneous instrument reading, or inaccurate data digitalization and post processing. Different measurement conditions in the predominantly conventional station networks in Bolivia and Peru compared to the mostly automated networks e.g. in Europe or Northern America may cause different types of errors. Hence, applying QC methods used on state of the art networks to Bolivian and Peruvian climate observations may not be suitable or sufficient. A comprehensive amount of Bolivian and Peruvian maximum and minimum temperature and precipitation in-situ measurements were analyzed to detect and describe common data quality problems. Furthermore, station visits and reviews of the original documents were done. Some of the errors could be attributed to a specific source. Such information is of great importance for data users, since it allows them to decide for what applications the data still can be used. In ideal cases, it may even allow to correct the error. Strategies on how to deal with data from the Central Andes will be suggested. However, the approach may be applicable to networks from other countries where conditions of climate observations are comparable.

Climate change education in informal settings: Using boundary objects to frame network dissemination

NASA Astrophysics Data System (ADS)

Steiner, Mary Ann

This study of climate change education dissemination takes place in the context of a larger project where institutions in four cities worked together to develop a linked set of informal learning experiences about climate change. Each city developed an organizational network to explore new ways to connect urban audiences with climate change education. The four city-specific networks shared tools, resources, and knowledge with each other. The networks were related in mission and goals, but were structured and functioned differently depending on the city context. This study illustrates how the tools, resources, and knowledge developed in one network were shared with networks in two additional cities. Boundary crossing theory frames the study to describe the role of objects and processes in sharing between networks. Findings suggest that the goals, capacity and composition of networks resulted in a different emphasis in dissemination efforts, in one case to push the approach out to partners for their own work and in the other to pull partners into a more collaborative stance. Learning experiences developed in each city as a result of the dissemination reflected these differences in the city-specific emphasis with the push city diving into messy examples of the approach to make their own examples, and the pull city offering polished experiences to partners in order to build confidence in the climate change messaging. The networks themselves underwent different kinds of growth and change as a result of dissemination. The emphasis on push and use of messy examples resulted in active use of the principles of the approach and the pull emphasis with polished examples resulted in the cultivation of partnerships with the hub and the potential to engage in the educational approach. These findings have implications for boundary object theory as a useful grounding for dissemination designs in the context of networks of informal learning organizations to support a shift in communication approach, particularly when developing interventions for wicked socio-scientific issues such as climate change.

An Actor-Network Theory Analysis of Policy Innovation for Smoke-Free Places: Understanding Change in Complex Systems

PubMed Central

Borland, Ron; Coghill, Ken

2010-01-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems. PMID:20466949

An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

PubMed

Young, David; Borland, Ron; Coghill, Ken

2010-07-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems.

Interdisciplinarity and Knowledge Networking: Co-Production of Climate-Authoritative Knowledge in Southern South America

ERIC Educational Resources Information Center

Hidalgo, Cecilia

2016-01-01

Interdisciplinarity and knowledge networking are at the core of current global, regional, and national initiatives concerning climate. Both scientifc knowledge and public participation are essential to enhance the capacity of different sectors and governments to respond to challenges posed by climate variability and change. Exchange and bridge…

Responses to Climate Change: Exploring Organisational Learning across Internationally Networked Organisations for Development

ERIC Educational Resources Information Center

Boyd, Emily; Osbahr, Henny

2010-01-01

Drawing from the organisational learning and governance literature, this paper assesses four internationally networked governmental and non-governmental organisations in the UK addressing climate change. We analyse how those concerned understand the climate change crisis, what mechanisms are put in place to address information flows, and what…

The MedCLIVAR Network

NASA Astrophysics Data System (ADS)

Lionello, Piero; Medclivar Sc, The

2014-05-01

MedCLIVAR serves as a scientific network to promote interaction among different scientific disciplines and to develop a multidisciplinary vision of the evolution of the Mediterranean climate through studies that integrate atmospheric, marine, and terrestrial climate components at time scales ranging from paleoreconstructions to future climate scenarios. The network deals with scientific issues including past climate variability; connections between the Mediterranean and global climate; the Mediterranean Sea circulation and sea level; feedbacks on the global climate system; and regional responses to greenhouse gas, air pollution, and aerosols. The MedCLIVAR initiative was proposed at the 2003 European Geosciences Union assembly in Nice, France. In 2005, it was endorsed by the International Climate Variability and Predictability (CLIVAR) office. Subsequently, the MedCLIVAR Research Network Project was formally approved by the European Science Foundation and launched in May 2006 for a five year duration. Now MedCLIVAR is continuing with self supporting initiatives, such as the third MedCLIVAR conference, which will be held in June 2014 in Ankara (Turkey) , the publication of a special issue of Regional Environmental Change devoted to the climate of the Mediterranean region, and a newsletter, which is published every six months. More information available in Lionello, P., Gacic, M., Gomis, D., Garcia-Herrera, R., Giorgi, F., Planton, S., Trigo, R., (...), Xoplaki, E. (2012) Program focuses on climate of the Mediterranean region, Eos Trans. AGU 93:105-106

Overland flow erosion inferred from Martian channel network geometry

NASA Astrophysics Data System (ADS)

Seybold, Hansjörg; Kirchner, James

2016-04-01

The controversy about the origin of Mars' channel networks is almost as old as their discovery 150 years ago. Over the last few decades, new Mars probes have revealed more detailed structures in Martian The controversy about the origin of Mars' channel networks is almost as old as their discovery 150 years ago. Over the last few decades, new Mars probes have revealed more detailed structures in Martian drainage networks, and new studies suggest that Mars once had large volumes of surface water. But how this water flowed, and how it could have carved the channels, remains unclear. Simple scaling arguments show that networks formed by similar mechanisms should have similar branching angles on Earth and Mars, suggesting that Earth analogues can be informative here. A recent analysis of high-resolution data for the continental United States shows that climate leaves a characteristic imprint in the branching geometry of stream networks. Networks growing in humid regions have an average branching angle of α = 2π/5 = 72° [1], which is characteristic of network growth by groundwater sapping [2]. Networks in arid regions, where overland flow erosion is more dominant, show much smaller branching angles. Here we show that the channel networks on Mars have branching angles that resemble those created by surficial flows on Earth. This result implies that the growth of Martian channel networks was dominated by near-surface flow, and suggests that deeper infiltration was inhibited, potentially by permafrost or by impermeable weathered soils. [1] Climate's Watermark in the Geometry of River Networks, Seybold et al.; under review [2] Ramification of stream networks, Devauchelle et al.; PNAS (2012)

Effects of Nitrogen Inputs on Freshwater Wetland Ecosystem Services–A Bayesian Network Analysis

EPA Science Inventory

Wetlands can provide a balance between regulating water quality and one aspect of mitigating climate change, by reducing the quantity of reactive nitrogen (Nr) reaching downstream receiving water bodies, while emitting negligible amounts of nitrous oxide (N2O) during incomplete d...

Spatial and Climate Literacy: Connecting Urban and Rural Students

NASA Astrophysics Data System (ADS)

Boger, R. A.; Low, R.; Mandryk, C.; Gorokhovich, Y.

2013-12-01

Through a collaboration between the University of Nebraska-Lincoln (UNL), Brooklyn College, and Lehman College, four independent but linked modules were developed and piloted in courses offered at Brooklyn College and UNL simultaneously. Module content includes climate change science and literacy principles, using geospatial technologies (GIS, GPS and remote sensing) as a vehicle to explore issues associated with global, regional, and local climate change in a concrete, quantitative and visual way using Internet resources available through NASA, NOAA, USGS, and a variety of universities and organizations. The materials take an Earth system approach and incorporate sustainability, resilience, water and watersheds, weather and climate, and food security topics throughout the semester. The research component of the project focuses on understanding the role of spatial literacy and authentic inquiry based experiences in climate change understanding and improving confidence in teaching science. In particular, engaging learners in both climate change science and GIS simultaneously provides opportunities to examine questions about the role that data manipulation, mental representation, and spatial literacy plays in students' abilities to understand the consequences and impacts of climate change. Pre and post surveys were designed to discern relationships between spatial cognitive processes and effective acquisition of climate change science concepts in virtual learning environments as well as alignment of teacher's mental models of nature of science and climate system dynamics to scientific models. The courses will again be offered simultaneously in Spring 2014 at Brooklyn College and UNL. Evaluation research will continue to examine the connections between spatial and climate literacy and teacher's mental models (via qualitative textual analysis using MAXQDA text analysis, and UCINET social network analysis programs) as well as how urban-rural learning interactions may influence climate literacy.

Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

NASA Astrophysics Data System (ADS)

Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.

2017-12-01

Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.

Framework for a hydrologic climate-response network in New England

USGS Publications Warehouse

Lent, Robert M.; Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

2015-01-01

Many climate-related hydrologic variables in New England have changed in the past century, and many are expected to change during the next century. It is important to understand and monitor these changes because they can affect human water supply, hydroelectric power generation, transportation infrastructure, and stream and riparian ecology. This report describes a framework for hydrologic monitoring in New England by means of a climate-response network. The framework identifies specific inland hydrologic variables that are sensitive to climate variation; identifies geographic regions with similar hydrologic responses; proposes a fixed-station monitoring network composed of existing streamflow, groundwater, lake ice, snowpack, and meteorological data-collection stations for evaluation of hydrologic response to climate variation; and identifies streamflow basins for intensive, process-based studies and for estimates of future hydrologic conditions.

Towards low carbon based economic development: Shanghai as a C40 city.

PubMed

Li, Zhijie; Galeano Galván, María José; Ravesteijn, Wim; Qi, Zhongying

2017-01-15

As a result of its rapid industrialization process, China has become the greatest emitter of carbon dioxide world-wide. Consequently, Shanghai - the most industrialized city in China - is facing serious challenges arising from carbon emissions and climate change in general. The main question of this paper is: How can Shanghai continue its economic growth, while controlling the negative consequences of its energy use and production in a responsible way? For the approach, it explores the use of the C40 framework, as an application and specification of new synergy seeking approaches, such as Value Sensitive Design. The C40 Cities Climate Leadership Group is a global city-level network to address climate change and promote world-class projects to reduce greenhouse gas emissions. In this paper, a quantitative analysis of Shanghai's energy trends is made as well as a SWOT analysis to map and evaluate its current environmental, social, economic and political characteristics. Three main challenges are presented, related to institutional inclusiveness, global relations, and long-term innovation. In view of the initiatives, targets, and the whole network of the C40 movement, this paper concludes that Shanghai is strongly recommended to fully use the C40 framework in creating a sustainable and responsible future. Copyright © 2016 Elsevier B.V. All rights reserved.

Building a stakeholder network for the Indiana Climate Change Impacts Assessment

NASA Astrophysics Data System (ADS)

Dukes, J. S.; Widhalm, M.

2017-12-01

The Indiana Climate Change Impacts Assessment (IN CCIA) is a stakeholder-informed, service-driven resource developed under the coordination of the Purdue Climate Change Research Center (PCCRC) and with involvement from a diverse mix of contributors throughout the state. The IN CCIA brings together the best available climate change research into a series of reports aimed at helping Hoosiers better understand climate change-related risks so they can prepare for challenges and capitalize on opportunities. The IN CCIA development process aims to 1) increase the dialogue about climate change across the state, 2) provide Indiana decision makers with accessible, credible climate impact information, and 3) build a network of experts and stakeholders to support ongoing assessment efforts and knowledge sharing. This presentation will report on our experience with developing and maintaining a diverse stakeholder network. We will describe our efforts to connect with stakeholders before, during, and after the development of assessment reports and share the top themes that emerged from our pre-assessment inquires and other interactions.

Effects of climate change and wildfire on stream temperatures and salmonid thermal habitat in a mountain river network

Treesearch

Daniel J. Isaak; Charles H. Luce; Bruce E. Rieman; David E. Nagel; Erin E. Peterson; Dona L. Horan; Sharon Parkes; Gwynne L. Chandler

2010-01-01

Mountain streams provide important habitats for many species, but their faunas are especially vulnerable to climate change because of ectothermic physiologies and movements that are constrained to linear networks that are easily fragmented. Effectively conserving biodiversity in these systems requires accurate downscaling of climatic trends to local habitat conditions...

Navigating future uncertainty in marine protected area governance: Lessons from the Scottish MPA network

NASA Astrophysics Data System (ADS)

Hopkins, Charlotte Rachael; Bailey, David Mark; Potts, Tavis

2018-07-01

As international pressure for marine protection has increased, Scotland has increased spatial protection through the development of a Marine Protected Area (MPA) network. Few MPA networks to date have included specific considerations of climate change in the design, monitoring or management of the network. The Scottish MPA network followed a feature-led approach to identify a series of MPAs across the Scottish marine area and incorporated the diverse views of many different stakeholders. This feature led approach has led to wide ranging opinions and understandings regarding the success of the MPA network. Translating ideas of success into a policy approach whilst also considering how climate change may affect these ideas of success is a complex challenge. This paper presents the results of a Delphi process that aimed to facilitate clear communication between academics, policy makers and stakeholders in order to identify specific climate change considerations applicable to the Scottish MPA network. This study engaged a group of academic and non-academic stakeholders to discuss potential options that could be translated into an operational process for management of the MPA network. The results of Delphi process discussion are presented with the output of a management matrix tool, which could aid in future decisions for MPA management under scenarios of climate change.

SE Asian freshwater fish population and networks: the impacts of climatic and environmental change on a vital resource

NASA Astrophysics Data System (ADS)

Santos, Rita; Parsons, Daniel; Cowx, Ian

2016-04-01

The Mekong River is the 10th largest freshwater river in the world, with the second highest biodiversity wealth, behind the much larger Amazon basin. The fisheries activity in the Lower Mekong countries counts for 2.7 million tons of fish per year, with an estimated value worth up to US 7 billion. For the 60 million people living in the basin, fish represent their primary source of economic income and protein intake, with an average per capita consumption estimated at 45.4 Kg. The proposed hydropower development in the basin is threatening its sustainability and resilience. Such developments affect fish migration patterns, hydrograph flood duration and magnitudes and sediment flux. Climate change is also likely to impact the basin, exacerbating the issues created by development. As a monsoonal system, the Mekong River's pronounced annual flood pulse cycle is important in creating variable habitat for fish productivity. Moreover, the annual flood also triggers fish migration and provides vital nutrients carried by the sediment flux. This paper examines the interactions between both dam development and climate change scenarios on fish habitat and habitat connectivity, with the aim of predicting how these will affect fish species composition and fisheries catch. The project will also employ Environmental DNA (eDNA) to quantify and understand the species composition of this complex and large freshwater system. By applying molecular analysis, it is possible to trace species abundance and migration patterns of fish and evaluate the ecological networks establish between an inland system. The aim of this work is to estimate, using process-informed models, the impacts of the proposed dam development and climate change scenarios on the hydrological and hydraulic conditions of habitat availability for fish. Furthermore, it will evaluate the connectivity along the Mekong and its tributaries, and the importance of maintaining these migration pathways, used by a great diversity of fish species. It will also present the preliminary findings on eDNA analysis for species composition and the ecological networks established along the river and particularly on the fish hotspot place for biodiversity, the Tonle Sap system in Cambodia. Keywords: Mekong River, climate change, fish production, dams, eDNA analysis, numerical modelling.

The Potential Connectivity of Waterhole Networks and the Effectiveness of a Protected Area under Various Drought Scenarios

PubMed Central

O’Farrill, Georgina; Gauthier Schampaert, Kim; Rayfield, Bronwyn; Bodin, Örjan; Calmé, Sophie; Sengupta, Raja; Gonzalez, Andrew

2014-01-01

Landscape connectivity is considered a priority for ecosystem conservation because it may mitigate the synergistic effects of climate change and habitat loss. Climate change predictions suggest changes in precipitation regimes, which will affect the availability of water resources, with potential consequences for landscape connectivity. The Greater Calakmul Region of the Yucatan Peninsula (Mexico) has experienced a 16% decrease in precipitation over the last 50 years, which we hypothesise has affected water resource connectivity. We used a network model of connectivity, for three large endangered species (Baird’s tapir, white-lipped peccary and jaguar), to assess the effect of drought on waterhole availability and connectivity in a forested landscape inside and adjacent to the Calakmul Biosphere Reserve. We used reported travel distances and home ranges for our species to establish movement distances in our model. Specifically, we compared the effects of 10 drought scenarios on the number of waterholes (nodes) and the subsequent changes in network structure and node importance. Our analysis revealed that drought dramatically influenced spatial structure and potential connectivity of the network. Our results show that waterhole connectivity and suitable habitat (area surrounding waterholes) is lost faster inside than outside the reserve for all three study species, an outcome that may drive them outside the reserve boundaries. These results emphasize the need to assess how the variability in the availability of seasonal water resource may affect the viability of animal populations under current climate change inside and outside protected areas. PMID:24830392

The potential connectivity of waterhole networks and the effectiveness of a protected area under various drought scenarios.

PubMed

O'Farrill, Georgina; Gauthier Schampaert, Kim; Rayfield, Bronwyn; Bodin, Örjan; Calmé, Sophie; Sengupta, Raja; Gonzalez, Andrew

2014-01-01

Landscape connectivity is considered a priority for ecosystem conservation because it may mitigate the synergistic effects of climate change and habitat loss. Climate change predictions suggest changes in precipitation regimes, which will affect the availability of water resources, with potential consequences for landscape connectivity. The Greater Calakmul Region of the Yucatan Peninsula (Mexico) has experienced a 16% decrease in precipitation over the last 50 years, which we hypothesise has affected water resource connectivity. We used a network model of connectivity, for three large endangered species (Baird's tapir, white-lipped peccary and jaguar), to assess the effect of drought on waterhole availability and connectivity in a forested landscape inside and adjacent to the Calakmul Biosphere Reserve. We used reported travel distances and home ranges for our species to establish movement distances in our model. Specifically, we compared the effects of 10 drought scenarios on the number of waterholes (nodes) and the subsequent changes in network structure and node importance. Our analysis revealed that drought dramatically influenced spatial structure and potential connectivity of the network. Our results show that waterhole connectivity and suitable habitat (area surrounding waterholes) is lost faster inside than outside the reserve for all three study species, an outcome that may drive them outside the reserve boundaries. These results emphasize the need to assess how the variability in the availability of seasonal water resource may affect the viability of animal populations under current climate change inside and outside protected areas.

Climate Controls on Tree Growth in the Western Mediterranean

NASA Technical Reports Server (NTRS)

Touchan, Ramzi; Anchukaitis, Kevin J.; Meko, David M.; Kerchouche, Dalila; Slimani, Said; Ilmen, Rachid; Hasnaoui, Fouad; Guibal, Frederic; Canarerim Hesys Hykui; Sanchez-Salguero, Raul;

Oak tree-ring chronologies - an instrument to estimate Carpathians role to separate climate influence in Northern Romania

NASA Astrophysics Data System (ADS)

Constantin, Nechita; Ionel, Popa; Francisca, Chiriloaei

2017-04-01

Actual climate conditions are in permanent changes and trees can provide information on the magnitude of current modifications compared with the past. Through dendrochronological methods we have analyzed a network composed of 17 chronologies belonging to the Quercus genus to highlight the role of macro-climate induced by the major landforms in printing a specific growth response pattern to climate. The transect is located in North Romania following a straight line of about 400 km length, crossing the Carpathian Arch. The aim of this study is to highlight the areas with homogenous response of trees to the climatic factors. This fact is important for building long dendrochronological series considering that it is appreciated reduced scale applicability. It is known that in the study area covered with oak-trees the number of long series used for climate reconstructions is reduced. The material used is represented by the dendrochronological series which were sampled according to the standards accepted by the scientific literature. The statistical methods used consist in employing PCA analysis to highlight the spatial segregation, related to PC1 scores. Also hierarchical cluster analysis (HCA) was applied in order to group the series with common features on basis of similarities/dissimilarities. The Euclidian distance between the chronologies was calculated and sampled areas were grouped according to Ward minimum variance method. In addition we performed a redundancy analysis (RDA) which the ordination of the axes it is a linear combination of supplied environmental variables. The correlation analysis with climate factors was accomplished by using bootstrap correlation. The pointer year analysis (the selection criteria is PC1 scores <-0.5) was also performed. The results were related to the postglacial recolonization routes obtained by analyzing the chloroplast DNA.

Globalization to amplify economic climate losses

NASA Astrophysics Data System (ADS)

Otto, C.; Wenz, L.; Levermann, A.

2015-12-01

Economic welfare under enhanced anthropogenic carbon emissions and associated future warming poses a major challenge for a society with an evolving globally connected economy. Unabated climate change will impact economic output for example through heat-stress-related reductions in productivity. Since meteorologically-induced production reductions can propagate along supply chains, structural changes in the economic network may influence climate-related losses. The role of the economic network evolution for climate impacts has been neither quantified nor qualitatively understood. Here we show that since the beginning of the 21st century the structural change of the global supply network has been such that an increase of spillover losses due to unanticipated climatic events has to be expected. We quantify primary, secondary and higher-order losses from reduced labor productivity under past and present economic and climatic conditions and find that indirect losses are significant and increase with rising temperatures. The connectivity of the economic network has increased in such a way as to foster the propagation of production loss. This supply chain connectivity robustly exhibits the characteristic distribution of self-organized criticality which has been shifted towards higher values since 2001. Losses due to this structural evolution dominated over the effect of comparably weak climatic changes during this decade. Our finding suggests that the current form of globalization may amplify losses due to climatic extremes and thus necessitate structural adaptation that requires more foresight than presently prevalent.

GCOS reference upper air network (GRUAN): Steps towards assuring future climate records

NASA Astrophysics Data System (ADS)

Thorne, P. W.; Vömel, H.; Bodeker, G.; Sommer, M.; Apituley, A.; Berger, F.; Bojinski, S.; Braathen, G.; Calpini, B.; Demoz, B.; Diamond, H. J.; Dykema, J.; Fassò, A.; Fujiwara, M.; Gardiner, T.; Hurst, D.; Leblanc, T.; Madonna, F.; Merlone, A.; Mikalsen, A.; Miller, C. D.; Reale, T.; Rannat, K.; Richter, C.; Seidel, D. J.; Shiotani, M.; Sisterson, D.; Tan, D. G. H.; Vose, R. S.; Voyles, J.; Wang, J.; Whiteman, D. N.; Williams, S.

2013-09-01

The observational climate record is a cornerstone of our scientific understanding of climate changes and their potential causes. Existing observing networks have been designed largely in support of operational weather forecasting and continue to be run in this mode. Coverage and timeliness are often higher priorities than absolute traceability and accuracy. Changes in instrumentation used in the observing system, as well as in operating procedures, are frequent, rarely adequately documented and their impacts poorly quantified. For monitoring changes in upper-air climate, which is achieved through in-situ soundings and more recently satellites and ground-based remote sensing, the net result has been trend uncertainties as large as, or larger than, the expected emergent signals of climate change. This is more than simply academic with the tropospheric temperature trends issue having been the subject of intense debate, two international assessment reports and several US congressional hearings. For more than a decade the international climate science community has been calling for the instigation of a network of reference quality measurements to reduce uncertainty in our climate monitoring capabilities. This paper provides a brief history of GRUAN developments to date and outlines future plans. Such reference networks can only be achieved and maintained with strong continuing input from the global metrological community.

Meteorological, environmental remote sensing and neural network analysis of the epidemiology of malaria transmission in Thailand.

PubMed

Kiang, Richard; Adimi, Farida; Soika, Valerii; Nigro, Joseph; Singhasivanon, Pratap; Sirichaisinthop, Jeeraphat; Leemingsawat, Somjai; Apiwathnasorn, Chamnarn; Looareesuwan, Sornchai

2006-11-01

In many malarious regions malaria transmission roughly coincides with rainy seasons, which provide for more abundant larval habitats. In addition to precipitation, other meteorological and environmental factors may also influence malaria transmission. These factors can be remotely sensed using earth observing environmental satellites and estimated with seasonal climate forecasts. The use of remote sensing usage as an early warning tool for malaria epidemics have been broadly studied in recent years, especially for Africa, where the majority of the world's malaria occurs. Although the Greater Mekong Subregion (GMS), which includes Thailand and the surrounding countries, is an epicenter of multidrug resistant falciparum malaria, the meteorological and environmental factors affecting malaria transmissions in the GMS have not been examined in detail. In this study, the parasitological data used consisted of the monthly malaria epidemiology data at the provincial level compiled by the Thai Ministry of Public Health. Precipitation, temperature, relative humidity, and vegetation index obtained from both climate time series and satellite measurements were used as independent variables to model malaria. We used neural network methods, an artificial-intelligence technique, to model the dependency of malaria transmission on these variables. The average training accuracy of the neural network analysis for three provinces (Kanchanaburi, Mae Hong Son, and Tak) which are among the provinces most endemic for malaria, is 72.8% and the average testing accuracy is 62.9% based on the 1994-1999 data. A more complex neural network architecture resulted in higher training accuracy but also lower testing accuracy. Taking into account of the uncertainty regarding reported malaria cases, we divided the malaria cases into bands (classes) to compute training accuracy. Using the same neural network architecture on the 19 most endemic provinces for years 1994 to 2000, the mean training accuracy weighted by provincial malaria cases was 73%. Prediction of malaria cases for 2001 using neural networks trained for 1994-2000 gave a weighted accuracy of 53%. Because there was a significant decrease (31%) in the number of malaria cases in the 19 provinces from 2000 to 2001, the networks overestimated malaria transmissions. The decrease in transmission was not due to climatic or environmental changes. Thailand is a country with long borders. Migrant populations from the neighboring countries enlarge the human malaria reservoir because these populations have more limited access to health care. This issue also confounds the complexity of modeling malaria based on meteorological and environmental variables alone. In spite of the relatively low resolution of the data and the impact of migrant populations, we have uncovered a reasonably clear dependency of malaria on meteorological and environmental remote sensing variables. When other contextual determinants do not vary significantly, using neural network analysis along with remote sensing variables to predict malaria endemicity should be feasible.

Vulnerability of Thai rice production to simultaneous climate and socioeconomic changes: a double exposure analysis

NASA Astrophysics Data System (ADS)

Sangpenchan, R.

2011-12-01

This research explores the vulnerability of Thai rice production to simultaneous exposure by climate and socioeconomic change -- so-called "double exposure." Both processes influence Thailand's rice production system, but the vulnerabilities associated with their interactions are unknown. To understand this double exposure, I adopts a mixed-method, qualitative-quantitative analytical approach consisting of three phases of analysis involving a Vulnerability Scoping Diagram, a Principal Component Analysis, and the EPIC crop model using proxy datasets collected from secondary data sources at provincial scales.The first and second phases identify key variables representing each of the three dimensions of vulnerability -- exposure, sensitivity, and adaptive capacity indicating that the greatest vulnerability in the rice production system occurs in households and areas with high exposure to climate change, high sensitivity to climate and socioeconomic stress, and low adaptive capacity. In the third phase, the EPIC crop model simulates rice yields associated with future climate change projected by CSIRO and MIROC climate models. Climate change-only scenarios project the decrease in yields by 10% from the current productivity during 2016-2025 and 30% during 2045-2054. Scenarios applying both climate change and improved technology and management practices show that a 50% increase in rice production is possible, but requires strong collaboration between sectors to advance agricultural research and technology and requires strong adaptive capacity in the rice production system characterized by well-developed social capital, social networks, financial capacity, and infrastructure and household mobility at the local scale. The vulnerability assessment and climate and crop adaptation simulations used here provide useful information to decision makers developing vulnerability reduction plans in the face of concurrent climate and socioeconomic change.

Global Change Network: Combine Nutrient Network and Drought Net in China

NASA Astrophysics Data System (ADS)

Yu, Q.; Wang, C.; Zhu, J.; Xu, X.; Yang, H.; Wei, C.; Cong, N.; Wu, H.; Li, H.; Tian, D.; An, H.; Yu, G.

2017-12-01

Globally, all ecosystems will be impacted to some extent by changes in climate means and more frequent and severe periods of climatic extremes. Although there have been numerous studies examining the effects of changes in climatic means on ecological processes and ecosystems, research on climate extremes is far less common and is only now emerging as a distinct research field in ecology. Furthermore, although we have learned much in the past 20 years about how individual ecosystems are likely to respond to climate change, extending this knowledge to regional and continental scales has been a far greater challenge because of the inconsistent design of experiments and ecological complexity. In order to better forecast how entire regions will respond to eutrophication and extreme drought, two key network has been set up, i.e. Nutrient Network, Drought Net. However, there were few sites in China in the network studies, where locates Eurasian Steppe (the biggest grassland in the world) and Tibetan Plateau grassland (the world's highest and largest plateau grassland). To fill the great gap, we have set up ten sites in China (including 5 sites in Eurasia Steppe and 5 site in Tibetan Plateau), combing Nutrient Network and Drought Net treatments and also increased precipitation, called Global Change Network. There are 16 treatments with 6 repeats, and thus 96 plots in the global change network. The nutrient addition treatments are the same with Nutrient Network, i.e. 10 treatments. Precipitation change treatments include an extreme drought (the same with Drought Net) and a water addition (the amount is the same with drought treatment) treatment. The interactive treatments were only conducted in control N and NPK.

Controls on stream network branching angles, tested using landscape evolution models

NASA Astrophysics Data System (ADS)

Theodoratos, Nikolaos; Seybold, Hansjörg; Kirchner, James W.

2016-04-01

Stream networks are striking landscape features. The topology of stream networks has been extensively studied, but their geometry has received limited attention. Analyses of nearly 1 million stream junctions across the contiguous United States [1] have revealed that stream branching angles vary systematically with climate and topographic gradients at continental scale. Stream networks in areas with wet climates and gentle slopes tend to have wider branching angles than in areas with dry climates or steep slopes, but the mechanistic linkages underlying these empirical correlations remain unclear. Under different climatic and topographic conditions different runoff generation mechanisms and, consequently, transport processes are dominant. Models [2] and experiments [3] have shown that the relative strength of channel incision versus diffusive hillslope transport controls the spacing between valleys, an important geometric property of stream networks. We used landscape evolution models (LEMs) to test whether similar factors control network branching angles as well. We simulated stream networks using a wide range of hillslope diffusion and channel incision parameters. The resulting branching angles vary systematically with the parameters, but by much less than the regional variability in real-world stream networks. Our results suggest that the competition between hillslope and channeling processes influences branching angles, but that other mechanisms may also be needed to account for the variability in branching angles observed in the field. References: [1] H. Seybold, D. H. Rothman, and J. W. Kirchner, 2015, Climate's watermark in the geometry of river networks, Submitted manuscript. [2] J. T. Perron, W. E. Dietrich, and J. W. Kirchner, 2008, Controls on the spacing of first-order valleys, Journal of Geophysical Research, 113, F04016. [3] K. E. Sweeney, J. J. Roering, and C. Ellis, 2015, Experimental evidence for hillslope control of landscape scale, Science, 349(6243), 51-53.

Building National Capacity for Climate Change Interpretation: The Role of Leaders, Partnerships, and Networks

NASA Astrophysics Data System (ADS)

Spitzer, W.

2015-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. Our project represents a cross-disciplinary partnership among climate scientists, social and cognitive scientists, and informal education practitioners. We have built a growing national network of more than 250 alumni, including approximately 15-20 peer leaders who co-lead both in-depth training programs and introductory workshops. We have found that this alumni network has been assuming increasing importance in providing for ongoing learning, support for implementation, leadership development, and coalition building. As we look toward the future, we are exploring potential partnerships with other existing networks, both to sustain our impact and to expand our reach. This presentation will address what we have learned in terms of network impacts, best practices, factors for success, and future directions.

Diagnosing climate change impacts and identifying adaptation strategies by involving key stakeholder organisations and farmers in Sikkim, India: Challenges and opportunities.

PubMed

Azhoni, Adani; Goyal, Manish Kumar

2018-06-01

Narrowing the gap between research, policy making and implementing adaptation remains a challenge in many parts of the world where climate change is likely to severely impact water security. This research aims to narrow this gap by matching the adaptation strategies being framed by policy makers to that of the perspectives of development agencies, researchers and farmers in the Himalayan state of Sikkim in India. Our case study examined the perspectives of various stakeholders for climate change impacts, current adaptation strategies, knowledge gaps and adaptation barriers, particularly in the context of implementing the Sikkim State Action Plan on Climate Change through semi-structured interviews carried out with decision makers in the Sikkim State Government, researchers, consultants, local academia, development agencies and farmers. Using Stakeholders Network Analysis tools, this research unravels the complexities of perceiving climate change impacts, identifying strategies, and implementing adaptation. While farmers are less aware about the global phenomenon of climate change impacts for water security, their knowledge of the local conditions and their close interaction with the State Government Agriculture Department provides them opportunities. Although important steps are being initiated through the Sikkim State Action Plan on Climate Change it is yet to deliver effective means of adaptation implementation and hence, strengthening the networks of close coordination between the various implementing agencies will pay dividends. Knowledge gaps and the need for capacity building identified in this research, based on the understandings of key stakeholders are highly relevant to both the research community and for informing policy. Copyright © 2018 Elsevier B.V. All rights reserved.

The Climate Voices Speakers Network: Collaborating with Nontraditional, National Networks to Develop Climate Literacy on a Local Level

NASA Astrophysics Data System (ADS)

Wegner, K.; Schmidt, C.; Herrin, S.

2015-12-01

How can we leverage the successes of the numerous organizations in the climate change communication arena to build momentum rather than reinvent the wheel? Over the past two years, Climate Voices (climatevoices.org) has established a network of nearly 400 speakers and established partnerships to scale programs that address climate change communication and community engagement. In this presentation, we will present how we have identified and fostered win-win partnerships with organizations, such as GreenFaith Interfaith Partners for the Environment and Rotary International, to reach the broader general public. We will also share how, by drawing on the resources from the National Climate Assessment and the expertise of our own community, we developed and provided our speakers the tools to provide their audiences access to basic climate science - contributing to each audience's ability to understand local impacts, make informed decisions, and gain the confidence to engage in solutions-based actions in response to climate change. We will also discuss how we have created webinar coaching presentations by speakers who aren't climate scientists- and why we have chosen to do so.

Comparison Of In Situ Soil Moisture Measurements: An Examination of the Neutron and Dielectric Measurements within the Illinois Climate Network

USDA-ARS?s Scientific Manuscript database

The continuity of soil moisture time series data is crucial for climatic research. Yet, a common problem for continuous data series is the changing of sensors, not only as replacements are necessary, but as technologies evolve. The Illinois Climate Network has one of the longest data records of soi...

United Kingdom Deriving Emissions linked to Climate Change Network: greenhouse gas and ozone depleting substance measurements from a UK network of tall towers

NASA Astrophysics Data System (ADS)

Stanley, Kieran; O'Doherty, Simon; Young, Dickon; Grant, Aoife; Manning, Alistair; Simmonds, Peter; Oram, Dave; Sturges, Bill; Derwent, Richard

2016-04-01

Real-time, high-frequency measurement networks are essential for investigating the emissions of gases linked with climate change and stratospheric ozone depletion. These networks can be used to verify greenhouse gas (GHG) and ozone depleting substances (ODS) emission inventories for the Kyoto and Montreal Protocols. Providing accurate and reliable country- and region-specific emissions to the atmosphere are critical for reporting to the UN agencies. The United Kingdom Deriving Emissions linked to Climate Change (UK DECC) Network, operating since 2012, is distinguished by its capability to measure at high-frequency, the influence of all of the important species in the Kyoto and Montreal Protocols from the UK, Ireland and Continental Europe. Data obtained from the UK DECC network are also fed into the European Integrated Carbon Observation System (ICOS). This presentation will give an overview of the UK DECC Network, detailing the analytical techniques used to determine the suite of GHGs and ODSs, as well as the calibration strategy used within the network. Interannual results of key GHGs from the network will also be presented.

Enhancing the Extreme Climate Index (ECI) to monitor climate extremes for an index-based insurance scheme across Africa

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Malherbe, J.; Chamunorwa, M.; Muthige, M.; Petitta, M.; Calmanti, S.; Cucchi, M.; Syroka, J.; Iyahen, E.; Engelbrecht, F.

2017-12-01

Climate services are a key component of National Adaptation Plan (NAP) processes, which require the analysis of current climate conditions, future climate change scenarios and the identification of adaptation strategies, including the capacity to finance and implement effective adaptation options. The Extreme Climate Facility (XCF) proposed by the African Risk Capacity (ARC) developed a climate index insurance scheme, which is based on the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events, thus indicating possible shifts to a new climate regime in various regions. The main hazards covered by ECI are extreme dry, wet and heat events, with the possibility of adding other region-specific risk events. The ECI is standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be compared. Initially developed by an Italian company specialized in Climate Services, research is now conducted at the CSIR and SASSCAL, to verify and further develop the ECI for application in southern African countries, through a project initiated by the World Food Programme (WFP) and ARC. The paper will present findings on the most appropriate definitions of extremely wet and dry conditions in Africa, in terms of their impact across a multitude of sub-regional climates of the African continent. Findings of a verification analysis of the ECI, as determined through vegetation monitoring data and the SASSCAL weather station network will be discussed. Changes in the ECI under climate change will subsequently be projected, using detailed regional projections generated by the CSIR and through the Coordinated Regional Downscaling Experiment (CORDEX). This work will be concluded by the development of a web-based climate service informing African Stakeholders on climate extremes.

Detecting climate variations and change: New challenges for observing and data management systems

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

Karl, T.R.; Quayle, R.G.; Groisman, P.Ya.

1993-08-01

Several essential aspects of weather observing and the management of weather data related to improving knowledge of climate variations and change in the surface boundary layer and the consequences for socioeconomic and biogeophysical systems, are discussed. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems. Although much has been learned from existing weather networks and methods of data management, the system is far frommore » perfect. Several vital areas have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changes are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food. 58 refs., 8 figs., 1 tab.« less

Formation of Valley Networks in a Cold and Icy Early Mars Climate: Predictions for Erosion Rates and Channel Morphology

NASA Astrophysics Data System (ADS)

Cassanelli, J.

2017-12-01

Mars is host to a diverse array of valley networks, systems of linear-to-sinuous depressions which are widely distributed across the surface and which exhibit branching patterns similar to the dendritic drainage patterns of terrestrial fluvial systems. Characteristics of the valley networks are indicative of an origin by fluvial activity, providing among the most compelling evidence for the past presence of flowing liquid water on the surface of Mars. Stratigraphic and crater age dating techniques suggest that the formation of the valley networks occurred predominantly during the early geologic history of Mars ( 3.7 Ga). However, whether the valley networks formed predominantly by rainfall in a relatively warm and wet early Mars climate, or by snowmelt and episodic rainfall in an ambient cold and icy climate, remains disputed. Understanding the formative environment of the valley networks will help distinguish between these warm and cold end-member early Mars climate models. Here we test a conceptual model for channel incision and evolution under cold and icy conditions with a substrate characterized by the presence of an ice-free dry active layer and subjacent ice-cemented regolith, similar to that found in the Antarctic McMurdo Dry Valleys. We implement numerical thermal models, quantitative erosion and transport estimates, and morphometric analyses in order to outline predictions for (1) the precise nature and structure of the substrate, (2) fluvial erosion/incision rates, and (3) channel morphology. Model predictions are compared against morphologic and morphometric observational data to evaluate consistency with the assumed cold climate scenario. In the cold climate scenario, the substrate is predicted to be characterized by a kilometers-thick globally-continuous cryosphere below a 50-100 meter thick desiccated ice-free zone. Initial results suggest that, with the predicted substrate structure, fluvial channel erosion and morphology in a cold early Mars climate exposed to episodic high temperatures will not differ significantly from that in a warm climate. The fundamentally different hydrologic conditions are likely to influence other aspects of valley network morphology and morphometry including: drainage density, drainage pattern, and stream orders.

A CLEAN Network Initiative - Accelerating Transition to Post Carbon and Resilient Communities through Education and Engagement

NASA Astrophysics Data System (ADS)

Ledley, T. S.; Niepold, F., III; Bozuwa, J.; Davis, A.; Fraser, J.; Kretser, J.; Poppleton, K. L. I.; Qusba, L.; Ruggiero, K.; Spitzer, W.; Stylinski, C.

2016-12-01

The Climate Literacy and Energy Awareness Network (CLEAN) was formed in 2008 to help climate and energy literacy stakeholders implement the Climate and Energy Literacy Essential Principles to enable effective and responsible decisions with regard to actions that may affect climate. The ongoing conversations of the CLEAN Network have cultivated a culture of shared resources and expertise and allowed for the development of collective impact strategies. However, it has become clear that to accelerate and scale change, effective mitigation, adaptation, and resilience strategies must be developed by a diverse network of stakeholders at the community level to deal with the local impacts of climate change and move toward decarbonized and resilient economies. A group of CLEAN Network members, experienced in establishing effective networks and representing mature climate change education programs, came together to discuss at the community level 1) how we can collectively enable larger scale efforts to 2) develop effective strategies, 3) identify gaps in the system that limit action, and 4) coordinate possible vectors for interceding to advance community level decisions related to climate. We will describe our Theory of Change, based on both the power of communities and increasing climate literacy as a key requirement for sustained progress on the crisis climate change presents. From our Theory of Change, we have begun to outline a national monitoring strategy that can provide communities a measured way to understand their local readiness to respond to the impacts of climate change and understand the magnitude of those impacts in relation to their political and ecological economies. The scale would help describe the robustness of their programs and partnerships to address those impacts, the political climate for working in advance of pending change, and the degree of citizen engagement in resilience planning and action. The goal is to provide a common tool equivalent to GDP that communities could use to see their strengths and leverage points, and where they have the local resources to build solutions or co-develop solutions with others. Though this new tool, communities may be better able to focus on mitigation, adaptation, and the building of resilience that will put into practice the identified Theory of Change.

Workplace injuries, safety climate and behaviors: application of an artificial neural network.

PubMed

Abubakar, A Mohammed; Karadal, Himmet; Bayighomog, Steven W; Merdan, Ethem

2018-05-09

This article proposes and tests a model for the interaction effect of the organizational safety climate and behaviors on workplace injuries. Using artificial neural network and survey data from 306 metal casting industry employees in central Anatolia, we found that an organizational safety climate mitigates workplace injuries, and safety behaviors enforce the strength of the negative impact of the safety climate on workplace injuries. The results suggest a complex relationship between the organizational safety climate, safety behavior and workplace injuries. Theoretical and practical implications are discussed in light of decreasing workplace injuries in the Anatolian metal casting industry.

An ID Network System to Prepare for Global Environmental/Health Concerns

NASA Astrophysics Data System (ADS)

Asano, Shoichiro; Yoneda, Susumu

Climate change and/or pandemics are global life threatening concerns. For verifying and utilizing monitored data for solving to the Climate Change concerns, a network system based on device ID would be proposed. In this paper, we review the recent standardization initiatives in ITU-T, and propose an ID network that can be used to verify the solutions.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.

Predictability Analysis of PM10 Concentrations in Budapest

NASA Astrophysics Data System (ADS)

Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

Data management and analysis for the Earth System Grid

NASA Astrophysics Data System (ADS)

Williams, D. N.; Ananthakrishnan, R.; Bernholdt, D. E.; Bharathi, S.; Brown, D.; Chen, M.; Chervenak, A. L.; Cinquini, L.; Drach, R.; Foster, I. T.; Fox, P.; Hankin, S.; Henson, V. E.; Jones, P.; Middleton, D. E.; Schwidder, J.; Schweitzer, R.; Schuler, R.; Shoshani, A.; Siebenlist, F.; Sim, A.; Strand, W. G.; Wilhelmi, N.; Su, M.

2008-07-01

The international climate community is expected to generate hundreds of petabytes of simulation data within the next five to seven years. This data must be accessed and analyzed by thousands of analysts worldwide in order to provide accurate and timely estimates of the likely impact of climate change on physical, biological, and human systems. Climate change is thus not only a scientific challenge of the first order but also a major technological challenge. In order to address this technological challenge, the Earth System Grid Center for Enabling Technologies (ESG-CET) has been established within the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC)-2 program, with support from the offices of Advanced Scientific Computing Research and Biological and Environmental Research. ESG-CET's mission is to provide climate researchers worldwide with access to the data, information, models, analysis tools, and computational capabilities required to make sense of enormous climate simulation datasets. Its specific goals are to (1) make data more useful to climate researchers by developing Grid technology that enhances data usability; (2) meet specific distributed database, data access, and data movement needs of national and international climate projects; (3) provide a universal and secure web-based data access portal for broad multi-model data collections; and (4) provide a wide-range of Grid-enabled climate data analysis tools and diagnostic methods to international climate centers and U.S. government agencies. Building on the successes of the previous Earth System Grid (ESG) project, which has enabled thousands of researchers to access tens of terabytes of data from a small number of ESG sites, ESG-CET is working to integrate a far larger number of distributed data providers, high-bandwidth wide-area networks, and remote computers in a highly collaborative problem-solving environment.

Mainstreaming climate adaptation in the Asia-Pacific: Role of networks and universities in promoting climate literacy

NASA Astrophysics Data System (ADS)

Ling, F. H.; Yasuhara, K.; Tamura, M.; Tabayashi, Y.; Mimura, N.

2011-12-01

As the international climate regime continues to evolve, adaptation has emerged as a key component of responding to climate change. Due to limited scientific, financial, and institutional capacities, as well as perceived competition with multiple priorities, strategies for adaptive measures are not being implemented at the pace needed to address current and future climate risks. Adaptation networks, both global and in the Asia-Pacific region, have formed to overcome the lack of sufficient communication and collaboration among different stakeholders and domains of expertise. In this presentation, we discuss various efforts at Ibaraki University in Japan to integrate technical and social aspects of adaptation into a multidisciplinary effort, to foster synergies among various networks, to clarify the roles of developed and developing countries, and to develop a standard for assessing vulnerability and adaptability across various geographical contexts.

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

Analysis of Compound Water Hazard in Coastal Urbanized Areas under the Future Climate

NASA Astrophysics Data System (ADS)

Shibuo, Y.; Taniguchi, K.; Sanuki, H.; Yoshimura, K.; Lee, S.; Tajima, Y.; Koike, T.; Furumai, H.; Sato, S.

2017-12-01

Several studies indicate the increased frequency and magnitude of heavy rainfalls as well as the sea level rise under the future climate, which implies that coastal low-lying urbanized areas may experience increased risk against flooding. In such areas, where river discharge, tidal fluctuation, and city drainage networks altogether influence urban inundation, it is necessary to consider their potential interference to understand the effect of compound water hazard. For instance, pump stations cannot pump out storm water when the river water level is high, and in the meantime the river water level shall increase when it receives pumped water from cities. At the further downstream, as the tidal fluctuation regulates the water levels in the river, it will also affect the functionality of pump stations and possible inundation from rivers. In this study, we estimate compound water hazard in the coastal low-lying urbanized areas of the Tsurumi river basin under the future climate. We developed the seamlessly integrated river, sewerage, and coastal hydraulic model that can simulate river water levels, water flow in sewerage network, and inundation from the rivers and/or the coast to address the potential interference issue. As a forcing, the pseudo global warming method, which applies the changes in GCM anomaly to re-analysis data, is employed to produce ensemble typhoons to drive the seamlessly integrated model. The results show that heavy rainfalls caused by the observed typhoon generally become stronger under the pseudo global climate condition. It also suggests that the coastal low-lying areas become extensively inundated if the onset of river flooding and storm surge coincides.

PHENOALP: a new project on phenology in the Western Alps

NASA Astrophysics Data System (ADS)

Cremonese, E.

2009-04-01

PHENOALP is a new EU co-funded Interreg Project under the operational programme for cross-border cooperation "Italy-France (Alps-ALCOTRA)" 2007 - 2013, aiming to get a better understanding of phenological changes in the Alps. The major goals of the project are: 1- The implementation of an observation network in the involved territories (i.e. the Aosta Valley and the Savoies in the Western Alps); 2- The definition of a common observation strategy and common protocols; 3- The involvement of local community members (e.g. through schools) in the observation activities as a way to increase the awareness on the issue of the effects of climate change. Project leader is the Environmental Protection Agency of Aosta Valley (ARPA Valle d'Aosta - IT) and the partners are the Research Center on High Altitude Ecosystem (CREA - FR), Mont Avic Regional Parc (IT), Bauges Massif Regional Natural Parc (FR) and the Protected Area Service of Aosta Valley (IT). Project activities are: 1. Pheno-plantes: definition of common observation protocols (e.g. field observation and webcams) of different alpine species (trees and herbaceous) and implementation of the observation network; analysis of the relations between climate and phenological events; application and evaluation of phenological models. 2. Pheno-detection: remote sensing of European larch and high elevation pastures with MODIS data; multitemporal analysis (2000-2011) of phenological variations in the Western Alps. 3. Pheno-flux: analysis of the relation between the seasonal and interannual variability of plant phenology and productivity, assessed measuring CO2 fluxes (eddy-covariance technique), radiometric indexes and phenological events at specific (European larch stand and alpine pastures) monitoring site. 4. Pheno-zoo: definition of common observation protocols for the phenology of animal taxa (birds, mammals, amphibians and insects) along altitudinal gradients; implementation of the observation network. 5. Inter-pheno: integrated analysis of the relationships between plants and animals phenology and their relation with climatic and other environmental conditions. 6. Meteo-reseau: implementation of a monitoring network of temperature data in the sites where phenological observations are done. 7. Pheno-form: involvement of community members (e.g. schools, naturalistic guides, ...) in the observations and diffusion of results. During the conference, details on project structures, methodology and expected outcomes will be exposed and discussed.

Dynamical analysis of the Indian Ocean climate network and its correlation with Australian Millennium Drought

NASA Astrophysics Data System (ADS)

Carpi, Laura; Masoller, Cristina; Díaz-Guilera, Albert; Ravetti, Martín G.

2015-04-01

During the period between the mid-1990s and late 2000s Australia had suffered one of the worst droughts on record. Severe rainfall deficits affected great part of southeast Australia, causing widespread drought conditions and catastrophic bushfires. The "Millennium Drought", as it was called, was unusual in terms of its severity, duration and extent, leaving important environmental and financial damages. One of the most important drivers of Australia climate variability is the Indian Ocean dipole (IOD), that is a coupled ocean and atmosphere phenomenon in the equatorial Indian Ocean. The IOD is measured by an index (DMI) that is the difference between sea surface temperature (SST) anomalies in the western and eastern equatorial Indian Ocean. Its positive phase is characterized by lower than normal sea surface temperatures in the tropical eastern coast, and higher than normal in the tropical western Indian Ocean. Extreme positive IOD (pIOD) events are associated to severe droughts in countries located over the eastern Indian Ocean, and to severe floods in the western tropical ones. Recent research works projected that the frequency of extreme pIOD events will increase significantly over the twenty-first century and consequently, the frequency of extreme climate conditions in the zones affected by it. In this work we study the dynamics of the Indian Ocean for the period of 1979-2014, by using climate networks of skin temperature and humidity (reanalysis data). Annual networks are constructed by creating links when the Pearson correlation coefficient between two nodes is greater than a specific value. The distance distribution Pd(k), that indicates the fraction of pairs of nodes at distance k, is computed to characterize the dynamics of the network by using Information Theory quantifiers. We found a clear change in the Indian Ocean dynamics and an increment in the network's similarities quantified by the Jensen-Shannon divergence in the late 1990s. We speculate that these findings are capturing mean state changes within the Indian Ocean that result in the increase of extreme positive IOD frequency, among other unknown consequences. We show that the unusual characteristics of the Australian Millennium Drought is strongly associated with this new Indian Ocean dynamics showing its relevance in the Australia climate variability.

The Power of Large Scale Partnerships to Increase Climate Awareness and Literacy Around the World

NASA Astrophysics Data System (ADS)

Murphy, T.; Andersen, T. J.; Wegner, K.

2016-12-01

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international science and education program that connects a network of communities around the world and gives them the opportunity to participate in data collection and the scientific process, and contribute meaningfully to our understanding of the Earth system and global environment. In the last few years, there has been an infusion of energy in the program as a result of a change to a more community focus. GLOBE was one of the first attempts at a citizen science program at the K-12 level proposed on a global scale. An initial ramp-up of the program was followed by the establishment of a network of partners in countries and within the U.S. One hundred and seventeen countries have participated in the program since its establishment in 1994. These countries are divided into six regions: Africa (23 countries); Asia and Pacific (18); Europe and Eurasia (41); Latin America and Caribbean (20); Near East and North Africa (13); and North America (2). The community within these regions has reached a maturity level that allows it to organize its own science campaigns ranging from aerosols to phenology…all of which increase awareness of climate issues. In addition, some countries within the regions have established science fairs, GLOBE proved to be the impetus for these fairs. The program's partnership network provides students and teachers with a platform for learning about climate issues in their local and global environment, as well as providing scientists with a network to organize data collection and analysis campaigns. Within the U.S., over 130 educational organizations (universities, science museums, nature centers) are members of a partner network divided into six geographical areas: Northwest; Midwest; Northeast and Mid-Atlantic; Southeast; Southwest; and Pacific. For the first time ever, the U.S. held GLOBE science fairs with considerable input and support from the community, the U.S. Partner Forum members, and U.S. Country Coordinator. GLOBE students exhibited their research and learned about climate issues at these fairs. GLOBE has evolved in 20 years and its strength is the community of partners that has helped moved climate literacy forward on a global scale.

Data Requirements for Ceiling and Visibility Products Development

DTIC Science & Technology

1994-04-13

and Water - Cycle Experiment (GEWEX), STORM 1, and the Naval Research Laboratory’s Coastal Me- teorology Accelerated Research Initiative field... Water - Cycle Experiment HPCN High Plains Climate Network lOP Intensive Observation Period ICN Illinois Climate Network ITWS Integrated Terminal Weather

United States Historical Climatology Network (US HCN) monthly temperature and precipitation data

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

Daniels, R.C.; Boden, T.A.; Easterling, D.R.

1996-01-11

This document describes a database containing monthly temperature and precipitation data for 1221 stations in the contiguous United States. This network of stations, known as the United States Historical Climatology Network (US HCN), and the resulting database were compiled by the National Climatic Data Center, Asheville, North Carolina. These data represent the best available data from the United States for analyzing long-term climate trends on a regional scale. The data for most stations extend through December 31, 1994, and a majority of the station records are serially complete for at least 80 years. Unlike many data sets that have beenmore » used in past climate studies, these data have been adjusted to remove biases introduced by station moves, instrument changes, time-of-observation differences, and urbanization effects. These monthly data are available free of charge as a numeric data package (NDP) from the Carbon Dioxide Information Analysis Center. The NDP includes this document and 27 machine-readable data files consisting of supporting data files, a descriptive file, and computer access codes. This document describes how the stations in the US HCN were selected and how the data were processed, defines limitations and restrictions of the data, describes the format and contents of the magnetic media, and provides reprints of literature that discuss the editing and adjustment techniques used in the US HCN.« less

Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?

NASA Astrophysics Data System (ADS)

Vu, Minh Tue; Aribarg, Thannob; Supratid, Siriporn; Raghavan, Srivatsan V.; Liong, Shie-Yui

2016-11-01

Artificial neural network (ANN) is an established technique with a flexible mathematical structure that is capable of identifying complex nonlinear relationships between input and output data. The present study utilizes ANN as a method of statistically downscaling global climate models (GCMs) during the rainy season at meteorological site locations in Bangkok, Thailand. The study illustrates the applications of the feed forward back propagation using large-scale predictor variables derived from both the ERA-Interim reanalyses data and present day/future GCM data. The predictors are first selected over different grid boxes surrounding Bangkok region and then screened by using principal component analysis (PCA) to filter the best correlated predictors for ANN training. The reanalyses downscaled results of the present day climate show good agreement against station precipitation with a correlation coefficient of 0.8 and a Nash-Sutcliffe efficiency of 0.65. The final downscaled results for four GCMs show an increasing trend of precipitation for rainy season over Bangkok by the end of the twenty-first century. The extreme values of precipitation determined using statistical indices show strong increases of wetness. These findings will be useful for policy makers in pondering adaptation measures due to flooding such as whether the current drainage network system is sufficient to meet the changing climate and to plan for a range of related adaptation/mitigation measures.

ONU Power Saving Scheme for EPON System

NASA Astrophysics Data System (ADS)

Mukai, Hiroaki; Tano, Fumihiko; Tanaka, Masaki; Kozaki, Seiji; Yamanaka, Hideaki

PON (Passive Optical Network) achieves FTTH (Fiber To The Home) economically, by sharing an optical fiber among plural subscribers. Recently, global climate change has been recognized as a serious near term problem. Power saving techniques for electronic devices are important. In PON system, the ONU (Optical Network Unit) power saving scheme has been studied and defined in XG-PON. In this paper, we propose an ONU power saving scheme for EPON. Then, we present an analysis of the power reduction effect and the data transmission delay caused by the ONU power saving scheme. According to the analysis, we propose an efficient provisioning method for the ONU power saving scheme which is applicable to both of XG-PON and EPON.

Why do the biotechnology and the climate change debates hardly mix? Evidence from a global stakeholder survey.

PubMed

Aerni, Philipp

2013-05-25

Despite its potential to address climate change problems, the role of biotechnology is hardly ever touched upon in the global sustainability debate. We wanted to know why. For that purpose, we conducted a global online stakeholder survey on biotechnology and climate change. The relevant stakeholders and their representatives were selected by means of key informants that were familiar with either of the two debates. A self-assessment showed that a majority of respondents felt more familiar with the climate change than the biotechnology debate. Even though the survey results reveal that most respondents consider the potential of modern biotechnology to address climate change to be substantial, the policy network analysis revealed that one stakeholder who is not just considered to be relevant in both debates but also crucial in the formation of global public opinion, strongly rejects the view that biotechnology is a climate-friendly and therefore clean technology. This influential opposition seems to ensure that the biotechnology and the climate change debates do not mix. Copyright © 2012 Elsevier B.V. All rights reserved.

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change.

PubMed

Albert, Cécile H; Rayfield, Bronwyn; Dumitru, Maria; Gonzalez, Andrew

2017-12-01

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. © 2017 Society for Conservation Biology.

Impacts of land cover changes on climate trends in Jiangxi province China.

PubMed

Wang, Qi; Riemann, Dirk; Vogt, Steffen; Glaser, Rüdiger

2014-07-01

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951-1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1% of the surface warming over vegetation index areas (0-0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.

The challenge of monitoring the cryosphere in alpine environments: Prepare the present for the future

NASA Astrophysics Data System (ADS)

Fischer, Andrea; Helfricht, Kay; Seiser, Bernd; Stocker-Waldhuber, Martin; Hartl, Lea; Wiesenegger, Hans

2017-04-01

Understanding the interaction of mountain glaciers and permafrost with weather and climate is essential for the interpretation of past states of the cryosphere in terms of climate change. Most of the glaciers and rock glaciers in Eastern Alpine terrain are subject to strong gradients in climatic forcing, and the persistence of these gradients under past climatic conditions is, more or less, unknown. Thus a key challenge of monitoring the cryosphere is to define the demands on a monitoring strategy for capturing essential processes and their potential changes. For example, the effects of orographic precipitation and local shading vary with general circulation patterns and the amount of solar radiation during the melt(ing) season. Recent investigations based on the Austrian glacier inventories have shown that glacier distribution is closely linked to topography and climatic situation, and that these two parameters imply also different sensitivities of the specific glaciers to progressing climate change. This leads to the need to develop a monitoring system capturing past, but also fairly unknown future ensembles of climatic state and sensitivities. As a first step, the Austrian glacier monitoring network has been analyzed from the beginning of the records onwards. Today's monitoring network bears the imprints of past research interests, but also past funding policies and personal/institutional engagements. As a limitation for long term monitoring in general, today's monitoring strategies have to cope with being restricted to these historical commitments to preserve the length of the time series, but at the same time expanding the measurements to fulfil present and future scientific and societal demands. The decision on cryospheric benchmark sites has an additional uncertainty: the ongoing disintegration of glaciers, their increasing debris cover as well as the potential low ice content and relatively unknown reaction of rock glaciers in the course of climate change, limits the number of potential candidates for future monitoring drastically. In the light of these developments, sample sizes are a critical question for reliable monitoring, together with strategies for coping with changing monitoring sites and composition of time series. As a first step, the Austrian monitoring network has been analyzed from 1891 onwards. Past changes evident from the glacier inventories capturing all glaciers have been compared to the subsamples of glaciers monitored for length change, mass balance and ice flow velocities. The results show that for capturing the full bandwidth of regional changes, glacier inventories are necessary. Without the analysis of larger scale changes, the interpretation of records with very low sample sizes, such as mass balance or length change, has a high uncertainty level. For specific research or monitoring purposes, for example, the development of runoff master sites with all types of monitoring techniques improve the certainty of the spatial extrapolations of local records or the interpretation of volume changes. The challenge of preparing the present network for the future requires a thorough analysis of potential future developments to be able to switch sites with a common observation period necessary to investigate the different sensitivities.

Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions.

PubMed

Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli

2017-10-01

Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1  yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.

Sensitivity of New England Stream Temperatures to Air Temperature and Precipitation Under Projected Climate

NASA Astrophysics Data System (ADS)

Huang, T.; Samal, N. R.; Wollheim, W. M.; Stewart, R. J.; Zuidema, S.; Prousevitch, A.; Glidden, S.

2015-12-01

The thermal response of streams and rivers to changing climate will influence aquatic habitat. This study examines the impact that changing climate has on stream temperatures in the Merrimack River, NH/MA USA using the Framework for Aquatic Modeling in the Earth System (FrAMES), a spatially distributed river network model driven by air temperature, air humidity, wind speed, precipitation, and solar radiation. Streamflow and water temperatures are simulated at a 45-second (latitude x longitude) river grid resolution for 135 years under historical and projected climate variability. Contemporary streamflow (Nash-Sutcliffe Coefficient = 0.77) and river temperatures (Nash-Sutcliffe Coefficient = 0.89) matched at downstream USGS gauge data well. A suite of model runs were made in combination with uniformly increased daily summer air temperatures by 2oC, 4 oC and 6 oC as well as adjusted precipitation by -40%, -30%, -20%, -10% and +10% as a sensitivity analysis to explore a broad range of potential future climates. We analyzed the summer stream temperatures and the percent of river length unsuitable for cold to warm water fish habitats. Impacts are greatest in large rivers due to the accumulation of river temperature warming throughout the entire river network. Cold water fish (i.e. brook trout) are most strongly affected while, warm water fish (i.e. largemouth bass) aren't expected to be impacted. The changes in stream temperatures under various potential climate scenarios will provide a better understanding of the specific impact that air temperature and precipitation have on aquatic thermal regimes and habitat.

Potential future exposure of European land transport infrastructure to rainfall-induced landslides throughout the 21st century

NASA Astrophysics Data System (ADS)

Schlögl, Matthias; Matulla, Christoph

2018-04-01

In the face of climate change, the assessment of land transport infrastructure exposure towards adverse climate events is of major importance for Europe's economic prosperity and social wellbeing. In this study, a climate index estimating rainfall patterns which trigger landslides in central Europe is analysed until the end of this century and compared to present-day conditions. The analysis of the potential future development of landslide risk is based on an ensemble of dynamically downscaled climate projections which are driven by the SRES A1B socio-economic scenario. Resulting regional-scale climate change projections across central Europe are concatenated with Europe's road and railway network. Results indicate overall increases of landslide occurrence. While flat terrain at low altitudes exhibits an increase of about 1 more potentially landslide-inducing rainfall period per year until the end of this century, higher elevated regions are more affected and show increases of up to 14 additional periods. This general spatial distribution emerges in the near future (2021-2050) but becomes more pronounced in the remote future (2071-2100). Since largest increases are to be found in Alsace, potential impacts of an increasing amount of landslides are discussed using the example of a case study covering the Black Forest mountain range in Baden-Württemberg by further enriching the climate information with additional geodata. The findings derived are suitable to support political decision makers and European authorities in transport, freight and logistics by offering detailed information on which parts of Europe's ground transport network are at particularly high risk concerning landslide activity.

Temporal network analysis identifies early physiological and transcriptomic indicators of mild drought in Brassica rapa

PubMed Central

Gehan, Malia A; Mockler, Todd C; Weinig, Cynthia; Ewers, Brent E

2017-01-01

The dynamics of local climates make development of agricultural strategies challenging. Yield improvement has progressed slowly, especially in drought-prone regions where annual crop production suffers from episodic aridity. Underlying drought responses are circadian and diel control of gene expression that regulate daily variations in metabolic and physiological pathways. To identify transcriptomic changes that occur in the crop Brassica rapa during initial perception of drought, we applied a co-expression network approach to associate rhythmic gene expression changes with physiological responses. Coupled analysis of transcriptome and physiological parameters over a two-day time course in control and drought-stressed plants provided temporal resolution necessary for correlation of network modules with dynamic changes in stomatal conductance, photosynthetic rate, and photosystem II efficiency. This approach enabled the identification of drought-responsive genes based on their differential rhythmic expression profiles in well-watered versus droughted networks and provided new insights into the dynamic physiological changes that occur during drought. PMID:28826479

Web processing service for climate impact and extreme weather event analyses. Flyingpigeon (Version 1.0)

NASA Astrophysics Data System (ADS)

Hempelmann, Nils; Ehbrecht, Carsten; Alvarez-Castro, Carmen; Brockmann, Patrick; Falk, Wolfgang; Hoffmann, Jörg; Kindermann, Stephan; Koziol, Ben; Nangini, Cathy; Radanovics, Sabine; Vautard, Robert; Yiou, Pascal

2018-01-01

Analyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the providers and processing the data files ;at home; with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives. We developed a WPS named 'flyingpigeon' that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC), to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely. Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues, illustrating the flexibility of WPS in designing custom outputs. Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets.

The GCOS Reference Upper-Air Network (GRUAN)

NASA Astrophysics Data System (ADS)

Vömel, H.; Berger, F. H.; Immler, F. J.; Seidel, D.; Thorne, P.

2009-04-01

While the global upper-air observing network has provided useful observations for operational weather forecasting for decades, its measurements lack the accuracy and long-term continuity needed for understanding climate change. Consequently, the scientific community faces uncertainty on such key issues as the trends of temperature in the upper troposphere and stratosphere or the variability and trends of stratospheric water vapour. To address these shortcomings, and to ensure that future climate records will be more useful than the records to date, the Global Climate Observing System (GCOS) program initiated the GCOS Reference Upper Air Network (GRUAN). GRUAN will be a network of about 30-40 observatories with a representative sampling of geographic regions and surface types. These stations will provide upper-air reference observations of the essential climate variables, i.e. temperature, geopotential, humidity, wind, radiation and cloud properties using specialized radiosondes and complementary remote sensing profiling instrumentation. Long-term stability, quality assurance / quality control, and a detailed assessment of measurement uncertainties will be the key aspects of GRUAN observations. The network will not be globally complete but will serve to constrain and adjust data from more spatially comprehensive global observing systems including satellites and the current radiosonde networks. This paper outlines the scientific rationale for GRUAN, its role in the Global Earth Observation System of Systems, network requirements and likely instrumentation, management structure, current status and future plans.

Past climate change on Sky Islands drives novelty in a core developmental gene network and its phenotype.

PubMed

Favé, Marie-Julie; Johnson, Robert A; Cover, Stefan; Handschuh, Stephan; Metscher, Brian D; Müller, Gerd B; Gopalan, Shyamalika; Abouheif, Ehab

2015-09-04

A fundamental and enduring problem in evolutionary biology is to understand how populations differentiate in the wild, yet little is known about what role organismal development plays in this process. Organismal development integrates environmental inputs with the action of gene regulatory networks to generate the phenotype. Core developmental gene networks have been highly conserved for millions of years across all animals, and therefore, organismal development may bias variation available for selection to work on. Biased variation may facilitate repeatable phenotypic responses when exposed to similar environmental inputs and ecological changes. To gain a more complete understanding of population differentiation in the wild, we integrated evolutionary developmental biology with population genetics, morphology, paleoecology and ecology. This integration was made possible by studying how populations of the ant species Monomorium emersoni respond to climatic and ecological changes across five 'Sky Islands' in Arizona, which are mountain ranges separated by vast 'seas' of desert. Sky Islands represent a replicated natural experiment allowing us to determine how repeatable is the response of M. emersoni populations to climate and ecological changes at the phenotypic, developmental, and gene network levels. We show that a core developmental gene network and its phenotype has kept pace with ecological and climate change on each Sky Island over the last ~90,000 years before present (BP). This response has produced two types of evolutionary change within an ant species: one type is unpredictable and contingent on the pattern of isolation of Sky lsland populations by climate warming, resulting in slight changes in gene expression, organ growth, and morphology. The other type is predictable and deterministic, resulting in the repeated evolution of a novel wingless queen phenotype and its underlying gene network in response to habitat changes induced by climate warming. Our findings reveal dynamics of developmental gene network evolution in wild populations. This holds important implications: (1) for understanding how phenotypic novelty is generated in the wild; (2) for providing a possible bridge between micro- and macroevolution; and (3) for understanding how development mediates the response of organisms to past, and potentially, future climate change.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Projected range contractions of European protected oceanic montane plant communities: focus on climate change impacts is essential for their future conservation.

PubMed

Hodd, Rory L; Bourke, David; Skeffington, Micheline Sheehy

2014-01-01

Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the north-west hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1) oceanic montane bryophytes and vascular plants; 2) species belonging to different montane plant communities; 3) species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need significantly greater focus on potential climate change impacts, including models with higher-resolution species distribution and environmental data, to aid these communities' long-term survival.

Projected Range Contractions of European Protected Oceanic Montane Plant Communities: Focus on Climate Change Impacts Is Essential for Their Future Conservation

PubMed Central

Skeffington, Micheline Sheehy

2014-01-01

Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the north-west hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1) oceanic montane bryophytes and vascular plants; 2) species belonging to different montane plant communities; 3) species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need significantly greater focus on potential climate change impacts, including models with higher-resolution species distribution and environmental data, to aid these communities' long-term survival. PMID:24752011

Determinants of bird species richness, endemism, and island network roles in Wallacea and the West Indies: is geography sufficient or does current and historical climate matter?

PubMed Central

Dalsgaard, Bo; Carstensen, Daniel W; Fjeldså, Jon; Maruyama, Pietro K; Rahbek, Carsten; Sandel, Brody; Sonne, Jesper; Svenning, Jens-Christian; Wang, Zhiheng; Sutherland, William J

2014-01-01

Island biogeography has greatly contributed to our understanding of the processes determining species' distributions. Previous research has focused on the effects of island geography (i.e., island area, elevation, and isolation) and current climate as drivers of island species richness and endemism. Here, we evaluate the potential additional effects of historical climate on breeding land bird richness and endemism in Wallacea and the West Indies. Furthermore, on the basis of species distributions, we identify island biogeographical network roles and examine their association with geography, current and historical climate, and bird richness/endemism. We found that island geography, especially island area but also isolation and elevation, largely explained the variation in island species richness and endemism. Current and historical climate only added marginally to our understanding of the distribution of species on islands, and this was idiosyncratic to each archipelago. In the West Indies, endemic richness was slightly reduced on islands with historically unstable climates; weak support for the opposite was found in Wallacea. In both archipelagos, large islands with many endemics and situated far from other large islands had high importance for the linkage within modules, indicating that these islands potentially act as speciation pumps and source islands for surrounding smaller islands within the module and, thus, define the biogeographical modules. Large islands situated far from the mainland and/or with a high number of nonendemics acted as links between modules. Additionally, in Wallacea, but not in the West Indies, climatically unstable islands tended to interlink biogeographical modules. The weak and idiosyncratic effect of historical climate on island richness, endemism, and network roles indicates that historical climate had little effects on extinction-immigration dynamics. This is in contrast to the strong effect of historical climate observed on the mainland, possibly because surrounding oceans buffer against strong climate oscillations and because geography is a strong determinant of island richness, endemism and network roles. PMID:25505528

Impact of four-dimensional data assimilation (FDDA) on urban climate analysis

NASA Astrophysics Data System (ADS)

Pan, Linlin; Liu, Yubao; Liu, Yuewei; Li, Lei; Jiang, Yin; Cheng, Will; Roux, Gregory

2015-12-01

This study investigates the impact of four-dimensional data assimilation (FDDA) on urban climate analysis, which employs the NCAR (National Center for Atmospheric Research) WRF (the weather research and forecasting model) based on climate FDDA (CFDDA) technology to develop an urban-scale microclimatology database for the Shenzhen area, a rapidly developing metropolitan located along the southern coast of China, where uniquely high-density observations, including ultrahigh-resolution surface AWS (automatic weather station) network, radio sounding, wind profilers, radiometers, and other weather observation platforms, have been installed. CFDDA is an innovative dynamical downscaling regional climate analysis system that assimilates diverse regional observations; and has been employed to produce a 5 year multiscale high-resolution microclimate analysis by assimilating high-density observations at Shenzhen area. The CFDDA system was configured with four nested-grid domains at grid sizes of 27, 9, 3, and 1 km, respectively. This research evaluates the impact of assimilating high-resolution observation data on reproducing the refining features of urban-scale circulations. Two experiments were conducted with a 5 year run using CFSR (climate forecast system reanalysis) as boundary and initial conditions: one with CFDDA and the other without. The comparisons of these two experiments with observations indicate that CFDDA greatly reduces the model analysis error and is able to realistically analyze the microscale features such as urban-rural-coastal circulation, land/sea breezes, and local-hilly terrain thermal circulations. It is demonstrated that the urbanization can produce 2.5 k differences in 2 m temperatures, delays/speeds up the land/sea breeze development, and interacts with local mountain-valley circulations.

Reconstitution de données climatiques pour l’Algérie du Nord : application des réseaux neuronaux

NASA Astrophysics Data System (ADS)

Bouaoune, Djahida; Dahmani-Megrerouche, Malika

2010-11-01

In the present context of climate change and preservation of biodiversity, the appreciation of the vulnerability of the natural ecosystems and their capacity of adaptation appears among the main preoccupations to the world level (GIEC, 2007). This assessment of the ecosystems requires the availability of climatic data, what is often made difficult by the weak density or even the absence of meteorological stations notably, to the level of the mountains zones. In order to study the climate-vegetation relationship in North Algeria, we use an automatic interpolation method, the neural network method, for the reconstitution of climatic data of the sampled sites, (1035 phytoecological samples), from the existing meteorological network (269 stations). This method is characterized by a great suppleness of non-linearity and by its capacity for reconstituting information from partial and not well-defined indications such as the case of data provided from meteorological networks. In order to reconstitution of climatic data, we use the explicate variables, longitude, latitude and altitude, the variables to explain being the rainfall and temperatures. To define the best approach, the network calibration has been activated on climatic parameters taken globally or solely, for the whole of study zone, and by geographical sector. The results of the interpolation are expressed through a climatic parameter cartography, released automatically by the MapInfo software. The reliability results obtained by this method can be appreciated by elaboration of errors maps comparing to reference data.

Climate change threatens European conservation areas

PubMed Central

Araújo, Miguel B; Alagador, Diogo; Cabeza, Mar; Nogués-Bravo, David; Thuiller, Wilfried

2011-01-01

Europe has the world's most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58 ± 2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63 ± 2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P<0.001), but Natura 2000 areas retain climate suitability for species no better and sometimes less effectively than unprotected areas. The risk is high that ongoing efforts to conserve Europe's biodiversity are jeopardized by climate change. New policies are required to avert this risk. PMID:21447141

WEPP FuME Analysis for a North Idaho Site

Treesearch

William Elliot; Ina Sue Miller; David Hall

2007-01-01

A computer interface has been developed to assist with analyzing soil erosion rates associated with fuel management activities. This interface uses the Water Erosion Prediction Project (WEPP) model to predict sediment yields from hillslopes and road segments to the stream network. The simple interface has a large database of climates, vegetation files and forest soil...

Citizen Science: linking the recent rapid advances of plant flowering in Canada with climate variability.

PubMed

Gonsamo, Alemu; Chen, Jing M; Wu, Chaoyang

2013-01-01

The timing of crucial events in plant life cycles is shifting in response to climate change. We use phenology records from PlantWatch Canada 'Citizen Science' networks to study recent rapid shifts of flowering phenology and its relationship with climate. The average first flower bloom day of 19 Canadian plant species has advanced by about 9 days during 2001-2012. 73% of the rapid and unprecedented first bloom day advances are explained by changes in mean annual national temperature, allowing the reconstruction of historic flower phenology records starting from 1948. The overall trends show that plant flowering in Canada is advancing by about 9 days per °C. This analysis reveals the strongest biological signal yet of climate warming in Canada. This finding has broad implications for niche differentiation among coexisting species, competitive interactions between species, and the asynchrony between plants and the organisms they interact with.

Stratosphere-Troposphere Coupling in the Northern Hemisphere analyzed with climate network measures

NASA Astrophysics Data System (ADS)

Kirsch, C.; Donner, R. V.

2017-12-01

The Stratosphere-Troposphere Coupling (STC) is a climate phenomenon providing additional predictive skills for extended-range weather forecasting. The variability of the winter stratospheric polar vortex can particularly influence the tropospheric circulation and, hence, mid-to-high latitude weather for a few weeks or months by strong or weak vortex signals propagating downward with time. This study investigates the STC with climate networks. For this purpose, we use the geopotential height field between 20°N and 90°N at 37 vertical levels from the ERA-Interim reanalysis data from 1979 until 2016. There are two main research questions: (i) Is it possible to define a new, more robust index of the variability of the polar vortex than the currently used NAM index by exploiting climate network properties? (ii) What additional information on STC is provided by climate networks? By calculating the transitivity of evolving climate networks at 10 hPa height, we obtain a new characteristic measure for tracing evolving patterns in stratospheric variability. A higher value than the baseline transitivity indicates an anomalous (strong or weak) polar vortex. Displayed for all vertical levels, the transitivity also exhibits the downward propagation of pressure anomalies into the troposphere. Beyond these findings, we observe additional peaks in the transitivity that does not coincide with weak and strong vortex events. These peaks could be used for identifying the change between winter and summer circulation, also called final warming. We will discuss how these results could potentially affect the predictability of tropospheric weather during boreal spring.

Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

PubMed

Howe, P D; Bryant, S R; Shreeve, T G

2007-10-01

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

Deciphering the expression of climate change within the Lower Colorado River basin by stochastic simulation of convective rainfall

NASA Astrophysics Data System (ADS)

Bliss Singer, Michael; Michaelides, Katerina

2017-10-01

In drylands, convective rainstorms typically control runoff, streamflow, water supply and flood risk to human populations, and ecological water availability at multiple spatial scales. Since drainage basin water balance is sensitive to climate, it is important to improve characterization of convective rainstorms in a manner that enables statistical assessment of rainfall at high spatial and temporal resolution, and the prediction of plausible manifestations of climate change. Here we present a simple rainstorm generator, STORM, for convective storm simulation. It was created using data from a rain gauge network in one dryland drainage basin, but is applicable anywhere. We employ STORM to assess watershed rainfall under climate change simulations that reflect differences in wetness/storminess, and thus provide insight into observed or projected regional hydrologic trends. Our analysis documents historical, regional climate change manifesting as a multidecadal decline in rainfall intensity, which we suggest has negatively impacted ephemeral runoff in the Lower Colorado River basin, but has not contributed substantially to regional negative streamflow trends.

Is U.S. climatic diversity well represented within the existing federal protection network?

Treesearch

Enric Batllori; Carol Miller; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz

2014-01-01

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans....

PRISM Climate Group, Oregon State U

Science.gov Websites

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

The Influence of Drivers and Barriers on Urban Adaptation and Mitigation Plans—An Empirical Analysis of European Cities

PubMed Central

Reckien, Diana; Flacke, Johannes

2015-01-01

Cities are recognised as key players in global adaptation and mitigation efforts because the majority of people live in cities. However, in Europe, which is highly urbanized and one of the most advanced regions in terms of environmental policies, there is considerable diversity in the regional distribution, ambition and scope of climate change responses. This paper explores potential factors contributing to such diversity in 200 large and medium-sized cities across 11 European countries. We statistically investigate institutional, socio-economic, environmental and vulnerability characteristics of cities as potential drivers of or barriers to the development of urban climate change plans. Our results show that factors such as membership of climate networks, population size, GDP per capita and adaptive capacity act as drivers of mitigation and adaptation plans. By contrast, factors such as the unemployment rate, warmer summers, proximity to the coast and projected exposure to future climate impacts act as barriers. We see that, overall, it is predominantly large and prosperous cities that engage in climate planning, while vulnerable cities and those at risk of severe climate impacts in the future are less active. Our analysis suggests that climate change planning in European cities is not proactive, i.e. not significantly influenced by anticipated future impacts. Instead, we found that the current adaptive capacity of a city significantly relates to climate planning. Along with the need to further explore these relations, we see a need for more economic and institutional support for smaller and less resourceful cities and those at high risk from climate change impacts in the future. PMID:26317420

The Influence of Drivers and Barriers on Urban Adaptation and Mitigation Plans-An Empirical Analysis of European Cities.

PubMed

Reckien, Diana; Flacke, Johannes; Olazabal, Marta; Heidrich, Oliver

2015-01-01

Cities are recognised as key players in global adaptation and mitigation efforts because the majority of people live in cities. However, in Europe, which is highly urbanized and one of the most advanced regions in terms of environmental policies, there is considerable diversity in the regional distribution, ambition and scope of climate change responses. This paper explores potential factors contributing to such diversity in 200 large and medium-sized cities across 11 European countries. We statistically investigate institutional, socio-economic, environmental and vulnerability characteristics of cities as potential drivers of or barriers to the development of urban climate change plans. Our results show that factors such as membership of climate networks, population size, GDP per capita and adaptive capacity act as drivers of mitigation and adaptation plans. By contrast, factors such as the unemployment rate, warmer summers, proximity to the coast and projected exposure to future climate impacts act as barriers. We see that, overall, it is predominantly large and prosperous cities that engage in climate planning, while vulnerable cities and those at risk of severe climate impacts in the future are less active. Our analysis suggests that climate change planning in European cities is not proactive, i.e. not significantly influenced by anticipated future impacts. Instead, we found that the current adaptive capacity of a city significantly relates to climate planning. Along with the need to further explore these relations, we see a need for more economic and institutional support for smaller and less resourceful cities and those at high risk from climate change impacts in the future.

Framework for a U.S. Geological Survey Hydrologic Climate-Response Program in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Lent, Robert M.; Dudley, Robert W.; Schalk, Charles W.

2009-01-01

This report presents a framework for a U.S. Geological Survey (USGS) hydrologic climate-response program designed to provide early warning of changes in the seasonal water cycle of Maine. Climate-related hydrologic changes on Maine's rivers and lakes in the winter and spring during the last century are well documented, and several river and lake variables have been shown to be sensitive to air-temperature changes. Monitoring of relevant hydrologic data would provide important baseline information against which future climate change can be measured. The framework of the hydrologic climate-response program presented here consists of four major parts: (1) identifying homogeneous climate-response regions; (2) identifying hydrologic components and key variables of those components that would be included in a hydrologic climate-response data network - as an example, streamflow has been identified as a primary component, with a key variable of streamflow being winter-spring streamflow timing; the data network would be created by maintaining existing USGS data-collection stations and establishing new ones to fill data gaps; (3) regularly updating historical trends of hydrologic data network variables; and (4) establishing basins for process-based studies. Components proposed for inclusion in the hydrologic climate-response data network have at least one key variable for which substantial historical data are available. The proposed components are streamflow, lake ice, river ice, snowpack, and groundwater. The proposed key variables of each component have extensive historical data at multiple sites and are expected to be responsive to climate change in the next few decades. These variables are also important for human water use and (or) ecosystem function. Maine would be divided into seven climate-response regions that follow major river-basin boundaries (basins subdivided to hydrologic units with 8-digit codes or larger) and have relatively homogeneous climates. Key hydrologic variables within each climate-response region would be analyzed regularly to maintain up-to-date analyses of year-to-year variability, decadal variability, and longer term trends. Finally, one basin in each climate-response region would be identified for process-based hydrologic and ecological studies.

Measuring the Dynamics of Climate Change Communication in Mass Media and Social Networks with Computer-Assisted Content Analysis

NASA Astrophysics Data System (ADS)

Kirilenko, A.; Stepchenkova, S.

2012-12-01

To date, multiple authors have examined media representations of and public attitudes towards climate change, as well as how these representations and attitudes differ from scientific knowledge on the issue of climate change. Content analysis of newspaper publications, TV news, and, recently, Internet blogs has allowed for identification of major discussion themes within the climate change domain (e.g., newspaper trends, comparison of climate change discourse in different countries, contrasting liberal vs. conservative press). The majority of these studies, however, have processed texts manually, limiting textual population size, restricting the analysis to a relatively small number of themes, and using time-expensive coding procedures. The use of computer-assisted text analysis (CATA) software is important because the difficulties with manual processing become more severe with an increased volume of data. We developed a CATA approach that allows a large body of text materials to be surveyed in a quantifiable, objective, transparent, and time-efficient manner. While staying within the quantitative tradition of content analysis, the approach allows for an interpretation of the public discourse closer to one of more qualitatively oriented methods. The methodology used in this study contains several steps: (1) sample selection; (2) data preparation for computer processing and obtaining a matrix of keyword frequencies; (3) identification of themes in the texts using Exploratory Factor Analysis (EFA); (4) combining identified themes into higher order themes using Confirmatory Factor Analysis (CFA); (5) interpretation of obtained public discourse themes using factor scores; and (6) tracking the development of the main themes of the climate change discourse through time. In the report, we concentrate on two examples of CATA applied to study public perception of climate change. First example is an analysis of temporal change in public discourse on climate change. Applying CATA to a conservatively selected sample of 4043 articles published on climate change in The New York Times from 1995, we found a considerable change in major topics of discussion. One of the most significant tendencies is a gradual decline in the volume of material within the "Science" topic and an expansion of themes classified under the "Politics" topic. The second example is the analysis of public ability to detect climate change, in which we used a database of over 1 million Twitter messages on climate change that we have collected. We compared the intensity of tweeting on climate change with the "common-sense climate index" by Hansen et al (1999) and found that the weather extremes experienced at a certain location is immediately reflected in the number of tweets discussing climate change originating from that location. Although the CATA approach certainly has its limitations, we are convinced that it has a number of advantages over manual processing: it is able to analyze large textual bodies, is more time efficient, has a higher level of detail, enhances the richness of interpretation, and is able to reliably track discourse development through time.

Estimating extreme river discharges in Europe through a Bayesian network

NASA Astrophysics Data System (ADS)

Paprotny, Dominik; Morales-Nápoles, Oswaldo

2017-06-01

Large-scale hydrological modelling of flood hazards requires adequate extreme discharge data. In practise, models based on physics are applied alongside those utilizing only statistical analysis. The former require enormous computational power, while the latter are mostly limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian networks (BNs), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables representing the geographical characteristics of their catchments. Annual maxima of daily discharges from more than 1800 river gauges (stations with catchment areas ranging from 1.4 to 807 000 km2) were collected, together with information on terrain, land use and local climate. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe and better than a comparable global statistical model. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and remains the same in a split-sample validation. Though discharge prediction under climate change is not the main scope of this paper, the BN was applied to a large domain covering all sizes of rivers in the continent both for present and future climate, as an example. Results show substantial variation in the influence of climate change on river discharges. The model can be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

Twitter Analytics: Are the U.S. Coastal Regions Prepared for Climate Change in 2017?

NASA Astrophysics Data System (ADS)

Singleton, S. L.; Kumar, S.

2017-12-01

According to the U.S. National Climate Assessment, the Southeast Coast and Gulf Coast of the United States are particularly susceptible to sea level rise, heat waves, hurricanes and less accessibility to clean water due to climate change. This is because of the extreme variation of topography in these two regions. Preparation for climate change consequences can only occur with conversation, which is a method of bringing awareness to the issue. Over the past decade, social media has taken over the spectrum of information exchange in the United States. Social Network Analysis (SNA) is a field that is emerging with the growth in popularity of social media. SNA is the practice of analyzing trends in volume and opinion of a population of social media users. Twitter, one popular social media platform, is one of the largest microblogging sites in the world, and it provides an abundance of data related to the trending topics such as climate change. Twitter analytics is a type of SNA performed on data from the tweets of Twitter users. In this work, Twitter analytics is performed on the data generated from the Twitter users in the United States, who were talking about climate change, global warming and/or CO2, over the course of one year (July 2016 - June 2017). Specifically, a regional comparative analysis on the coastal U.S. regions was conducted to recognize which region(s) is/are falling behind on the conversation about climate change. Sentiment analysis was also performed to understand the trends in opinion about climate change that vary over time. Experimental results determined that the southeast coast of the United States is deficient in their discussion about climate change compared to the other coastal regions. Igniting the conversation about this issue in these regions will mitigate the disasters due to climate change by increasing awareness in the people of these regions so they can properly prepare.

Climate Voices: Bridging Scientist Citizens and Local Communities across the United States

NASA Astrophysics Data System (ADS)

Wegner, K.; Ristvey, J. D., Jr.

2016-12-01

Based out of the University Corporation for Atmospheric Research (UCAR), the Climate Voices Science Speakers Network (climatevoices.org) has more than 400 participants across the United States that volunteer their time as scientist citizens in their local communities. Climate Voices experts engage in nonpartisan conversations about the local impacts of climate change with groups such as Rotary clubs, collaborate with faith-based groups on climate action initiatives, and disseminate their research findings to K-12 teachers and classrooms through webinars. To support their participants, Climate Voices develops partnerships with networks of community groups, provides trainings on how to engage these communities, and actively seeks community feedback. In this presentation, we will share case studies of science-community collaborations, including meta-analyses of collaborations and lessons learned.

Climatic Changes and Evaluation of Their Effects on Agriculture in Asian Monsoon Region- A project of GRENE-ei programs in Japan

NASA Astrophysics Data System (ADS)

Mizoguchi, M.; Matsumoto, J.; Takahashi, H. G.; Tanaka, K.; Kuwagata, T.

2015-12-01

It is important to predict climate change correctly in regional scale and to build adaptation measures and mitigation measures in the Asian monsoon region where more than 60 % of the world's population are living. The reliability of climate change prediction model is evaluated by the reproducibility of past climate in general. However, because there are many developing countries in the Asian monsoon region, adequate documentations of past climate which are needed to evaluate the climate reproducibility have not been prepared. In addition, at present it is difficult to get information on wide-area agricultural meteorological data which affect the growth of agricultural crops when considering the impact on agriculture of climate. Therefore, we have started a research project entitled "Climatic changes and evaluation of their effects on agriculture in Asian monsoon region (CAAM)" under the research framework of the Green Network of Excellence (GRENE) for the Japanese fiscal years from 2011 to 2015 supported by the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT). This project aims to improve the reliability of future climate prediction and to develop the information platform which will be useful to design adaptation and mitigation strategies in agriculture against the predicted climatic changes in Asian monsoon regions. What is GRENE?Based on the new growth strategy which was approved by the Cabinet of Japan in June 2010, Green Network of Excellence program (GRENE) has started under MEXT from FY 2011. The objectives of this program are that the domestic leading universities work together strategically and promote a comprehensive human resource development and research of the highest level in the world while sharing research resources and research goals. In the field of environmental information, it is required that universities and research institutions, which are working on issues such as adaptation to climate change, cooperate to promote the utilization of environmental information and to develop human resources while using DIAS (Data Integration and Analysis System) which has been built by MEXT.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

78 FR 18323 - Notice of Availability of a Draft Programmatic Environmental Assessment of the Proposed United...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

... Proposed United States Regional Climate Reference Network (USRCRN) AGENCY: National Weather Service (NWS..., is proposing to implement, operate, and manage a USRCRN. With other climate monitoring efforts..., high-quality climate data for use in climate-monitoring activities and for placing current climate...

The predictive state: Science, territory and the future of the Indian climate.

PubMed

Mahony, Martin

2014-02-01

Acts of scientific calculation have long been considered central to the formation of the modern nation state, yet the transnational spaces of knowledge generation and political action associated with climate change seem to challenge territorial modes of political order. This article explores the changing geographies of climate prediction through a study of the ways in which climate change is rendered knowable at the national scale in India. The recent controversy surrounding an erroneous prediction of melting Himalayan glaciers by the Intergovernmental Panel on Climate Change provides a window onto the complex and, at times, antagonistic relationship between the Panel and Indian political and scientific communities. The Indian reaction to the error, made public in 2009, drew upon a national history of contestation around climate change science and corresponded with the establishment of a scientific assessment network, the Indian Network for Climate Change Assessment, which has given the state a new platform on which to bring together knowledge about the future climate. I argue that the Indian Network for Climate Change Assessment is indicative of the growing use of regional climate models within longer traditions of national territorial knowledge-making, allowing a rescaling of climate change according to local norms and practices of linking scientific knowledge to political action. I illustrate the complex co-production of the epistemic and the normative in climate politics, but also seek to show how co-productionist understandings of science and politics can function as strategic resources in the ongoing negotiation of social order. In this case, scientific rationalities and modes of environmental governance contribute to the contested epistemic construction of territory and the evolving spatiality of the modern nation state under a changing climate.

Climate Science Centers: Growing Federal and Academic Expertise in the Nation's Interests

NASA Astrophysics Data System (ADS)

Ryker, S. J.

2014-12-01

The U.S. Department of the Interior's (Interior) natural and cultural resource managers face increasingly complex challenges exacerbated by climate change. In 2009, under Secretarial Order 3289, Interior created eight regional Climate Science Centers managed by the U.S. Geological Survey's (USGS) National Climate Change and Wildlife Science Center and in partnership with universities. Secretarial Order 3289 provides a framework to coordinate climate change science and adaptation efforts across Interior and to integrate science and resource management expertise from Federal, State, Tribal, private, non-profit, and academic partners. In addition to broad research expertise, these Federal/university partnerships provide opportunities to develop a next generation of climate science professionals. These include opportunities to increase the climate science knowledge base of students and practicing professionals; build students' skills in working across the boundary between research and implementation; facilitate networking among researchers, students, and professionals for the application of research to on-the-ground issues; and support the science pipeline in climate-related fields through structured, intensive professional development. In 2013, Climate Science Centers supported approximately 10 undergraduates, 60 graduate students, and 26 postdoctoral researchers. Additional students trained by Climate Science Center-affiliated faculty also contribute valuable time and expertise, and are effectively part of the Climate Science Center network. The Climate Science Centers' education and training efforts have also reached a number of high school students interested in STEM careers, and professionals in natural and cultural resource management. The Climate Science Centers are coordinating to build on each other's successful education and training efforts. Early successes include several intensive education experiences, such as the Alaska Climate Science Center's Girls on Ice, the Northeast's Consortium Retreat, the Northwest's Climate Science Boot Camp; the whole-network Early Career Climate Forum; the South Central Climate Science Center's Minority Internship; and a growing curriculum through Interior's National Conservation Training Center.

Global drivers of the stratospheric polar vortex via nonlinear causal discovery

NASA Astrophysics Data System (ADS)

Kretschmer, M.; Runge, J.; Coumou, D.

2016-12-01

The stratospheric polar vortex plays a major role in the Northern Hemisphere midlatitudes, especially in driving extreme weather conditions. Many different global drivers, from Arctic sea ice to tropical climate patterns, are hypothesized to influence its stability, including linear and nonlinear mechanisms. Here a novel causal discovery approach, extending previous work [1], that is adapted to the particular challenges posed by such a high-dimensional dataset comprised of multiple, possibly nonlinearly coupled time series is demonstrated. While links in the reconstructed network can be called causal only with respect to the set of analyzed variables, the absence of causal links allows to assess where physical mechanisms are unlikely.The present work confirms recent results obtained with a similar, but linear, approach [2], regarding the impact of Barents and Kara sea ice concentrations, and extends the analysis also to tropical drivers to cover more proposed mechanisms. [1] Jakob Runge, Vladimir Petoukhov, and Jürgen Kurths, 2014: Quantifying the Strength and Delay of Climatic Interactions: The Ambiguities of Cross Correlation and a Novel Measure Based on Graphical Models. J. Climate 27, 720-739, doi: 10.1175/JCLI-D-13-00159.1.[2] Marlene Kretschmer, Dim Coumou, Jonathan F. Donges, and Jakob Runge, 2016: Using Causal Effect Networks to Analyze Different Arctic Drivers of Midlatitude Winter Circulation. J. Climate 29, 4069-4081, doi: 10.1175/JCLI-D-15-0654.1.

Geosphere-biosphere interactions in European Protected Areas: a view from the H2020 ECOPOTENTIAL Project

NASA Astrophysics Data System (ADS)

Provenzale, Antonello; Beierkuhnlein, Carl; Karnieli, Arnon; Marangi, Carmela; Giamberini, Mariasilvia; Imperio, Simona

2017-04-01

The large H2020 project ECOPOTENTIAL (2015-2019, 47 partners, contributing to GEO and GEOSS - http://www.ecopotential-project.eu/) is devoted to making best use of remote sensing and in situ data to improve future ecosystem benefits, adopting the view of ecosystems as one physical system with their environment, focusing on geosphere-biosphere interactions, Earth Critical Zone dynamics, Macrosystem Ecology and cross-scale interactions, the effect of extreme events and using Essential (Climate, Biodiversity and Ocean) Variables as descriptors of change. In ECOPOTENTIAL, remote sensing and in situ data are collected, processed and used for a better understanding of the ecosystem dynamics, analysing and modelling the effects of global changes on ecosystem functions and services, over an array of different ecosystem types, including mountain, marine, coastal, arid and semi-arid ecosystems. The project focuses on a network of Protected Areas of international relevance, that is representative of the range of environmental and biogeographical conditions characterizing Europe. Some of the activities of the project are devoted to detect and quantify the changes taking place in the Protected Areas, through the analysis of remote sensing observations, in-situ data and gridded climatic datasets. Likewise, the project aims at providing estimates of the future ecosystem conditions in different climate and environmental change scenarios. In all such endeavours, one is faced with cross-scale issues: downscaling of climate information to drive ecosystem response, and upscaling of local ecosystem changes to larger scales. So far, the analysis has been conducted mainly by using traditional methods, but there is wide room for improvement by using more refined approaches. In particular, a crucial question is how to upscale the information gained at single-site scale to larger, regional or continental scale, an issue that could benefit from using, for example, complex network analysis.

Lessons from the construction of a climate change adaptation plan: A Broads wetland case study.

PubMed

Turner, R Kerry; Palmieri, Maria Giovanna; Luisetti, Tiziana

2016-10-01

The dynamic nature of environmental change in coastal areas means that a flexible "learning by doing" management strategy has a number of advantages. This article lays out the principles of such a strategy and then assesses an actual planning and management process focused on climate change consequences for the Broads wetland on the East coast of England. The management strategy focused on the concept of ecosystem services (stocks and flows) provided by the coastal wetland and the threats and opportunities posed to the area by sea level rise and other climate change impacts. The analysis explores the process by which an adaptive management plan has been formulated and coproduced by a combination of centralized (vertical) and stakeholder social network (horizontal) arrangements. The process values where feasible the ecosystem services under threat and prioritizes response actions. Coastal management needs a careful balance between strategic requirements imposed at a national scale and local schemes that affect regional and/or local communities and social networks. These networks aided by electronic media have allowed groups to engage more rapidly and effectively with policy proposals. However, successful deliberation is conditioned by a range of context specific factors, including the type of social networks present and their relative competitive and/or complementary characteristics. The history of consultation and dialogue between official agencies and stakeholders also plays a part in contemporary deliberation processes and the success of their outcomes. Among the issues highlighted are the multiple dimensions of nature's value; the difficulty of quantifying some ecosystem service changes, especially for cultural services; and the problem of "stakeholder fatigue" complicating engagement arrangements. Integr Environ Assess Manag 2016;12:719-725. © 2016 SETAC. © 2016 SETAC.

Challenges in network science: Applications to infrastructures, climate, social systems and economics

NASA Astrophysics Data System (ADS)

Havlin, S.; Kenett, D. Y.; Ben-Jacob, E.; Bunde, A.; Cohen, R.; Hermann, H.; Kantelhardt, J. W.; Kertész, J.; Kirkpatrick, S.; Kurths, J.; Portugali, J.; Solomon, S.

2012-11-01

Network theory has become one of the most visible theoretical frameworks that can be applied to the description, analysis, understanding, design and repair of multi-level complex systems. Complex networks occur everywhere, in man-made and human social systems, in organic and inorganic matter, from nano to macro scales, and in natural and anthropogenic structures. New applications are developed at an ever-increasing rate and the promise for future growth is high, since increasingly we interact with one another within these vital and complex environments. Despite all the great successes of this field, crucial aspects of multi-level complex systems have been largely ignored. Important challenges of network science are to take into account many of these missing realistic features such as strong coupling between networks (networks are not isolated), the dynamics of networks (networks are not static), interrelationships between structure, dynamics and function of networks, interdependencies in given networks (and other classes of links, including different signs of interactions), and spatial properties (including geographical aspects) of networks. This aim of this paper is to introduce and discuss the challenges that future network science needs to address, and how different disciplines will be accordingly affected.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Treesearch

Kristina J. Anderson-Teixeira; Stuart J. Davies; Amy C. Bennett; Erika B. Gonzalez-Akre; Helene C. Muller-Landau; S. Joseph Wright; Kamariah Abu Salim; Angélica M. Almeyda Zambrano; Alfonso Alonso; Jennifer L. Baltzer; Yves Basset; Norman A. Bourg; Eben N. Broadbent; Warren Y. Brockelman; Sarayudh Bunyavejchewin; David F. R. P. Burslem; Nathalie Butt; Min Cao; Dairon Cardenas; George B. Chuyong; Keith Clay; Susan Cordell; Handanakere S. Dattaraja; Xiaobao Deng; Matteo Detto; Xiaojun Du; Alvaro Duque; David L. Erikson; Corneille E.N. Ewango; Gunter A. Fischer; Christine Fletcher; Robin B. Foster; Christian P. Giardina; Gregory S. Gilbert; Nimal Gunatilleke; Savitri Gunatilleke; Zhanqing Hao; William W. Hargrove; Terese B. Hart; Billy C.H. Hau; Fangliang He; Forrest M. Hoffman; Robert W. Howe; Stephen P. Hubbell; Faith M. Inman-Narahari; Patrick A. Jansen; Mingxi Jiang; Daniel J. Johnson; Mamoru Kanzaki; Abdul Rahman Kassim; David Kenfack; Staline Kibet; Margaret F. Kinnaird; Lisa Korte; Kamil Kral; Jitendra Kumar; Andrew J. Larson; Yide Li; Xiankun Li; Shirong Liu; Shawn K.Y. Lum; James A. Lutz; Keping Ma; Damian M. Maddalena; Jean-Remy Makana; Yadvinder Malhi; Toby Marthews; Rafizah Mat Serudin; Sean M. McMahon; William J. McShea; Hervé R. Memiaghe; Xiangcheng Mi; Takashi Mizuno; Michael Morecroft; Jonathan A. Myers; Vojtech Novotny; Alexandre A. de Oliveira; Perry S. Ong; David A. Orwig; Rebecca Ostertag; Jan den Ouden; Geoffrey G. Parker; Richard P. Phillips; Lawren Sack; Moses N. Sainge; Weiguo Sang; Kriangsak Sri-ngernyuang; Raman Sukumar; I-Fang Sun; Witchaphart Sungpalee; Hebbalalu Sathyanarayana Suresh; Sylvester Tan; Sean C. Thomas; Duncan W. Thomas; Jill Thompson; Benjamin L. Turner; Maria Uriarte; Renato Valencia; Marta I. Vallejo; Alberto Vicentini; Tomáš Vrška; Xihua Wang; Xugao Wang; George Weiblen; Amy Wolf; Han Xu; Sandra Yap; Jess Zimmerman

2014-01-01

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses...

Nonlinear dynamics of ice-wedge networks and resulting sensitivity to severe cooling events.

PubMed

Plug, L J; Werner, B T

2002-06-27

Patterns of subsurface wedges of ice that form along cooling-induced tension fractures, expressed at the ground surface by ridges or troughs spaced 10 30 m apart, are ubiquitous in polar lowlands. Fossilized ice wedges, which are widespread at lower latitudes, have been used to infer the duration and mean temperature of cold periods within Proterozoic and Quaternary climates, and recent climate trends have been inferred from fracture frequency in active ice wedges. Here we present simulations from a numerical model for the evolution of ice-wedge networks over a range of climate scenarios, based on the interactions between thermal tensile stress, fracture and ice wedges. We find that short-lived periods of severe cooling permanently alter the spacing between ice wedges as well as their fracture frequency. This affects the rate at which the widths of ice wedges increase as well as the network's response to subsequent climate change. We conclude that wedge spacing and width in ice-wedge networks mainly reflect infrequent episodes of rapidly falling ground temperatures rather than mean conditions.

Early Mars Climate Revisited With a Global Probability Map of Martian Valley Network Origin and Distribution

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.; Osinski, G. R.

2016-12-01

Valley networks are among the most arresting features on the surface of Mars. Their provocative morphologic resemblance to river valleys on Earth has lead many scientists to argue for Martian river valleys in a "warm and wet" climate scenario, with conditions similar to the terrestrial mid-to-low latitudes. However, this warm scenario is difficult to reconcile with climate models for an Early Mars receiving radiation from a fainter young Sun. Moreover, recent models suggest a colder scenario, with conditions more similar to present day Greenland or Antarctica. Here we use three independent characterization schemes to show quantitative evidence for fluvial, glacial, groundwater sapping and subglacial meltwater channels to build the first global probability map of Martian valley networks. We distinguish a SW-NE corridor of fluvial drainage networks spanning latitudes from 30ºS to 30ºN. We identify additional widespread patterns related to glaciation, subglacial drainage and channels incised by groundwater springs. This global characterization of Martian valleys has profound implications for the average climate of early Mars as well as its variability in space and time.

Interpretation of link fluctuations in climate networks during El Niño periods

NASA Astrophysics Data System (ADS)

Martin, E. A.; Paczuski, M.; Davidsen, J.

2013-05-01

Recent work has shown that the topologies of functional climate networks are sensitive to El Niño events. One important interpretation of the findings was that parts of the globe act in correlated relationships which become weaker, on average, during El Niño periods (this was shown using monthly averaged data where no time lag is required, and with daily averaged data where time lags were utilized). In contrast to this, we show that El Niño periods actually exhibit higher correlations than “Normal” climate conditions, while typically having lower correlations than La Niña periods. We also show that it is crucial to establish the sensitivity and the robustness of a given method used to extract functional climate networks —parameters such as time lags can significantly influence and even totally alter the outcome.

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

NASA Astrophysics Data System (ADS)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

NASA Astrophysics Data System (ADS)

Gilligan, J. M.; John, N. J.; van der Linden, M.

2015-12-01

Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest.

PubMed

Albert, Loren P; Keenan, Trevor F; Burns, Sean P; Huxman, Travis E; Monson, Russell K

2017-05-01

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone.

Application of Network Analysis to Identify and Map Relationships between Information Systems in the context of Arctic Sustainability

NASA Astrophysics Data System (ADS)

Kontar, Y. Y.

2017-12-01

The Arctic Council is an intergovernmental forum promoting cooperation, coordination and interaction among the Arctic States and indigenous communities on issues of sustainable development and environmental protection in the North. The work of the Council is primarily carried out by six Working Groups: Arctic Contaminants Action Program, Arctic Monitoring and Assessment Programme, Conservation of Arctic Flora and Fauna, Emergency Prevention, Preparedness and Response, Protection of the Arctic Marine Environment, and Sustainable Development Working Group. The Working Groups are composed of researchers and representatives from government agencies. Each Working Group issues numerous scientific assessments and reports on a broad field of subjects, from climate change to emergency response in the Arctic. A key goal of these publications is to contribute to policy-making in the Arctic. Complex networks of information systems and the connections between the diverse elements within the systems have been identified via network analysis. This allowed to distinguish data sources that were used in the composition of the primary publications of the Working Groups. Next step is to implement network analysis to identify and map the relationships between the Working Groups and policy makers in the Arctic.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

ATP3 Unified Field Study Data

DOE Data Explorer

Wolfrum, Ed (ORCID:0000000273618931); Knoshug, Eric (ORCID:000000025709914X); Laurens, Lieve (ORCID:0000000349303267); Harmon, Valerie; Dempster, Thomas (ORCID:000000029550488X); McGowan, John (ORCID:0000000266920518); Rosov, Theresa; Cardello, David; Arrowsmith, Sarah; Kempkes, Sarah; Bautista, Maria; Lundquist, Tryg; Crowe, Brandon; Murawsky, Garrett; Nicolai, Eric; Rowe, Egan; Knurek, Emily; Javar, Reyna; Saracco Alvarez, Marcela; Schlosser, Steve; Riddle, Mary; Withstandley, Chris; Chen, Yongsheng; Van Ginkel, Steven; Igou, Thomas; Xu, Chunyan; Hu, Zixuan

2017-10-20

ATP3 Unified Field Study Data The Algae Testbed Public-Private Partnership (ATP3) was established with the goal of investigating open pond algae cultivation across different geographic, climatic, seasonal, and operational conditions while setting the benchmark for quality data collection, analysis, and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework, the Unified Field Studies (UFS) were designed to characterize the cultivation of different algal strains during all 4 seasons across this testbed network. The dataset presented here is the complete, curated, climatic, cultivation, harvest, and biomass composition data for each season at each site. These data enable others to do in-depth cultivation, harvest, techno-economic, life cycle, resource, and predictive growth modeling analysis, as well as develop crop protection strategies for the nascent algae industry. NREL Sub award Number: DE-AC36-08-GO28308

A spatiotemporal analysis of U.S. station temperature trends over the last century

NASA Astrophysics Data System (ADS)

Capparelli, V.; Franzke, C.; Vecchio, A.; Freeman, M. P.; Watkins, N. W.; Carbone, V.

2013-07-01

This study presents a nonlinear spatiotemporal analysis of 1167 station temperature records from the United States Historical Climatology Network covering the period from 1898 through 2008. We use the empirical mode decomposition method to extract the generally nonlinear trends of each station. The statistical significance of each trend is assessed against three null models of the background climate variability, represented by stochastic processes of increasing temporal correlation length. We find strong evidence that more than 50% of all stations experienced a significant trend over the last century with respect to all three null models. A spatiotemporal analysis reveals a significant cooling trend in the South-East and significant warming trends in the rest of the contiguous U.S. It also shows that the warming trend appears to have migrated equatorward. This shows the complex spatiotemporal evolution of climate change at local scales.

Quantification of biophysical adaptation benefits from Climate-Smart Agriculture using a Bayesian Belief Network.

PubMed

de Nijs, Patrick J; Berry, Nicholas J; Wells, Geoff J; Reay, Dave S

2014-10-20

The need for smallholder farmers to adapt their practices to a changing climate is well recognised, particularly in Africa. The cost of adapting to climate change in Africa is estimated to be $20 to $30 billion per year, but the total amount pledged to finance adaptation falls significantly short of this requirement. The difficulty of assessing and monitoring when adaptation is achieved is one of the key barriers to the disbursement of performance-based adaptation finance. To demonstrate the potential of Bayesian Belief Networks for describing the impacts of specific activities on climate change resilience, we developed a simple model that incorporates climate projections, local environmental data, information from peer-reviewed literature and expert opinion to account for the adaptation benefits derived from Climate-Smart Agriculture activities in Malawi. This novel approach allows assessment of vulnerability to climate change under different land use activities and can be used to identify appropriate adaptation strategies and to quantify biophysical adaptation benefits from activities that are implemented. We suggest that multiple-indicator Bayesian Belief Network approaches can provide insights into adaptation planning for a wide range of applications and, if further explored, could be part of a set of important catalysts for the expansion of adaptation finance.

Quantification of biophysical adaptation benefits from Climate-Smart Agriculture using a Bayesian Belief Network

NASA Astrophysics Data System (ADS)

de Nijs, Patrick J.; Berry, Nicholas J.; Wells, Geoff J.; Reay, Dave S.

2014-10-01

The need for smallholder farmers to adapt their practices to a changing climate is well recognised, particularly in Africa. The cost of adapting to climate change in Africa is estimated to be $20 to $30 billion per year, but the total amount pledged to finance adaptation falls significantly short of this requirement. The difficulty of assessing and monitoring when adaptation is achieved is one of the key barriers to the disbursement of performance-based adaptation finance. To demonstrate the potential of Bayesian Belief Networks for describing the impacts of specific activities on climate change resilience, we developed a simple model that incorporates climate projections, local environmental data, information from peer-reviewed literature and expert opinion to account for the adaptation benefits derived from Climate-Smart Agriculture activities in Malawi. This novel approach allows assessment of vulnerability to climate change under different land use activities and can be used to identify appropriate adaptation strategies and to quantify biophysical adaptation benefits from activities that are implemented. We suggest that multiple-indicator Bayesian Belief Network approaches can provide insights into adaptation planning for a wide range of applications and, if further explored, could be part of a set of important catalysts for the expansion of adaptation finance.

Toward a phenology network in Turkey

NASA Astrophysics Data System (ADS)

Dalfes, H. N.; Ülgen, H.; Zeydanli, U.; Durak, A. T.

2012-04-01

All climate projections indicate that drastic changes are to occur in the Mediterranean Basin and Southwestern Asia. Detailed studies also foresee strong patterns of change in seasonality for most climate fields all across the country, threatening Turkey's rich biodiversity and diverse ecosystems already in trouble due to massive land use changes and careless resource extraction projects. It is therefore obvious that climate impact studies can benefit from detailed and continuous monitoring of relationships between climate and natural systems. Recently started efforts to build a phenology network for Turkey will hopefully constitute a component of a more comprehensive ecological observation infrastructure. The Phenology Network of Turkey Project saw its debut as a joint initiative of an academic institution (Istanbul Technical University) and a research NGO (Nature Conservation Center). It has been decided from the very beginning to rely a much as possible on Internet technologies (provided by the National High Performance Computing Center of Turkey). The effort is also inspired by and collaborates with already established networks in general and USA National Phenology Network in particular. Many protocols, instructional materials and Nature's Notebook application has been barrowed from the USA NPN. The project has been designed from the start as a two-faceted effort: an infrastructure to accumulate/provide useful data to climate/ecosystem research communities and a 'citizen science' project to raise nature and climate change awareness among all components of the society in Turkey in general and secondary education teachers and students in particular. It has been opted to start by gathering plant phenological data. A set with 20 plant species has been designed to serve as a countrywide 'calibration set'. It is also anticipated to salvage and extend as much of possible historical animal (especially bird and butterfly) observations.

Evaluating the Connectivity of a Protected Areas' Network under the Prism of Global Change: The Efficiency of the European Natura 2000 Network for Four Birds of Prey

PubMed Central

Mazaris, Antonios D.; Papanikolaou, Alexandra D.; Barbet-Massin, Morgane; Kallimanis, Athanasios S.; Jiguet, Frédéric; Schmeller, Dirk S.; Pantis, John D.

2013-01-01

Climate and land use changes are major threats to biodiversity. To preserve biodiversity, networks of protected areas have been established worldwide, like the Natura 2000 network across the European Union (EU). Currently, this reserve network consists of more than 26000 sites covering more than 17% of EU terrestrial territory. Its efficiency to mitigate the detrimental effects of land use and climate change remains an open research question. Here, we examined the potential current and future geographical ranges of four birds of prey under scenarios of both land use and climate changes. By using graph theory, we examined how the current Natura 2000 network will perform in regard to the conservation of these species. This approach determines the importance of a site in regard to the total network and its connectivity. We found that sites becoming unsuitable due to climate change are not a random sample of the network, but are less connected and contribute less to the overall connectivity than the average site and thus their loss does not disrupt the full network. Hence, the connectivity of the remaining network changed only slightly from present day conditions. Our findings highlight the need to establish species-specific management plans with flexible conservation strategies ensuring protection under potential future range expansions. Aquila pomarina is predicted to disappear from the southern part of its range and to become restricted to northeastern Europe. Gyps fulvus, Aquila chrysaetos, and Neophron percnopterus are predicted to locally lose some suitable sites; hence, some isolated small populations may become extinct. However, their geographical range and metapopulation structure will remain relatively unaffected throughout Europe. These species would benefit more from an improved habitat quality and management of the existing network of protected areas than from increased connectivity or assisted migration. PMID:23527237

Trends and Controls of inter-annual Variability in the Carbon Budget of Terrestrial Ecosystems

NASA Astrophysics Data System (ADS)

Cescatti, A.; Marcolla, B.

2014-12-01

The climate sensitivity of the terrestrial carbon budget will substantially affect the sign and strength of the land-climate feedbacks and the future climate trajectories. Current trends in the inter-annual variability of terrestrial carbon fluxes (IAV) may contribute to clarify the relative role of physical and biological controls of ecosystem responses to climate change. For this purpose we investigated how recent climate variability has impacted the carbon fluxes at long-term FLUXNET sites. Using a novel method, the IAV has been factored out in climate induced variability (physical control), variability due to changes in ecosystem functioning (biological control) and the interaction of the two terms. The relative control of the main climatic drivers (temperature, water availability) on the physical and biological sources of IAV has been investigated using both site level fluxes and global gridded products generated from the up-scaling of flux data. Results of this analysis highlight the fundamental role of precipitation trends on the pattern of IAV in the last 30 years. Our findings on the spatial/temporal trends of IAV have been finally confirmed using the signal derived from the global network of atmospheric CO2 concentrations measurements.

Extraction of Martian valley networks from digital topography

NASA Technical Reports Server (NTRS)

Stepinski, T. F.; Collier, M. L.

2004-01-01

We have developed a novel method for delineating valley networks on Mars. The valleys are inferred from digital topography by an autonomous computer algorithm as drainage networks, instead of being manually mapped from images. Individual drainage basins are precisely defined and reconstructed to restore flow continuity disrupted by craters. Drainage networks are extracted from their underlying basins using the contributing area threshold method. We demonstrate that such drainage networks coincide with mapped valley networks verifying that valley networks are indeed drainage systems. Our procedure is capable of delineating and analyzing valley networks with unparalleled speed and consistency. We have applied this method to 28 Noachian locations on Mars exhibiting prominent valley networks. All extracted networks have a planar morphology similar to that of terrestrial river networks. They are characterized by a drainage density of approx.0.1/km, low in comparison to the drainage density of terrestrial river networks. Slopes of "streams" in Martian valley networks decrease downstream at a slower rate than slopes of streams in terrestrial river networks. This analysis, based on a sizable data set of valley networks, reveals that although valley networks have some features pointing to their origin by precipitation-fed runoff erosion, their quantitative characteristics suggest that precipitation intensity and/or longevity of past pluvial climate were inadequate to develop mature drainage basins on Mars.

The Role of Surface Water for the Branching Geometry of Mars' Channel Networks

NASA Astrophysics Data System (ADS)

Seybold, H. F.; Rothman, D.; Kirchner, J. W.

2016-12-01

The controversy over the origin of Mars' channel networks is almost as old as their discovery 150 years ago. In recent decades, new Mars probe missions have revealed detailed network structures, and new studies suggest that Mars once had an active hydrologic cycle. But how this water flowed and how it could have carved these huge channel networks remains unclear. A recent analysis of high-resolution data for the Continental United States suggests that climate leaves a characteristic imprint in the branching geometry of stream networks: arid regions dominated by overland or near-surface flows have much narrower branching angles than humid regions with greater groundwater recharge. Based on this result we analyze the channel networks of Mars, and find that their geometry resembles those created by near-surface and overland flows on Earth. This result gives additional support to the hypothesis that Mars once had a more active hydrologic cycle, with liquid water flowing over its surface.

Topical Collection: Climate-change research by early-career hydrogeologists

NASA Astrophysics Data System (ADS)

Re, Viviana; Maldaner, Carlos H.; Gurdak, Jason J.; Leblanc, Marc; Resende, Tales Carvalho; Stigter, Tibor Y.

2018-05-01

Scientific outreach, international networking, collaboration and adequate courses are needed in both developed and developing countries to enable early-career hydrogeologists to promote long-term multidisciplinary approaches to cope with climate-change issues and emphasize the importance of groundwater in a global strategy for adaptation. One such collaboration has involved the Early Career Hydrogeologists' Network of the International Association of Hydrogeologists (ECHN-IAH) and the UNESCO International Hydrological Programme's (IHP) Groundwater Resources Assessment under the Pressures of Humanity and Climate Changes (GRAPHIC) project. This collaboration seeks to foster the education and involvement of the future generation of water leaders in the debate over groundwater and climate change.

NOAA/NCEI/Regional Climate Services: Working with Partners and Stakeholders across a Wide Network

NASA Astrophysics Data System (ADS)

Mecray, E. L.

2015-12-01

Federal agencies all require plans to be prepared at the state level that outline the implementation of funding to address wildlife habitat, human health, transportation infrastructure, coastal zone management, environmental management, emergency management, and others. These plans are now requiring the consideration of changing climate conditions. So where does a state turn to discuss lessons learned, obtain tools and information to assess climate conditions, and to work with other states in their region? Regional networks and collaboratives are working to deliver this sector by sector. How do these networks work? Do they fit together in any way? What similarities and differences exist? Is anyone talking across these lines to find common climate information requirements? A sketch is forming that links these efforts, not by blending the sectors, but by finding the areas where coordination is critical, where information needs are common, and where delivery mechanisms can be streamlined. NOAA/National Centers for Environmental Information's Regional Climate Services Directors have been working at the interface of stakeholder-driven information delivery since 2010. This talk will outline the regional climate services delivery framework for the Eastern Region, with examples of regional products and information.

Online matchmaking: It's not just for dating sites anymore! Connecting the Climate Voices Science Speakers Network to Educators

NASA Astrophysics Data System (ADS)

Wegner, K.; Herrin, S.; Schmidt, C.

2015-12-01

Scientists play an integral role in the development of climate literacy skills - for both teachers and students alike. By partnering with local scientists, teachers can gain valuable insights into the science practices highlighted by the Next Generation Science Standards (NGSS), as well as a deeper understanding of cutting-edge scientific discoveries and local impacts of climate change. For students, connecting to local scientists can provide a relevant connection to climate science and STEM skills. Over the past two years, the Climate Voices Science Speakers Network (climatevoices.org) has grown to a robust network of nearly 400 climate science speakers across the United States. Formal and informal educators, K-12 students, and community groups connect with our speakers through our interactive map-based website and invite them to meet through face-to-face and virtual presentations, such as webinars and podcasts. But creating a common language between scientists and educators requires coaching on both sides. In this presentation, we will present the "nitty-gritty" of setting up scientist-educator collaborations, as well as the challenges and opportunities that arise from these partnerships. We will share the impact of these collaborations through case studies, including anecdotal feedback and metrics.

Online Matchmaking: It's Not Just for Dating Sites Anymore! Connecting the Climate Voices Science Speakers Network to Educators

NASA Technical Reports Server (NTRS)

Wegner, Kristin; Herrin, Sara; Schmidt, Cynthia

2015-01-01

Scientists play an integral role in the development of climate literacy skills - for both teachers and students alike. By partnering with local scientists, teachers can gain valuable insights into the science practices highlighted by the Next Generation Science Standards (NGSS), as well as a deeper understanding of cutting-edge scientific discoveries and local impacts of climate change. For students, connecting to local scientists can provide a relevant connection to climate science and STEM skills. Over the past two years, the Climate Voices Science Speakers Network (climatevoices.org) has grown to a robust network of nearly 400 climate science speakers across the United States. Formal and informal educators, K-12 students, and community groups connect with our speakers through our interactive map-based website and invite them to meet through face-to-face and virtual presentations, such as webinars and podcasts. But creating a common language between scientists and educators requires coaching on both sides. In this presentation, we will present the "nitty-gritty" of setting up scientist-educator collaborations, as well as the challenges and opportunities that arise from these partnerships. We will share the impact of these collaborations through case studies, including anecdotal feedback and metrics.

The Social Network of Tracer Variations and O(100) Uncertain Photochemical Parameters in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Labute, M.; Chowdhary, K.; Debusschere, B.; Cameron-Smith, P. J.

2014-12-01

Simulating the atmospheric cycles of ozone, methane, and other radiatively important trace gases in global climate models is computationally demanding and requires the use of 100's of photochemical parameters with uncertain values. Quantitative analysis of the effects of these uncertainties on tracer distributions, radiative forcing, and other model responses is hindered by the "curse of dimensionality." We describe efforts to overcome this curse using ensemble simulations and advanced statistical methods. Uncertainties from 95 photochemical parameters in the trop-MOZART scheme were sampled using a Monte Carlo method and propagated through 10,000 simulations of the single column version of the Community Atmosphere Model (CAM). The variance of the ensemble was represented as a network with nodes and edges, and the topology and connections in the network were analyzed using lasso regression, Bayesian compressive sensing, and centrality measures from the field of social network theory. Despite the limited sample size for this high dimensional problem, our methods determined the key sources of variation and co-variation in the ensemble and identified important clusters in the network topology. Our results can be used to better understand the flow of photochemical uncertainty in simulations using CAM and other climate models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC).

Famine Early Warning Systems Network (FEWS NET) Contributions to Strengthening Resilience and Sustainability for the East African Community

NASA Astrophysics Data System (ADS)

Budde, M. E.; Galu, G.; Funk, C. C.; Verdin, J. P.; Rowland, J.

2014-12-01

The Planning for Resilience in East Africa through Policy, Adaptation, Research, and Economic Development (PREPARED) is a multi-organizational project aimed at mainstreaming climate-resilient development planning and program implementation into the East African Community (EAC). The Famine Early Warning Systems Network (FEWS NET) has partnered with the PREPARED project to address three key development challenges for the EAC; 1) increasing resiliency to climate change, 2) managing trans-boundary freshwater biodiversity and conservation and 3) improving access to drinking water supply and sanitation services. USGS FEWS NET has been instrumental in the development of gridded climate data sets that are the fundamental building blocks for climate change adaptation studies in the region. Tools such as the Geospatial Climate Tool (GeoCLIM) have been developed to interpolate time-series grids of precipitation and temperature values from station observations and associated satellite imagery, elevation data, and other spatially continuous fields. The GeoCLIM tool also allows the identification of anomalies and assessments of both their frequency of occurrence and directional trends. A major effort has been put forth to build the capacities of local and regional institutions to use GeoCLIM to integrate their station data (which is not typically available to the public) into improved national and regional gridded climate data sets. In addition to the improvements and capacity building activities related to geospatial analysis tools, FEWS NET will assist in two other areas; 1) downscaling of climate change scenarios and 2) vulnerability impact assessments. FEWS NET will provide expertise in statistical downscaling of Global Climate Model output fields and work with regional institutions to assess results of other downscaling methods. Completion of a vulnerability impact assessment (VIA) involves the examination of sectoral consequences in identified climate "hot spots". FEWS NET will lead the VIA for the agriculture and food security sector, but will also provide key geospatial layers needed by multiple sectors in the areas of exposure, sensitivity, and adaptive capacity. Project implementation will strengthen regional coordination in policy-making, planning, and response to climate change issues.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

Climatic similarity and biological exchange in the worldwide airline transportation network

PubMed Central

Tatem, Andrew J; Hay, Simon I

2007-01-01

Recent increases in the rates of biological invasion and spread of infectious diseases have been linked to the continued expansion of the worldwide airline transportation network (WAN). Here, the global structure of the WAN is analysed in terms of climatic similarity to illuminate the risk of deliberate or accidental movements of climatically sensitive organisms around the world. From over 44 000 flight routes, we show, for each month of an average year, (i) those scheduled routes that link the most spatially distant but climatically similar airports, (ii) the climatically best-connected airports, and (iii) clusters of airports with similar climatic features. The way in which traffic volumes alter these findings is also examined. Climatic similarity across the WAN is skewed (most geographically close airports are climatically similar) but heavy-tailed (there are considerable numbers of geographically distant but climatically similar airports), with climate similarity highest in the June–August period, matching the annual peak in air traffic. Climatically matched, geographically distant airports form subnetworks within the WAN that change throughout the year. Further, the incorporation of passenger and freight traffic data highlight at greater risk of invasion those airports that are climatically well connected by numerous high capacity routes. PMID:17426013

Drought prediction using co-active neuro-fuzzy inference system, validation, and uncertainty analysis (case study: Birjand, Iran)

NASA Astrophysics Data System (ADS)

Memarian, Hadi; Pourreza Bilondi, Mohsen; Rezaei, Majid

2016-08-01

This work aims to assess the capability of co-active neuro-fuzzy inference system (CANFIS) for drought forecasting of Birjand, Iran through the combination of global climatic signals with rainfall and lagged values of Standardized Precipitation Index (SPI) index. Using stepwise regression and correlation analyses, the signals NINO 1 + 2, NINO 3, Multivariate Enso Index, Tropical Southern Atlantic index, Atlantic Multi-decadal Oscillation index, and NINO 3.4 were recognized as the effective signals on the drought event in Birjand. Based on the results from stepwise regression analysis and regarding the processor limitations, eight models were extracted for further processing by CANFIS. The metrics P-factor and D-factor were utilized for uncertainty analysis, based on the sequential uncertainty fitting algorithm. Sensitivity analysis showed that for all models, NINO indices and rainfall variable had the largest impact on network performance. In model 4 (as the model with the lowest error during training and testing processes), NINO 1 + 2(t-5) with an average sensitivity of 0.7 showed the highest impact on network performance. Next, the variables rainfall, NINO 1 + 2(t), and NINO 3(t-6) with the average sensitivity of 0.59, 0.28, and 0.28, respectively, could have the highest effect on network performance. The findings based on network performance metrics indicated that the global indices with a time lag represented a better correlation with El Niño Southern Oscillation (ENSO). Uncertainty analysis of the model 4 demonstrated that 68 % of the observed data were bracketed by the 95PPU and D-Factor value (0.79) was also within a reasonable range. Therefore, the fourth model with a combination of the input variables NINO 1 + 2 (with 5 months of lag and without any lag), monthly rainfall, and NINO 3 (with 6 months of lag) and correlation coefficient of 0.903 (between observed and simulated SPI) was selected as the most accurate model for drought forecasting using CANFIS in the climatic region of Birjand.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

CTFS/ForestGEO: A global network to monitor forest interactions with a changing climate

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Muller-Landau, H.; McMahon, S.; Davies, S. J.

2013-12-01

Forests are an influential component of the global carbon cycle and strongly influence Earth's climate. Climate change is altering the dynamics of forests globally, which may result in significant climate feedbacks. Forest responses to climate change entail both short-term ecophysiological responses and longer-term directional shifts in community composition. These short- and long-term responses of forest communities to climate change may be better understood through long-term monitoring of large forest plots globally using standardized methodology. Here, we describe a global network of forest research plots (CTFS/ForestGEO) of utility for understanding forest responses to climate change and consequent feedbacks to the climate system. CTFS/ForestGEO is an international network consisting of 51 sites ranging in size from 2-150 ha (median size: 25 ha) and spanning from 25°S to 52°N latitude. At each site, every individual > 1cm DBH is mapped and identified, and recruitment, growth, and mortality are monitored every 5 years. Additional measurements include aboveground productivity, carbon stocks, soil nutrients, plant functional traits, arthropod and vertebrates monitoring, DNA barcoding, airborne and ground-based LiDAR, micrometeorology, and weather monitoring. Data from this network are useful for understanding how forest ecosystem structure and function respond to spatial and temporal variation in abiotic drivers, parameterizing and evaluating ecosystem and earth system models, aligning airborne and ground-based measurements, and identifying directional changes in forest productivity and composition. For instance, CTFS/ForestGEO data have revealed that solar radiation and night-time temperature are important drivers of aboveground productivity in moist tropical forests; that tropical forests are mixed in terms of productivity and biomass trends over the past couple decades; and that the composition of Panamanian forests has shifted towards more drought-tolerant species. Ongoing monitoring will be vital to understanding global forest dynamics in an era of climate change.

Analysis of hydrological processes across the Northern Eurasia with recently re-developed online informational system

NASA Astrophysics Data System (ADS)

Shiklomanov, A. I.; Proussevitch, A. A.; Gordov, E. P.; Okladnikov, I.; Titov, A. G.

2016-12-01

The volume of georeferenced datasets used for hydrology and climate research is growing immensely due to recent advances in modeling, high performance computers, and sensor networks, as well as initiation of a set of large scale complex global and regional monitoring experiments. To facilitate the management and analysis of these extensive data pools we developed Web-based data management, visualization, and analysis system - RIMS - http://earthatlas.sr.unh.edu/ (Rapid Integrated Mapping and Analysis System) with a focus on hydrological applications. Recently, under collaboration with Russian colleagues from the Institute of Monitoring of Climatic and Ecological Systems SB RAS, Russia, we significantly re-designed the RIMS to include the latest Web and GIS technologies in compliance with the Open Geospatial Consortium (OGC) standards. An upgraded RIMS can be successfully applied to address multiple research problems using an extensive data archive and embedded tools for data computations, visualizations and distributions. We will demonstrate current possibility of the system providing several results of applied data analysis fulfilled for territory of the Northern Eurasia. These results will include the analysis of historical, contemporary and future changes in climate and hydrology based on station and gridded data, investigations of recent extreme hydrological events, their anomalies, causes and potential impacts, and creation and analysis of new data sets through integration of social and geophysical data.

Global terrestrial water storage connectivity revealed using complex climate network analyses

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

PAVICS: A platform for the Analysis and Visualization of Climate Science - adopting a workflow-based analysis method for dealing with a multitude of climate data sources

NASA Astrophysics Data System (ADS)

Gauvin St-Denis, B.; Landry, T.; Huard, D. B.; Byrns, D.; Chaumont, D.; Foucher, S.

2017-12-01

As the number of scientific studies and policy decisions requiring tailored climate information continues to increase, the demand for support from climate service centers to provide the latest information in the format most helpful for the end-user is also on the rise. Ouranos, being one such organization based in Montreal, has partnered with the Centre de recherche informatique de Montreal (CRIM) to develop a platform that will offer climate data products that have been identified as most useful for users through years of consultation. The platform is built as modular components that target the various requirements of climate data analysis. The data components host and catalog NetCDF data as well as geographical and political delimitations. The analysis components are made available as atomic operations through Web Processing Service (WPS) or as workflows, whereby the operations are chained through a simple JSON structure and executed on a distributed network of computing resources. The visualization components range from Web Map Service (WMS) to a complete frontend for searching the data, launching workflows and interacting with maps of the results. Each component can easily be deployed and executed as an independent service through the use of Docker technology and a proxy is available to regulate user workspaces and access permissions. PAVICS includes various components from birdhouse, a collection of WPS initially developed by the German Climate Research Center (DKRZ) and Institut Pierre Simon Laplace (IPSL) and is designed to be highly interoperable with other WPS as well as many Open Geospatial Consortium (OGC) standards. Further connectivity is made with the Earth System Grid Federation (ESGF) nodes and local results are made searchable using the same API terminology. Other projects conducted by CRIM that integrate with PAVICS include the OGC Testbed 13 Innovation Program (IP) initiative that will enhance advanced cloud capabilities, application packaging deployment processes, as well as enabling Earth Observation (EO) processes relevant to climate. As part of its experimental agenda, working implementations of scalable machine learning on big climate data with Spark and SciSpark were delivered.

Climate-change scenarios

USGS Publications Warehouse

Wagner, Frederic H.; Stohlgren, T.J.; Baldwin, C.K.; Mearns, L.O.; Wagner, Frederic H.

2003-01-01

Three procedures were used to develop a set of plausible scenarios of anthropogenic climate change by the year 2100 that could be posed to the sectors selected for assessment (Fig. 2.2). First, a workshop of climatologists with expertise in western North American climates was convened from September 10-12, 1998 at the National Center for Ecological Analysis and Synthesis in Santa Barbara, CA to discuss and propose a set of scenarios for the Rocky Mountain/Great Basin (RMGB) region.Secondly, the 20th-century climate record was analyzed to determine what trends might have occurred during the period. Since CO2 and other greenhouse gases increased during the century, it was reasonable to examine whether the changes projected for the 21st century had begun to appear during the 20th, at least qualitatively though not quantitatively.Third, on the assumption of a two-fold increase in atmospheric CO2 by 2100, climate-change scenarios for the 21st century were projected with two, state-of-the-art computer models that simulate the complex interactions between earth, atmosphere, and ocean to produce the earth’s climate system. Each of the last two procedures has its strengths and weaknesses, and each can function to some degree as a check on the other. The historical analysis has the advantage of using empirical measurements of actual climate change taken over an extensive network of measuring stations. These make it possible to subdivide a large region like the RMGB into subreqions to assess the uniformity of climate and climate change over the region. And the historical measurements can to some degree serve as a check on the GCM simulations when the two are compared over the same time period.

Generating Southern Africa Precipitation Forecast Using the FEWS Engine, a New Application for the Google Earth Engine

NASA Astrophysics Data System (ADS)

Landsfeld, M. F.; Hegewisch, K.; Daudert, B.; Morton, C.; Husak, G. J.; Friedrichs, M.; Funk, C. C.; Huntington, J. L.; Abatzoglou, J. T.; Verdin, J. P.

2016-12-01

The Famine Early Warning Systems Network (FEWS NET) focuses on food insecurity in developing nations and provides objective, evidence-based analysis to help government decision-makers and relief agencies plan for and respond to humanitarian emergencies. The network of FEWS NET analysts and scientists require flexible, interactive tools to aid in their monitoring and research efforts. Because they often work in bandwidth-limited regions, lightweight Internet tools and services that bypass the need for downloading massive datasets are preferred for their work. To support food security analysis FEWS NET developed a custom interface for the Google Earth Engine (GEE). GEE is a platform developed by Google to support scientific analysis of environmental data in their cloud computing environment. This platform allows scientists and independent researchers to mine massive collections of environmental data, leveraging Google's vast computational resources for purposes of detecting changes and monitoring the Earth's surface and climate. GEE hosts an enormous amount of satellite imagery and climate archives, one of which is the Climate Hazards Group Infrared Precipitation with Stations dataset (CHIRPS). CHIRPS precipitation dataset is a key input for FEWS NET monitoring and forecasting efforts. In this talk we introduce the FEWS Engine interface. We present an application that highlights the utility of FEWS Engine for forecasting the upcoming seasonal precipitation of southern Africa. Specifically, the current state of ENSO is assessed and used to identify similar historical seasons. The FEWS Engine compositing tool is used to examine rainfall and other environmental data for these analog seasons. The application illustrates the unique benefits of using FEWS Engine for on-the-fly food security scenario development.

The PAGES 2k Network, Phase 3: Themes and Call for Participation

NASA Astrophysics Data System (ADS)

von Gunten, L.; Mcgregor, H. V.; Martrat, B.; St George, S.; Neukom, R.; Bothe, O.; Linderholm, H. W.; Phipps, S. J.; Abram, N.

2017-12-01

The past 2000 years (the "2k" interval) provides critical context for understanding recent anthropogenic forcing of the climate and provides baseline information about the characteristics of natural climate variability. It also presents opportunities to improve the interpretation of proxy observations and to evaluate the climate models used to make future projections. Phases 1 and 2 of the PAGES 2k Network focussed on building regional and global surface temperature reconstructions for terrestrial regions and the oceans, and comparing these with model simulations to identify mechanisms of climate variation on interannual to bicentennial time scales. Phase 3 was launched in May 2017 and aims to address major questions around past hydroclimate, climate processes and proxy uncertainties. Its scientific themes are: Theme 1: "Climate Variability, Modes and Mechanisms"Further understand the mechanisms driving regional climate variability and change on interannual to centennial time scales; Theme 2: "Methods and Uncertainties"Reduce uncertainties in the interpretation of observations imprinted in paleoclimatic archives by environmental sensors; Theme 3: "Proxy and Model Understanding"Identify and analyse the extent of agreement between reconstructions and climate model simulations. Research is organized as a linked network of well-defined projects, identified and led by 2k community members. The 2k projects focus on specific scientific questions aligned with Phase 3 themes, rather than being defined along regional boundaries. New 2k projects can be proposed at any time at http://www.pastglobalchanges.org/ini/wg/2k-network/projects An enduring element of PAGES 2k is a culture of collegiality, transparency, and reciprocity. Phase 3 seeks to stimulate community based projects and facilitate collaboration between researchers from different regions and career stages, drawing on the breadth and depth of the global PAGES 2k community. All PAGES 2k projects also promote best practises in data stewardship for the research community. The network is open to anyone who is interested. If you would like to participate in PAGES 2k or receive updates, please join our mailing list or speak to a coordinating committee member.

WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

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.

A New View of Dynamic River Networks

NASA Astrophysics Data System (ADS)

Perron, J. T.; Willett, S.; McCoy, S. W.

2014-12-01

River networks are the main conduits that transport water, sediment, and nutrients from continental interiors to the oceans. They also shape topography as they erode through bedrock. These hierarchical networks are dynamic: there are numerous examples of apparent changes in the topology of river networks through geologic time. But these examples are geographically scattered, the evidence can be ambiguous, and the mechanisms that drive changes in river networks are poorly understood. This makes it difficult to assess how pervasive river network reorganization is, how it operates, and how the interlocking river basins that compose a given landscape are changing through time. Recent progress has improved the situation. We describe three developments that have dramatically advanced our understanding of dynamic river networks. First, new topographic, geophysical and geochronological measurement techniques are revealing the rate and extent of river network adjustment. Second, laboratory experiments and computational models are clarifying how river networks respond to tectonic and climatic perturbations at scales ranging from local to continental. Third, spatial analysis of genetic data is exposing links between landscape evolution, biological evolution, and the development of biodiversity. We highlight key problems that remain unsolved, and suggest ways to build on recent advances that will bring dynamic river networks into even sharper focus.

Development of a robust analytical framework for assessing landbird trends, dynamics and relationships with environmental covariates in the North Coast and Cascades Network

USGS Publications Warehouse

Ray, Chris; Saracco, James; Jenkins, Kurt J.; Huff, Mark; Happe, Patricia J.; Ransom, Jason I.

2017-01-01

During 2015-2016, we completed development of a new analytical framework for landbird population monitoring data from the National Park Service (NPS) North Coast and Cascades Inventory and Monitoring Network (NCCN). This new tool for analysis combines several recent advances in modeling population status and trends using point-count data and is designed to supersede the approach previously slated for analysis of trends in the NCCN and other networks, including the Sierra Nevada Network (SIEN). Advances supported by the new model-based approach include 1) the use of combined data on distance and time of detection to estimate detection probability without assuming perfect detection at zero distance, 2) seamless accommodation of variation in sampling effort and missing data, and 3) straightforward estimation of the effects of downscaled climate and other local habitat characteristics on spatial and temporal trends in landbird populations. No changes in the current field protocol are necessary to facilitate the new analyses. We applied several versions of the new model to data from each of 39 species recorded in the three mountain parks of the NCCN, estimating trends and climate relationships for each species during 2005-2014. Our methods and results are also reported in a manuscript in revision for the journal Ecosphere (hereafter, Ray et al.). Here, we summarize the methods and results outlined in depth by Ray et al., discuss benefits of the new analytical framework, and provide recommendations for its application to synthetic analyses of long-term data from the NCCN and SIEN. All code necessary for implementing the new analyses is provided within the Appendices to this report, in the form of fully annotated scripts written in the open-access programming languages R and JAGS.

"It Takes a Network": Building National Capacity for Climate Change Interpretation

NASA Astrophysics Data System (ADS)

Spitzer, W.

2014-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. More than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the U.S. population. These visitors expect reliable information about environmental issues and solutions. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Beyond providing in-depth training, we have found that our "alumni network" is assuming an increasingly important role in achieving our goals: 1. Ongoing learning - Training must be ongoing given continuous advances in climate and social science research. 2. Implementation support - Social support is critical as interpreters move from learning to practice, given complex and potentially contentious subject matter. 3. Leadership development - We rely on a national cadre of interpretive leaders to conduct workshops, facilitate study circle trainings, and support alumni. 4. Coalition building - A peer network helps to build and maintain connections with colleagues, and supports further dissemination through the informal science community. We are experimenting with a variety of online and face to face strategies to support the growing alumni network. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy.

Downscaling large-scale circulation to local winter climate using neural network techniques

NASA Astrophysics Data System (ADS)

Cavazos Perez, Maria Tereza

1998-12-01

The severe impacts of climate variability on society reveal the increasing need for improving regional-scale climate diagnosis. A new downscaling approach for climate diagnosis is developed here. It is based on neural network techniques that derive transfer functions from the large-scale atmospheric controls to the local winter climate in northeastern Mexico and southeastern Texas during the 1985-93 period. A first neural network (NN) model employs time-lagged component scores from a rotated principal component analysis of SLP, 500-hPa heights, and 1000-500 hPa thickness as predictors of daily precipitation. The model is able to reproduce the phase and, to some decree, the amplitude of large rainfall events, reflecting the influence of the large-scale circulation. Large errors are found over the Sierra Madre, over the Gulf of Mexico, and during El Nino events, suggesting an increase in the importance of meso-scale rainfall processes. However, errors are also due to the lack of randomization of the input data and the absence of local atmospheric predictors such as moisture. Thus, a second NN model uses time-lagged specific humidity at the Earth's surface and at the 700 hPa level, SLP tendency, and 700-500 hPa thickness as input to a self-organizing map (SOM) that pre-classifies the atmospheric fields into different patterns. The results from the SOM classification document that negative (positive) anomalies of winter precipitation over the region are associated with: (1) weaker (stronger) Aleutian low; (2) stronger (weaker) North Pacific high; (3) negative (positive) phase of the Pacific North American pattern; and (4) La Nina (El Nino) events. The SOM atmospheric patterns are then used as input to a feed-forward NN that captures over 60% of the daily rainfall variance and 94% of the daily minimum temperature variance over the region. This demonstrates the ability of artificial neural network models to simulate realistic relationships on daily time scales. The results of this research also reveal that the SOM pre-classification of days with similar atmospheric conditions succeeded in emphasizing the differences of the atmospheric variance conducive to extreme events. This resulted in a downscaling NN model that is highly sensitive to local-scale weather anomalies associated with El Nino and extreme cold events.

Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach

NASA Astrophysics Data System (ADS)

Archetti, R.; Bolognesi, A.; Casadio, A.; Maglionico, M.

2011-04-01

The operating conditions of urban drainage networks during storm events certainly depend on the hydraulic conveying capacity of conduits but also on downstream boundary conditions. This is particularly true in costal areas where the level of the receiving water body is directly or indirectly affected by tidal or wave effects. In such cases, not just different rainfall conditions (varying intensity and duration), but also different sea-levels and their effects on the network operation should be considered. This paper aims to study the behaviour of a seaside town storm sewer network, estimating the threshold condition for flooding and proposing a simplified method to assess the urban flooding severity as a function of either climate variables. The case study is a portion of the drainage system of Rimini (Italy), implemented and numerically modelled by means of InfoWorks CS code. The hydraulic simulation of the sewerage system has therefore allowed to identify the percentage of nodes of the drainage system where flooding is expected to occur. Combining these percentages with both climate variables values has lead to the definition charts representing the combined degree of risk "sea-rainfall" for the drainage system under investigation. A final comparison between such charts and the results obtained from a one-year sea-rainfall time series has confirmed the reliability of the analysis.

Development of flood probability charts for urban drainage network in coastal areas through a simplified joint assessment approach

NASA Astrophysics Data System (ADS)

Archetti, R.; Bolognesi, A.; Casadio, A.; Maglionico, M.

2011-10-01

The operating conditions of urban drainage networks during storm events depend on the hydraulic conveying capacity of conduits and also on downstream boundary conditions. This is particularly true in coastal areas where the level of the receiving water body is directly or indirectly affected by tidal or wave effects. In such cases, not just different rainfall conditions (varying intensity and duration), but also different sea-levels and their effects on the network operation should be considered. This paper aims to study the behaviour of a seaside town storm sewer network, estimating the threshold condition for flooding and proposing a simplified method to assess the urban flooding severity as a function of climate variables. The case study is a portion of the drainage system of Rimini (Italy), implemented and numerically modelled by means of InfoWorks CS code. The hydraulic simulation of the sewerage system identified the percentage of nodes of the drainage system where flooding is expected to occur. Combining these percentages with both climate variables' values has lead to the definition of charts representing the combined degree of risk "rainfall-sea level" for the drainage system under investigation. A final comparison between such charts and the results obtained from a one-year rainfall-sea level time series has demonstrated the reliability of the analysis.

Urban Water Innovation Network (UWIN): Transitioning Toward Sustainbale Urban Water Systems

NASA Astrophysics Data System (ADS)

Arabi, M.

2015-12-01

City water systems are at risk of disruption from global social and environmental hazards, which could have deleterious effects on human health, property, and loss of critical infrastructure. The Urban Water Innovation Network (UWIN), a consortium of 14 academic institutions and other key partners across the U.S., is working to address challenges that threaten urban water systems across the nation. UWIN's mission is to create technological, institutional and management solutions to help communities increase the resilience of their water systems and enhance their preparedness for responding to water crisis. The network seeks solutions that achieve widespread adoption consistent with inclusive, equitable and sustainable urban development. The integrative and adaptive analysis framework of UWIN is presented. The framework identifies a toolbox of sustainable solutions by simultaneously minimizing pressures, enhancing resilience to extreme events, and maximizing cobenefits. The benefits of sustainable urban water solutions for linked urban ecosystems, economies, and arrangements for environmental justice and social equity, will be discussed. The network encompasses six U.S. regions with varying ecohydrologic and climatic regimes ranging from the coastal moist mid-latitude climates of the Mid-Atlantic to the subtropical semi-arid deserts of the Southwest. These regions also represent a wide spectrum of demographic, cultural, and policy settings. The opportunities for cross-site assessments that facilitate the exploration of locally appropriate solutions across regions undergoing various development trajectories will be discussed.

Fragility of estimated spatial temperature patterns in climate field reconstructions of the Common Era

NASA Astrophysics Data System (ADS)

Wang, J.; Emile-Geay, J.; Vaccaro, A.; Guillot, D.; Rajaratnam, B.

2013-12-01

Climate field reconstructions (CFRs) of the Common Era can provide insight into dynamical causes of low-frequency climate variability. For instance, the Mann et al. [2009] study found that the reconstructed sea-surface temperature difference between the Medieval Climate Anomaly and the Little Ice Age (hereinafter MCA - LIA) is marked by a La-Niña like pattern over the tropical Pacific, and proposed dynamical explanations for this observation. In this talk, we assess the robustness of such spatial patterns. First we examine the impact of the CFR methodology. Starting with the network of Mann et al. [2008] (hereinafter M08), we perform temperature reconstruction using four different CFR techniques: RegEM-TTLS [Schneider, 2001], the Mann et al. [2009] implementation of RegEM-TTLS (hereinafter M09), Canonical Correlation Analysis [Smerdon et al., 2010, CCA] and GraphEM [Guillot et al., in revision]. We find that results are greatly method-dependent even with identical inputs. While the M09 reconstruction displays a La Niña-like pattern over the tropical Pacific for MCA - LIA, CCA gives a neutral pattern, RegEM-TTLS and GraphEM both display El Niño-like pattern but show different amplitudes. Next we assess a given CFR technique's sensitivity to the selection of inputs. Proxies are selected based on the statistical significance of their correlations with HadCRUT3v annual temperature. A multiple hypothesis test [Ventura et al., 2004] is conducted to preclude spurious correlations. This choice has a large impact on resulting CFRs. In particular, whether the correlation is calculated between local or regional temperature-proxy pairs determines the number of significant records included in the proxy network. This in turn greatly affects the reconstructed spatial patterns and the Northern Hemispheric mean temperature time series with all CFR methods investigated. In order to further analyze CFRs' sensitivities to the abovementioned procedural choices, we assemble an updated multi-proxy network and produce a new 2000-year-long global temperature reconstruction. The network expands upon the existing M08 network by screening tree-ring proxies for the 'divergence problem' [D'Arrigo et al., 2008] and adds 58 non tree-ring proxies, of which 28 are located in the tropics and 11 are available within at least the past 1500 years. Overall, considerable differences are still evident among reconstructions using different CFR methods. Yet such differences are smaller using the updated proxy network compared with using the M08 network, consistent with pseudoproxy studies [Wang et al, 2013]. Our results collectively highlight the fragility of reconstructed patterns in the current state of proxy networks and CFR methods. We conclude that dynamical interpretations of such patterns are premature until these technical aspects are resolved. Reference: Wang, J., Emile-Geay, J., Guillot, D., Smerdon, J. E., and Rajaratnam, B.: Evaluating climate field reconstruction techniques using improved emulations of real-world conditions, Clim. Past Discuss., 9, 3015-3060, doi:10.5194/cpd-9-3015-2013, 2013.

ACMECS Bioenergy Network: Implementing a transnational science-based policy network on bioenergy

NASA Astrophysics Data System (ADS)

Bruckman, Viktor J.; Haruthaithanasan, Maliwan; Kraxner, Florian; Brenner, Anna

2017-04-01

Despite the currently low prices for fossil energy resulting from a number of geopolitical reasons, intergovernmental efforts are being made towards a transition to a sustainable bio-economy. The main reasons for this include climate change mitigation, decreasing dependencies fossil fuel imports and hence external market fluctuations, diversification of energy generation and feedstock production for industrial processes. Since 2012, the ACMECS bioenergy network initiative leads negotiations and organizes workshops to set up a regional bioenergy network in Indochina, with the aim to promote biomass and -energy markets, technology transfer, rural development and income generation. Policy development is guided by the International Union of Forest Research Institutions (IUFRO) Task Force "Sustainable Forest Bioenergy Network". In this paper, we highlight the achievements so far and present results of a multi-stakeholder questionnaire in combination with a quantitative analysis of the National Bioenergy Development Plans (NBDP's). We found that traditional fuelwood is still the most important resource for generating thermal energy in the region, especially in rural settings, and it will remain an important resource even in 25 years. However, less fuelwood will be sourced from natural forests as compared to today. NBDP's have a focus on market development, technology transfer and funding possibilities of a regional bioenergy strategy, while the responses of the questionnaire favored more altruistic goals, i.e. sustainable resource management, environmental protection and climate change mitigation, generation of rural income and community involvement etc. This is surprising, since a sub-population of the (anonymous) questionnaire respondents was actually responsible drafting the NBDP's. We therefore suggest the following measures to ensure regulations that represent the original aims of the network (climate change mitigation, poverty alleviation, sustainable resource use, diversification of energy generation): i) More communication between policy makers and the other stakeholders, ii) Invitation of stakeholders representing rural communities to participate in this process, iii) development of sustainability criteria, vi) feedback cycles ensuring more intensive discussion of policy drafts, v) association of an international board of experts to provide scientifically sound feedback and input and vi) establishment of a local demonstration region, containing various steps in the biomass/bioenergy supply chain including transboundary collaboration in the ACMECS region.

Plasticity in Dendroclimatic Response across the Distribution Range of Aleppo Pine (Pinus halepensis)

PubMed Central

de Luis, Martin; Čufar, Katarina; Di Filippo, Alfredo; Novak, Klemen; Papadopoulos, Andreas; Piovesan, Gianluca; Rathgeber, Cyrille B. K.; Raventós, José; Saz, Miguel Angel; Smith, Kevin T.

2013-01-01

We investigated the variability of the climate-growth relationship of Aleppo pine across its distribution range in the Mediterranean Basin. We constructed a network of tree-ring index chronologies from 63 sites across the region. Correlation function analysis identified the relationships of tree-ring index to climate factors for each site. We also estimated the dominant climatic gradients of the region using principal component analysis of monthly, seasonal, and annual mean temperature and total precipitation from 1,068 climatic gridpoints. Variation in ring width index was primarily related to precipitation and secondarily to temperature. However, we found that the dendroclimatic relationship depended on the position of the site along the climatic gradient. In the southern part of the distribution range, where temperature was generally higher and precipitation lower than the regional average, reduced growth was also associated with warm and dry conditions. In the northern part, where the average temperature was lower and the precipitation more abundant than the regional average, reduced growth was associated with cool conditions. Thus, our study highlights the substantial plasticity of Aleppo pine in response to different climatic conditions. These results do not resolve the source of response variability as being due to either genetic variation in provenance, to phenotypic plasticity, or a combination of factors. However, as current growth responses to inter-annual climate variability vary spatially across existing climate gradients, future climate-growth relationships will also likely be determined by differential adaptation and/or acclimation responses to spatial climatic variation. The contribution of local adaptation and/or phenotypic plasticity across populations to the persistence of species under global warming could be decisive for prediction of climate change impacts across populations. In this sense, a more complex forest dynamics modeling approach that includes the contribution of genetic variation and phenotypic plasticity can improve the reliability of the ecological inferences derived from the climate-growth relationships. PMID:24391786

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity

USGS Publications Warehouse

Isaak, Daniel J.; Young, Michael K; Luce, Charles H; Hostetler, Steven W.; Wengerd, Seth J.; Peterson, Erin E.; Ver Hoef, Jay; Groce, Matthew C.; Horan, Dona L.; Nagel, David E.

2016-01-01

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.

Federal climate change programs in the water-limited Southwest: intersection of mission, stakeholders and geography to build successful collaboration

NASA Astrophysics Data System (ADS)

Elias, E.; Steele, C. M.; Rango, A.; Reyes, J. J.; Langston, M. A.; Johnson, K.

2016-12-01

As one of the newest federal programs to emerge in response to climate change, the U.S. Department of Agriculture (USDA) Climate Hubs were established to assist farmers, ranchers and forest landowners in their adaptation and mitigation efforts under a changing climate. The Hubs' mission is to deliver science-based information and tools to agricultural and natural resource land managers, to enable climate-informed decision-making. By facilitating and transferring tools and knowledge, the Hubs also provide value to cooperative extension, land grant institutions, and USDA itself, especially in leveraging existing resource capacity. Various federal agencies (NOAA, USGS, USFWS) have also developed climate change coordination networks: RISAs, CSCs, and LCCs. These regionally-based federal networks can best operate in collaboration with one another. At their programmatic level, however, there are fundamental discrepancies in mission, stakeholder definition and geographic region. In this presentation, we seek to compare and contrast these divergent characteristics by identifying `hot spots' and `hot moments' where definitions, programs, or priorities may intersect due to place-based or event-based issues. The Southwest (SW) region of the United States, which presently operates under warm and dry conditions, is projected to become warmer and drier in the future. On-going drought conditions have presented an opportunity to maintain and build professional networks among these federal climate change coordination networks, as well as within USDA, to better understand impacts and respond to stakeholder needs. Projects in the Rio Grande River Valley and with Tribal nations highlight successful collaboration based on geography and common stakeholders, respectively. Aridity and water scarcity characterize the SW region and provide an overarching theme to better support adaptation and mitigation, as well as create opportunities for collaborative success.

Designing optimized multi-species monitoring networks to detect range shifts driven by climate change: a case study with bats in the North of Portugal.

PubMed

Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo

2014-01-01

Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity

PubMed Central

Isaak, Daniel J.; Young, Michael K.; Luce, Charles H.; Hostetler, Steven W.; Wenger, Seth J.; Peterson, Erin E.; Ver Hoef, Jay M.; Groce, Matthew C.; Horan, Dona L.; Nagel, David E.

2016-01-01

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century. PMID:27044091

Moving toward Collective Impact in Climate Change Literacy: The Climate Literacy and Energy Awareness Network (CLEAN)

ERIC Educational Resources Information Center

Ledley, Tamara Shapiro; Gold, Anne U.; Niepold, Frank; McCaffrey, Mark

2014-01-01

In recent years, various climate change education efforts have been launched, including federally (National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration, National Science Foundation, etc.) and privately funded projects. In addition, climate literacy and energy literacy frameworks have been developed and…

Regional climate services: A regional partnership between NOAA and USDA

USDA-ARS?s Scientific Manuscript database

Climate services in the Midwest and Northern Plains regions have been enhanced by a recent addition of the USDA Climate Hubs to NOAA’s existing network of partners. This new partnership stems from the intrinsic variability of intra and inter-annual climatic conditions, which makes decision-making fo...

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

A climate stress-test of the financial system

NASA Astrophysics Data System (ADS)

Battiston, Stefano; Mandel, Antoine; Monasterolo, Irene; Schütze, Franziska; Visentin, Gabriele

2017-03-01

The urgency of estimating the impact of climate risks on the financial system is increasingly recognized among scholars and practitioners. By adopting a network approach to financial dependencies, we look at how climate policy risk might propagate through the financial system. We develop a network-based climate stress-test methodology and apply it to large Euro Area banks in a `green' and a `brown' scenario. We find that direct and indirect exposures to climate-policy-relevant sectors represent a large portion of investors' equity portfolios, especially for investment and pension funds. Additionally, the portion of banks' loan portfolios exposed to these sectors is comparable to banks' capital. Our results suggest that climate policy timing matters. An early and stable policy framework would allow for smooth asset value adjustments and lead to potential net winners and losers. In contrast, a late and abrupt policy framework could have adverse systemic consequences.

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

A Reusable Framework for Regional Climate Model Evaluation

NASA Astrophysics Data System (ADS)

Hart, A. F.; Goodale, C. E.; Mattmann, C. A.; Lean, P.; Kim, J.; Zimdars, P.; Waliser, D. E.; Crichton, D. J.

2011-12-01

Climate observations are currently obtained through a diverse network of sensors and platforms that include space-based observatories, airborne and seaborne platforms, and distributed, networked, ground-based instruments. These global observational measurements are critical inputs to the efforts of the climate modeling community and can provide a corpus of data for use in analysis and validation of climate models. The Regional Climate Model Evaluation System (RCMES) is an effort currently being undertaken to address the challenges of integrating this vast array of observational climate data into a coherent resource suitable for performing model analysis at the regional level. Developed through a collaboration between the NASA Jet Propulsion Laboratory (JPL) and the UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), the RCMES uses existing open source technologies (MySQL, Apache Hadoop, and Apache OODT), to construct a scalable, parametric, geospatial data store that incorporates decades of observational data from a variety of NASA Earth science missions, as well as other sources into a consistently annotated, highly available scientific resource. By eliminating arbitrary partitions in the data (individual file boundaries, differing file formats, etc), and instead treating each individual observational measurement as a unique, geospatially referenced data point, the RCMES is capable of transforming large, heterogeneous collections of disparate observational data into a unified resource suitable for comparison to climate model output. This facility is further enhanced by the availability of a model evaluation toolkit which consists of a set of Python libraries, a RESTful web service layer, and a browser-based graphical user interface that allows for orchestration of model-to-data comparisons by composing them visually through web forms. This combination of tools and interfaces dramatically simplifies the process of interacting with and utilizing large volumes of observational data for model evaluation research. We feel that the RCMES is particularly appealing in that it represents a principled, reusable architectural approach rather than a one-off technological implementation. In fact, early RCMES prototypes have already utilized a variety of implementation technologies in an effort to address different performance and scalability concerns. This has been greatly facilitated by the fact that, at the architectural level, the RCMES is fundamentally domain agnostic. Strictly separating the data model from the implementation has enabled us to create a reusable architecture that we believe can be modified and configured to suit the demands of researchers in other domains.

Modeling economic and carbon consequences of a shift to wood-based energy in a rural 'cluster'; a network analysis in southeast Alaska

Treesearch

David Saah; Trista Patterson; Thomas Buchholz; David Ganz; David Albert; Keith Rush

2014-01-01

Integrated ecological and economic solutions are increasingly sought after by communities to provide basic energy needs such as home heating, transport, and electricity, while reducing drivers of and vulnerability to climate change. Small rural communities may require a coordinated approach to overcome the limitations of economies of scale. Low-carbon development...

Building Climate Service Capacities in Eastern Africa with CHIRP and GeoCLIM

NASA Astrophysics Data System (ADS)

Pedreros, D. H.; Magadzire, T.; Funk, C. C.; Verdin, J. P.; Peterson, P.; Landsfeld, M.; Husak, G. J.

2013-12-01

In developing countries there is a great need for capacity building within national and regional climate agencies to develop and analyze historical and real time gridded rainfall datasets. These datasets are of key importance for monitoring climate and agricultural food production at decadal and seasonal time scales, and for informing local decision makers. The Famine Early Warning Systems Network (FEWS NET), working together with the U.S. Geological Survey (USGS) and the Climate Hazards Group (CHG) of the University of California Santa Barbara, has developed an integrated set of data products and tools to support the development of African climate services. The core data product is the Climate Hazards Group Infrared Precipitation (CHIRP) dataset. The CHIRP is a new rainfall dataset resulting from the blending of satellite estimated precipitation with high resolution precipitation climatology. The CHIRP depicts rainfall on five day totals at 5km spatial resolution from 1981 to present. The CHG is developing and deploying a standalone tool - the GeoCLIM - which will allow national and regional meteorological agencies to blend the CHIRP with station observations, run simple crop water balance models, and conduct climatological, trend, and time series analysis. Blending satellite estimates and gauge data helps overcome limited in situ observing networks. Furthermore, the GeoCLIM combines rainfall, soil, and evapotranspiration data with crop hydrological requirements to calculate agricultural water balance, presented as the Water Requirement Satisfaction Index (WRSI). The WRSI is a measurement of the degree in which a crop's hydrological requirements have been satisfied by rainfall. We present the results of a training session for personnel of the East African Intergovernmental Authority on Development Climate Prediction and Applications Center. The two week training program included the use of the GeoCLIM to improve CHIRP using station data, and to calculate and analyze trends in rainfall, WRSI, and drought frequency in the region.

Integrating Climate Change Scenarios and Co-developed Policy Scenarios to Inform Coastal Adaptation: Results from a Tillamook County, Oregon Knowledge to Action Network

NASA Astrophysics Data System (ADS)

Lipiec, E.; Ruggiero, P.; Serafin, K.; Bolte, J.; Mills, A.; Corcoran, P.; Stevenson, J.; Lach, D.

2014-12-01

Local decision-makers often lack both the information and tools to reduce their community's overall vulnerability to current and future climate change impacts. Managers are restricted in their actions by the scale of the problem, inherent scientific uncertainty, limits of information exchange, and the global nature of available data, rendering place-based strategies difficult to generate. Several U.S. Pacific Northwest coastal communities are already experiencing chronic erosion and flooding, hazards only to be exacerbated by sea level rise and changing patterns of storminess associated with climate change. To address these issues, a knowledge to action network (KTAN) consisting of local Tillamook County stakeholders and Oregon State University researchers, was formed to project future flooding and erosion impacts and determine possible adaptation policies to reduce vulnerability. Via an iterative scenario planning process, the KTAN has developed four distinct adaptation policy scenarios, including 'Status Quo', 'Hold The Line', 'ReAlign', and 'Laissez-Faire'. These policy scenarios are being integrated with a range of climate change scenarios within the modeling framework Envision, a multi-agent GIS-based tool, which allows for the combination of physical processes data, probabilistic climate change information, coastal flood and erosion models, and stakeholder driven adaptation strategies into distinct plausible future scenarios. Because exact physical and social responses to climate change are impossible to ascertain, information about the differences between possible future scenarios can provide valuable information to decision-makers and the community at large. For example, the fewest projected coastal flood and erosion impacts to buildings occur under the 'ReAlign' policy scenario (i.e., adaptation strategies that move dwellings away from the coast) under both low and high climate change scenarios, especially in comparison to the 'Status Quo' or 'Hold The Line' scenarios. Statistical analysis of the scenario-based variations in impacts to private and public resources can help guide future adaptation policy implementation and support Oregon's coastal communities for years to come.

Climate change, coral reef ecosystems, and management options for marine protected areas.

PubMed

Keller, Brian D; Gleason, Daniel F; McLeod, Elizabeth; Woodley, Christa M; Airamé, Satie; Causey, Billy D; Friedlander, Alan M; Grober-Dunsmore, Rikki; Johnson, Johanna E; Miller, Steven L; Steneck, Robert S

2009-12-01

Marine protected areas (MPAs) provide place-based management of marine ecosystems through various degrees and types of protective actions. Habitats such as coral reefs are especially susceptible to degradation resulting from climate change, as evidenced by mass bleaching events over the past two decades. Marine ecosystems are being altered by direct effects of climate change including ocean warming, ocean acidification, rising sea level, changing circulation patterns, increasing severity of storms, and changing freshwater influxes. As impacts of climate change strengthen they may exacerbate effects of existing stressors and require new or modified management approaches; MPA networks are generally accepted as an improvement over individual MPAs to address multiple threats to the marine environment. While MPA networks are considered a potentially effective management approach for conserving marine biodiversity, they should be established in conjunction with other management strategies, such as fisheries regulations and reductions of nutrients and other forms of land-based pollution. Information about interactions between climate change and more "traditional" stressors is limited. MPA managers are faced with high levels of uncertainty about likely outcomes of management actions because climate change impacts have strong interactions with existing stressors, such as land-based sources of pollution, overfishing and destructive fishing practices, invasive species, and diseases. Management options include ameliorating existing stressors, protecting potentially resilient areas, developing networks of MPAs, and integrating climate change into MPA planning, management, and evaluation.

Climate change and vulnerability of bull trout (Salvelinus confluentus) in a fire-prone landscape.

USGS Publications Warehouse

Falke, Jeffrey A.; Flitcroft, Rebecca L; Dunham, Jason B.; McNyset, Kristina M.; Hessburg, Paul F.; Reeves, Gordon H.

2015-01-01

Linked atmospheric and wildfire changes will complicate future management of native coldwater fishes in fire-prone landscapes, and new approaches to management that incorporate uncertainty are needed to address this challenge. We used a Bayesian network (BN) approach to evaluate population vulnerability of bull trout (Salvelinus confluentus) in the Wenatchee River basin, Washington, USA, under current and future climate and fire scenarios. The BN was based on modeled estimates of wildfire, water temperature, and physical habitat prior to, and following, simulated fires throughout the basin. We found that bull trout population vulnerability depended on the extent to which climate effects can be at least partially offset by managing factors such as habitat connectivity and fire size. Moreover, our analysis showed that local management can significantly reduce the vulnerability of bull trout to climate change given appropriate management actions. Tools such as our BN that explicitly integrate the linked nature of climate and wildfire, and incorporate uncertainty in both input data and vulnerability estimates, will be vital in effective future management to conserve native coldwater fishes.

Data in support of energy performance of double-glazed windows.

PubMed

Shakouri, Mahmoud; Banihashemi, Saeed

2016-06-01

This paper provides the data used in a research project to propose a new simplified windows rating system based on saved annual energy ("Developing an empirical predictive energy-rating model for windows by using Artificial Neural Network" (Shakouri Hassanabadi and Banihashemi Namini, 2012) [1], "Climatic, parametric and non-parametric analysis of energy performance of double-glazed windows in different climates" (Banihashemi et al., 2015) [2]). A full factorial simulation study was conducted to evaluate the performance of 26 different types of windows in a four-story residential building. In order to generalize the results, the selected windows were tested in four climates of cold, tropical, temperate, and hot and arid; and four different main orientations of North, West, South and East. The accompanied datasets include the annual saved cooling and heating energy in different climates and orientations by using the selected windows. Moreover, a complete dataset is provided that includes the specifications of 26 windows, climate data, month, and orientation of the window. This dataset can be used to make predictive models for energy efficiency assessment of double glazed windows.

Inversion Estimate of California Methane Emissions Using a Bayesian Inverse Model with Multi-Tower Greenhouse Gas Monitoring Network and Aircraft Measurements

NASA Astrophysics Data System (ADS)

Cui, Y.; Falk, M.; Chen, Y.; Herner, J.; Croes, B. E.; Vijayan, A.

2017-12-01

Methane (CH4) is an important short-lived climate pollutant (SLCP), and the second most important greenhouse gas (GHG) in California which accounts for 9% of the statewide GHG emissions inventory. Over the years, California has enacted several ambitious climate change mitigation goals, including the California Global Warming Solutions Act of 2006 which requires ARB to reduce statewide GHG emissions to 1990 emission level by 2020, as well as Assembly Bill 1383 which requires implementation of a climate mitigation program to reduce statewide methane emissions by 40% below the 2013 levels. In order to meet these requirements, ARB has proposed a comprehensive SLCP Strategy with goals to reduce oil and gas related emissions and capture methane emissions from dairy operations and organic waste. Achieving these goals will require accurate understanding of the sources of CH4 emissions. Since direct monitoring of CH4 emission sources in large spatial and temporal scales is challenging and resource intensive, we developed a complex inverse technique combined with atmospheric three-dimensional (3D) transport model and atmospheric observations of CH4 concentrations from a regional tower network and aircraft measurements, to gain insights into emission sources in California. In this study, develop a comprehensive inversion estimate using available aircraft measurements from CalNex airborne campaigns (May-June 2010) and three years of hourly continuous measurements from the ARB Statewide GHG Monitoring Network (2014-2016). The inversion analysis is conducted using two independent 3D Lagrangian models (WRF-STILT and WRF-FLEXPART), with a variety of bottom-up prior inputs from national and regional inventories, as well as two different probability density functions (Gaussian and Lognormal). Altogether, our analysis provides a detailed picture of the spatially resolved CH4 emission sources and their temporal variation over a multi-year period.

U.S. Department of the Interior Climate Science Centers and U.S. Geological Survey National Climate Change and Wildlife Science Center—Annual report for 2015

USGS Publications Warehouse

Varela Minder, Elda; Padgett, Holly A.

2016-04-07

2015 was another great year for the Department of the Interior (DOI) Climate Science Centers (CSCs) and U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC) network. The DOI CSCs and USGS NCCWSC continued their mission of providing the science, data, and tools that are needed for on-the-ground decision making by natural and cultural resource managers to address the effects of climate change on fish, wildlife, ecosystems, and communities. Our many accomplishments in 2015 included initiating a national effort to understand the influence of drought on wildlife and ecosystems; providing numerous opportunities for students and early career researchers to expand their networks and learn more about climate change effects; and working with tribes and indigenous communities to expand their knowledge of and preparation for the impacts of climate change on important resources and traditional ways of living. Here we illustrate some of these 2015 activities from across the CSCs and NCCWSC.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information; with a section on theory and application of generalized least squares

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1987-01-01

This report documents the results of an analysis of the surface-water data network in Kansas for its effectiveness in providing regional streamflow information. The network was analyzed using generalized least squares regression. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-, low-, and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow-gaging-station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations, and (or) adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and for discontinued stations for which unregulated flow characteristics, as well as physical and climatic characteristics, were available. The State was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for the three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean-square error for each cost level could be obtained by adding new stations and discontinuing some current network stations. Large reductions in sampling mean-square error for low-flow information could be achieved in all three network areas, the reduction in western Kansas being the most dramatic. The addition of new stations would be most beneficial for mean-flow information in western Kansas. The reduction of sampling mean-square error for high-flow information would benefit most from the addition of new stations in western Kansas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas.

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

NASA Astrophysics Data System (ADS)

Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron

2016-02-01

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

Non—Linear Flood Assessment with Neural Network

NASA Astrophysics Data System (ADS)

Murariu, Gabriel; Puscasu, Gheorghe; Gogoncea, Vlad

2010-01-01

In our days, theoretical investigations are used in obtaining the mathematical model for the studied systems or processes. In general, the dynamics of the system are deeply nonlinear, complex or unknown. Generally speaking, such complex structure is a set of interconnected components. The common approach is therefore to start from measurements of the behavior of the system and the external influences (inputs) and try to determine a mathematical relation between them without going into the details of what is actually happening inside the system. Such strategy had known a great success during the time and it was applied for a large class of multifaceted processes. Accepting this approach, there could be investigated the climatic phenomena. In this paper is presented, in a comparative way, a non-linear water flood assessment made in a very sensitive area of the Lower Danube zone where, in the past years, a series of climatic problems have been happening. In these conditions, climatic risk factor management is a necessity. In a regular way, there could be considered and designed nonlinear models for the climatic factors' analysis by using a huge historical evidence data archive. In a previous paper we reached a notable intermediary result basing on a mathematical model constructed on internal recurrent neural network structure. Such approach had been presented considering the internal state estimation when no measurements coming from the sensors are available for system states. A modified backpropagation algorithm had been introduced in order to train the internal recurrent neural networks for nonlinear system identification. In this paper is exposed a comparative study between a numerical advances based on fluid dynamics' equations and our previous approach, based on internal recurrent neural networks (IRNN). The numerical approaching was made in order to succeed in building a physics model of a water flow evaluation and further, to achieve including the rainfall contributions. This condition is necessary for prediction and it is the first step toward a DSS—Decision Support System in the area. The relationship between the simulated results and the registered data allows considering our particular method to be useful for considered water flood assessment.

Unraveling spurious properties of interaction networks with tailored random networks.

PubMed

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Unraveling Spurious Properties of Interaction Networks with Tailored Random Networks

PubMed Central

Bialonski, Stephan; Wendler, Martin; Lehnertz, Klaus

2011-01-01

We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis. PMID:21850239

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

Increasing aridity threats to Himalayan alpine ecosystems? A millenial history of hydroclimate from the Tibetan plateau derived from a δ18O tree-ring network

NASA Astrophysics Data System (ADS)

Griessinger, J.

2015-12-01

The Tibetan plateau (TP) plays an important role as an elevated heat source responsible for the establishment of the Asias monsoonal systems. Besides the Indian Summer Monsoon (ISM), also the East Asian Summer Monsoon (EASM) is triggering the regional precipitation regimes during the vegetation period from May to September. Within recent decades, fundamental climate changes on the southeastern part of the TP were detected leading to substantial changes within the regional hydrological budget and affecting local ecosystems. By using a spatial network of multicentennial to 1.5 millenial year old tree-ring δ18O time-series from the southeastern part of the TP, the regional climate history as well as the late Holocene monsoonal variability will be presented. Since the main climatically sensitive periods like the Medieval Warm Period and the Little Ice Age are displayed in all chronologies, their typical hydroclimatological characteristics and impacts will be discussed especially in regard to the recent warming trend on the TP and the responsible climatic triggers. Arising from these results, regional impacts and differences of the proposed hydrological changes will be discussed. In addition, first results of a comparison between proxy-based (δ18O) and model-based (re-analysis datasets) trajectory calculations will be presented, trying to give insights in the origin and impact of air masses for the most striking last three decades on the southeastern part of the TP.

Putting Citizen-Collected Observations to Work -- The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS)

NASA Astrophysics Data System (ADS)

Doesken, N.

2015-12-01

When CoCoRaHS was born (1998), climate-relevant information was far from our minds. We were simply enlisting volunteers to help capture, display and communicate the nature of small scale variability within northern Colorado storms. Climate change was talked about then, but not with the sense of concern and urgency as today. Now, many years later, the simple back-yard precipitation measurements being taken by thousands of volunteers across much of North America are creating valuable and easily-accessible data and information serving many and varied purposes from federal and state climate monitoring to drought and extreme storm analysis and research. Many volunteers have been with the project now for a decade or longer and have contributed literally thousands of individual observations and reports. Long-time participants along with recent recruits of all ages are seeing first-hand how day by day observations of weather conditions combine - over time and space -- to define and describe key elements of our climate and its variations. The fact that the data from volunteers are frequently used and applied by scientists and decision makers is one of the key factors in retaining long-term volunteers. Examples will be presented of volunteer precipitation data being used both independently and in combination with data from federal monitoring systems. Challenges of maintaining a large volunteer network will be discussed along with some plans and opportunities for the future.

Complex Networks Dynamics Based on Events-Phase Synchronization and Intensity Correlation Applied to The Anomaly Patterns and Extremes in The Tropical African Climate System

NASA Astrophysics Data System (ADS)

Oluoch, K.; Marwan, N.; Trauth, M.; Loew, A.; Kurths, J.

2012-04-01

The African continent lie almost entirely within the tropics and as such its (tropical) climate systems are predominantly governed by the heterogeneous, spatial and temporal variability of the Hadley and Walker circulations. The variabilities in these meridional and zonal circulations lead to intensification or suppression of the intensities, durations and frequencies of the Inter-tropical Convergence Zone (ICTZ) migration, trade winds and subtropical high-pressure regions and the continental monsoons. The above features play a central role in determining the African rainfall spatial and temporal variability patterns. The current understanding of these climate features and their influence on the rainfall patterns is not sufficiently understood. Like many real-world systems, atmospheric-oceanic processes exhibit non-linear properties that can be better explored using non-linear (NL) methods of time-series analysis. Over the recent years, the complex network approach has evolved as a powerful new player in understanding spatio-temporal dynamics and evolution of complex systems. Together with NL techniques, it is continuing to find new applications in many areas of science and technology including climate research. We would like to use these two powerful methods to understand the spatial structure and dynamics of African rainfall anomaly patterns and extremes. The method of event synchronization (ES) developed by Quiroga et al., 2002 and first applied to climate networks by Malik et al., 2011 looks at correlations with a dynamic time lag and as such, it is a more intuitive way to correlate a complex and heterogeneous system like climate networks than a fixed time delay most commonly used. On the other hand, the short comings of ES is its lack of vigorous test statistics for the significance level of the correlations, and the fact that only the events' time indices are synchronized while all information about how the relative intensities propagate within network framework is lost. The new method we present is motivated by the ES and borrows ideas from signal processing where a signal is represented by its intensity and frequency. Even though the anomaly signals are not periodic, the idea of phase synchronization is not far fetched. It brings into one umbrella, the traditionally known linear Intensity correlation methods like Pearson correlation, spear-man's rank or non-linear ones like mutual information with the ES for non-linear temporal synchronization. The intensity correlation is only performed where there is a temporal synchronization. The former just measures how constant the intensity differences are. In other words, how monotonic are the two functions. The overall measure of correlation and synchronization is the product of the two coefficients. Complex networks constructed by this technique has all the advantages inherent in each of the techniques it borrows. But, it is more superior and able to uncover many known and unknown dynamical features in rainfall field or any variable of interest. The main aim of this work is to develop a method that can identify the footprints of coherent or incoherent structures within the ICTZ, the African and the Indian monsoons and the ENSO signal on the tropical African continent and their temporal evolution.

Investigation of land subsidence due to climate changes in surrounding areas of Urmia Lake (located in northwest of Iran) using wavelet coherence analysis of geodetic measurements and methodological data

NASA Astrophysics Data System (ADS)

Moghtased-Azar, K.; Mirzaei, A.; Nankali, H. R.; Tavakoli, F.

2012-04-01

Urmia Lake (salt lake in northwest of Iran) plays a valuable role in environment, wildlife and economy of Iran and the region, and now faces great challenges for survival. The Lake is in immediate and great danger and rapidly going to become salty desert. During the recent years and new heat wave, Iran, like many other countries are experiencing, is faced with relativity reduced rain fall. From a few years ago environment activists warned about potential dangers. Geodetic measurements, e.g., repeated leveling measurements of first order leveling network of Iran and continuous GPS measurements of Iranian Permanent GPS network of Iran (IPGN) showed that there is subsidence in surrounding areas of the lake. This paper investigates the relation between subsidence and climate changing in the area, using the wavelet coherence of the data of permanent GPS stations and daily methodological data. The results show that there is strong coherence between the subsidence phenomena induced by GPS data and climate warming from January 2009 up to end of August 2009. However, relative lake height variations computed from altimetry observations (TOPEX/POSEIDON (T/P), Jason-1 and Jason-2/OSTM) confirms maximum evaporation rates of the lake in this period.

Seeing is Believing? An Examination of Perceptions of Local Weather Conditions and Climate Change Among Residents in the U.S. Gulf Coast.

PubMed

Shao, Wanyun; Goidel, Kirby

2016-11-01

What role do objective weather conditions play in coastal residents' perceptions of local climate shifts and how do these perceptions affect attitudes toward climate change? While scholars have increasingly investigated the role of weather and climate conditions on climate-related attitudes and behaviors, they typically assume that residents accurately perceive shifts in local climate patterns. We directly test this assumption using the largest and most comprehensive survey of Gulf Coast residents conducted to date supplemented with monthly temperature data from the U.S. Historical Climatology Network and extreme weather events data from National Climatic Data Center. We find objective conditions have limited explanatory power in determining perceptions of local climate patterns. Only the 15- and 19-year hurricane trends and decadal summer temperature trend have some effects on perceptions of these weather conditions, while the decadal trend of total number of extreme weather events and 15- and 19-year winter temperature trends are correlated with belief in climate change. Partisan affiliation, in contrast, plays a powerful role affecting individual perceptions of changing patterns of air temperatures, flooding, droughts, and hurricanes, as well as belief in the existence of climate change and concern for future consequences. At least when it comes to changing local conditions, "seeing is not believing." Political orientations rather than local conditions drive perceptions of local weather conditions and these perceptions-rather than objectively measured weather conditions-influence climate-related attitudes. © 2016 Society for Risk Analysis.

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

USGS Publications Warehouse

Stanislawski, Larry V.; Survila, Kornelijus; Wendel, Jeffrey; Liu, Yan; Buttenfield, Barbara P.

2018-01-01

This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

Adaptations to Climate in Candidate Genes for Common Metabolic Disorders

PubMed Central

Hancock, Angela M; Witonsky, David B; Gordon, Adam S; Eshel, Gidon; Pritchard, Jonathan K; Coop, Graham; Di Rienzo, Anna

2008-01-01

Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders. PMID:18282109

Predicting lodgepole pine site index from climatic parameters in Alberta.

Treesearch

Robert A. Monserud; Shongming Huang; Yuqing Yang

2006-01-01

We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based...

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2014-04-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and Dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall, including well-known associations from prior climate knowledge, as well as promising discoveries that invite further research by the climate science community.

ENES the European Network for Earth System modelling and its infrastructure projects IS-ENES

NASA Astrophysics Data System (ADS)

Guglielmo, Francesca; Joussaume, Sylvie; Parinet, Marie

2016-04-01

The scientific community working on climate modelling is organized within the European Network for Earth System modelling (ENES). In the past decade, several European university departments, research centres, meteorological services, computer centres, and industrial partners engaged in the creation of ENES with the purpose of working together and cooperating towards the further development of the network, by signing a Memorandum of Understanding. As of 2015, the consortium counts 47 partners. The climate modelling community, and thus ENES, faces challenges which are both science-driven, i.e. analysing of the full complexity of the Earth System to improve our understanding and prediction of climate changes, and have multi-faceted societal implications, as a better representation of climate change on regional scales leads to improved understanding and prediction of impacts and to the development and provision of climate services. ENES, promoting and endorsing projects and initiatives, helps in developing and evaluating of state-of-the-art climate and Earth system models, facilitates model inter-comparison studies, encourages exchanges of software and model results, and fosters the use of high performance computing facilities dedicated to high-resolution multi-model experiments. ENES brings together public and private partners, integrates countries underrepresented in climate modelling studies, and reaches out to different user communities, thus enhancing European expertise and competitiveness. In this need of sophisticated models, world-class, high-performance computers, and state-of-the-art software solutions to make efficient use of models, data and hardware, a key role is played by the constitution and maintenance of a solid infrastructure, developing and providing services to the different user communities. ENES has investigated the infrastructural needs and has received funding from the EU FP7 program for the IS-ENES (InfraStructure for ENES) phase I and II projects. We present here the case study of an existing network of institutions brought together toward common goals by a non-binding agreement, ENES, and of its two IS-ENES projects. These latter will be discussed in their double role as a means to provide and/or maintain the actual infrastructure (hardware, software, skilled human resources, services) to achieve ENES scientific goals -fulfilling the aims set in a strategy document-, but also to inform and provide to the network a structured way of working and of interacting with the extended community. The genesis and evolution of the network and the interaction network/projects will also be analysed in terms of long-term sustainability.

Defining climate modeling user needs: which data are actually required to support impact analysis and adaptation policy development?

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.

Coupling climate conditions, sediment sources and sediment transport in an alpine basin

NASA Astrophysics Data System (ADS)

Rainato, Riccardo; Picco, Lorenzo; Cavalli, Marco; Mao, Luca; Neverman, Andrew J.; Tarolli, Paolo

2017-04-01

In a fluvial system, mountain basins control sediment export to the lowland rivers. Hence, the analysis of the erosion processes and sediment delivery patterns that act in mountain basins is important. Several studies have investigated the alterations triggered by recent climatic change on the hydrological regime, whilst only a few works have explored the consequences on the sediment dynamics. Here we combined and analyzed the quasi-unique dataset of climatic conditions, landscape response, and sediment export produced, since 1986 in the Rio Cordon basin (5 km2, Eastern Italian Alps) to examine the sediment delivery processes occurring in the last three decades. The temperature, precipitation, and fluvial sediment fluxes in the basin were analyzed using continuous measurement executed by a permanent monitoring station, while the landscape evolution was investigated by three sediment source inventories established in 1994, 2006, and 2016. Thus, the analysis focused on the trends exhibited during the periods 1986-1993, 1994-2006, and 2007-2015. In terms of climatic conditions, three distinct climate forcing stages can be observed in the periods analyzed: a relatively stable phase (1986-1993), a period characterized by temperature and rainfall fluctuations (1994-2006), and a more recent warmer and wetter phase (2007-2015). In the 1986-1993 period, the fluvial sediment fluxes reflected the stable trend exhibited by the climatic conditions. In the subsequent 1994-2006 period, the average temperature and precipitation were in line with that previously observed, although with higher interannual variability. Notwithstanding the climate forcing and the occurrence of high magnitude/low frequency floods that strongly influenced the source areas, between 1994 and 2006 the Rio Cordon basin showed relatively limited erosion activity. Hence, the climatic conditions and the landscape response can only partially explain the strong increase of sediment export recorded in the 1994-2006 period. In this sense, the sediment availability resulting from armour layer and bedform removal appears crucial to describing the sediment fluxes during this period, stressing the key role of the in-channel sediment supply. In the recent period 2007-2015 a marked climate warming accompanied by increased precipitation was observed. This climate forcing did not affect the landscape evolution, with sediment source extent remaining substantially in line between 2006 and 2016. The absence of a significant landscape response and the restoration of the channel armour layer can describe the limited sediment fluxes observed during the last decade. In particular, the increased temperature and precipitation were not accompanied by an increase in flood occurrence and magnitude, stressing the evident absence of hillslope-channel network coupling. This research was funded by the University of Padova Research Projects 'Sediment transfer processes in an Alpine basin: sediment cascades from hillslopes to the channel network-BIRD167919'.

Leveraging modern climatology to increase adaptive capacity across protected area networks

USGS Publications Warehouse

Davison, J.E.; Graumlich, L.J.; Rowland, E.L.; Pederson, G.T.; Breshears, D.D.

2012-01-01

Human-driven changes in the global environment pose an increasingly urgent challenge for the management of ecosystems that is made all the more difficult by the uncertain future of both environmental conditions and ecological responses. Land managers need strategies to increase regional adaptive capacity, but relevant and rapid assessment approaches are lacking. To address this need, we developed a method to assess regional protected area networks across biophysically important climatic gradients often linked to biodiversity and ecosystem function. We plot the land of the southwestern United States across axes of historical climate space, and identify landscapes that may serve as strategic additions to current protected area portfolios. Considering climate space is straightforward, and it can be applied using a variety of relevant climate parameters across differing levels of land protection status. The resulting maps identify lands that are climatically distinct from existing protected areas, and may be utilized in combination with other ecological and socio-economic information essential to collaborative landscape-scale decision-making. Alongside other strategies intended to protect species of special concern, natural resources, and other ecosystem services, the methods presented herein provide another important hedging strategy intended to increase the adaptive capacity of protected area networks. ?? 2011 Elsevier Ltd.

Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS

NASA Astrophysics Data System (ADS)

Tobin, Kenneth J.; Torres, Roberto; Crow, Wade T.; Bennett, Marvin E.

2017-09-01

This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lasting AMSR-E mission. Additionally, three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-active, CCI-passive, and CCI-combined). All of these products were 0.25° and taken daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997-2002; 2002-2005; 2005-2008; 2008-2011; 2011-2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the US Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the US Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root-zone soil moisture had a reasonably high lagged r value (r > 0. 5). The unknown T value was constrained based on two approaches: optimization of root mean square error (RMSE) and calculation based on the normalized difference vegetation index (NDVI) value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI-based estimates. The best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. The average Nash-Sutcliffe coefficients (NSs) for ARM ranged from -0. 1 to 0.3 and were similar to the results obtained from the USCRN network (0.2-0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1-0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of RMSE (in volumetric soil moisture), ARM values actually outperformed those from other networks (0.02-0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher (0.05-0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

PubMed

Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

2016-04-01

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

Humans reclaimed lands in NorthEastern Italy and artificial drainage networks: effects of 30 years of Agricultural Surface Water Management

NASA Astrophysics Data System (ADS)

Sofia, Giulia; Pizzulli, Federica; Tarolli, Paolo

2017-04-01

Agriculture and land-use management has changed drastically in Italy since the end of the Second World War, driven by local but also European agricultural policies. As a result of these changes in farming practices and land use, many drainage networks have changed producing a greater exposure to flooding with a broad range of impacts on society, also because of climate inputs coupling with the human drivers. This study focuses on two main points: which kind of land use and farming changes have been observed in the most recent years ( 30 years)? How do these changes interact with climate and soil conditions? An open challenge to understand how these changes influence the watershed response, is, in fact, to understand if rainfall characteristics and climate have a synergistic effect, if their interaction matters, or to understand what element has the greatest influence on the watershed response connected to agricultural changes. The work is based on a simple model of water infiltration due to soil properties, and a connected evaluation of the distributed surface water storage offered by artificial drainage networks in a study area in Veneto (north-eastern Italy). The analysis shows that economic changes control the development of agro-industrial landscapes, with effects on the hydrological response. However, these changes deeply interact with antecedent soil conditions and climate characteristics. Intense and irregular rainfall events and events with a high recurrence should be expected to be the most critical. The presented outcomes highlight the importance of understanding how agricultural practices can be the driver of or can be used to avoid, or at least mitigate, flooding. The proposed methods can be valuable tools in evaluating the costs and benefits of the management of water in agriculture to inform better policy decision-making. References Sofia G, Tarolli P. 2017. Hydrological Response to 30 years of Agricultural Surface Water Management. Land 6 (1): 3 DOI: 10.3390/land6010003 Sofia G, Roder G, Dalla Fontana G, Tarolli P. 2017. Flood dynamics in urbanised landscapes: 100 years of climate and humans' interaction. Scientific Reports 7, 40527 DOI: 10.1038/srep40527

Anticipating changes to future connectivity within a network of marine protected areas.

PubMed

Coleman, Melinda A; Cetina-Heredia, Paulina; Roughan, Moninya; Feng, Ming; van Sebille, Erik; Kelaher, Brendan P

2017-09-01

Continental boundary currents are projected to be altered under future scenarios of climate change. As these currents often influence dispersal and connectivity among populations of many marine organisms, changes to boundary currents may have dramatic implications for population persistence. Networks of marine protected areas (MPAs) often aim to maintain connectivity, but anticipation of the scale and extent of climatic impacts on connectivity are required to achieve this critical conservation goal in a future of climate change. For two key marine species (kelp and sea urchins), we use oceanographic modelling to predict how continental boundary currents are likely to change connectivity among a network of MPAs spanning over 1000 km of coastline off the coast of eastern Australia. Overall change in predicted connectivity among pairs of MPAs within the network did not change significantly over and above temporal variation within climatic scenarios, highlighting the need for future studies to incorporate temporal variation in dispersal to robustly anticipate likely change. However, the intricacies of connectivity between different pairs of MPAs were noteworthy. For kelp, poleward connectivity among pairs of MPAs tended to increase in the future, whereas equatorward connectivity tended to decrease. In contrast, for sea urchins, connectivity among pairs of MPAs generally decreased in both directions. Self-seeding within higher-latitude MPAs tended to increase, and the role of low-latitude MPAs as a sink for urchins changed significantly in contrasting ways. These projected changes have the potential to alter important genetic parameters with implications for adaptation and ecosystem vulnerability to climate change. Considering such changes, in the context of managing and designing MPA networks, may ensure that conservation goals are achieved into the future. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Integrated metagenomics and network analysis of soil microbial community of the forest timberline

PubMed Central

Ding, Junjun; Zhang, Yuguang; Deng, Ye; Cong, Jing; Lu, Hui; Sun, Xin; Yang, Caiyun; Yuan, Tong; Van Nostrand, Joy D.; Li, Diqiang; Zhou, Jizhong; Yang, Yunfeng

2015-01-01

The forest timberline responds quickly and markedly to climate changes, rendering it a ready indicator. Climate warming has caused an upshift of the timberline worldwide. However, the impact on belowground ecosystem and biogeochemical cycles remain elusive. To understand soil microbial ecology of the timberline, we analyzed microbial communities via 16s rRNA Illumina sequencing, a microarray-based tool named GeoChip 4.0 and a random matrix theory-based association network approach. We selected 24 sampling sites at two vegetation belts forming the timberline of Shennongjia Mountain in Hubei Province of China, a region with extraordinarily rich biodiversity. We found that temperature, among all of measured environmental parameters, showed the most significant and extensive linkages with microbial biomass, microbial diversity and composition at both taxonomic and functional gene levels, and microbial association network. Therefore, temperature was the best predictor for microbial community variations in the timberline. Furthermore, abundances of nitrogen cycle and phosphorus cycle genes were concomitant with NH4+-N, NO3−-N and total phosphorus, offering tangible clues to the underlying mechanisms of soil biogeochemical cycles. As the first glimpse at both taxonomic and functional compositions of soil microbial community of the timberline, our findings have major implications for predicting consequences of future timberline upshift. PMID:25613225

Interagency collaboration in the Rocky Mountains and Great Plains: Federal-university climate service networks for producing actionable information for climate change adaptation

NASA Astrophysics Data System (ADS)

Ray, A. J.; McNie, E.; Averyt, K.; Morisette, J. T.; Derner, J. D.; Ojima, D. S.; Dilling, L.; Barsugli, J. J.

2014-12-01

Several federal agencies in north-central United States are each working to develop and disseminate useful climate information to enhance resilience to climate change. This talk will discuss how the U.S. Geological Survey (USGS) the North Central Climate Science Center, the National Oceanic and Atmospheric Administration Western Water Assessment RISA, and the U.S. Department of Agriculture Climate Hub, are building and managing a collaborative research and climate-service network in the Rocky Mountains and Great Plains. This presentation will describe the evolution of the interagency collaboration and the partnership with universities to build a climate service network. Such collaboration takes time and intention and must include the right people and organizations to effectively bridge the gap between use-inspired research and application. In particular, we will discuss a focus on the Upper Missouri Basin, developing research to meet needs in a basin that has had relatively less attention on risks of climate change and adaptation to those risks. Each organization has its own mission, stakeholders, and priorities, but there are many commonalities and potential synergies. Together, these organizations, and their agency scientists and university partners, are fostering cross-agency collaboration at the regional scale to optimize efficient allocation of resources while simultaneously enabling information to be generated at a scale that is relevant to decision makers. By each organization knowing the others needs and priorities, there are opportunities to craft research agendas and strategies for providing services that take advantage of the strengths and skills of the different organizations. University partners are key components of each organization, and of the collaboration, who bring in expertise beyond that in the agencies, in particular connections to social scientists, extension services.

Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network

PubMed Central

Virkkala, Raimo; Heikkinen, Risto K.; Fronzek, Stefan; Leikola, Niko

2013-01-01

National reserve networks are one of the most important means of species conservation, but their efficiency may be diminished due to the projected climatic changes. Using bioclimatic envelope models and spatial data on habitats and conservation areas, we studied how efficient the reserve network will be in preserving 100 forest, mire, marshland, and alpine bird species of conservation concern in Finland in 2051–2080 under three different climate scenarios. The occurrences of the studied bird species were related to the amount of habitat preferred by each species in the different boreal zones. We employed a novel integrated habitat suitability index that takes into account both the species’ probability of occurrence from the bioclimatic models and the availability of suitable habitat. Using this suitability index, the distribution of the topmost 5% suitability squares (“hotspots”) in the four bird species groups in the period 1971–2000 and under the three scenarios were compared with the location of reserves with the highest amounts of the four habitats to study the efficiency of the network. In species of mires, marshlands, and Arctic mountains, a high proportion of protected habitat was included in the 5% hotspots in the scenarios in 2051–2080, showing that protected areas cover a high proportion of occurrences of bird species. In contrast, in forests in the southern and middle boreal zones, only a small proportion of the protected habitat was included in the 5% hotspots, indicating that the efficiency of the protected area network will be insufficient for forest birds in the future. In the northern boreal zone, the efficiency of the reserve network in forests was highly dependent on the strength of climate change varying between the scenarios. Overall, there is no single solution to preserving biodiversity in a changing climate, but several future pathways should be considered. PMID:23700420

Climate change, northern birds of conservation concern and matching the hotspots of habitat suitability with the reserve network.

PubMed

Virkkala, Raimo; Heikkinen, Risto K; Fronzek, Stefan; Leikola, Niko

2013-01-01

National reserve networks are one of the most important means of species conservation, but their efficiency may be diminished due to the projected climatic changes. Using bioclimatic envelope models and spatial data on habitats and conservation areas, we studied how efficient the reserve network will be in preserving 100 forest, mire, marshland, and alpine bird species of conservation concern in Finland in 2051-2080 under three different climate scenarios. The occurrences of the studied bird species were related to the amount of habitat preferred by each species in the different boreal zones. We employed a novel integrated habitat suitability index that takes into account both the species' probability of occurrence from the bioclimatic models and the availability of suitable habitat. Using this suitability index, the distribution of the topmost 5% suitability squares ("hotspots") in the four bird species groups in the period 1971-2000 and under the three scenarios were compared with the location of reserves with the highest amounts of the four habitats to study the efficiency of the network. In species of mires, marshlands, and Arctic mountains, a high proportion of protected habitat was included in the 5% hotspots in the scenarios in 2051-2080, showing that protected areas cover a high proportion of occurrences of bird species. In contrast, in forests in the southern and middle boreal zones, only a small proportion of the protected habitat was included in the 5% hotspots, indicating that the efficiency of the protected area network will be insufficient for forest birds in the future. In the northern boreal zone, the efficiency of the reserve network in forests was highly dependent on the strength of climate change varying between the scenarios. Overall, there is no single solution to preserving biodiversity in a changing climate, but several future pathways should be considered.

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Do networking activities outside of the classroom protect students against being bullied? A field study with students in secondary school settings in Germany.

PubMed

Blickle, Gerhard; Meurs, James A; Schoepe, Christine

2013-01-01

Research has shown that having close relationships with fellow classmates can provide a buffer for students against bullying and the negative outcomes associated with it. But, research has not explicitly examined the potential benefits of social networking behaviors outside of the classroom for those who could be bullied. This study addresses this gap and finds that, although a bullying climate in the classroom increases overall bullying, students high on external networking activities did not experience an increase in the bullying they received when in a classroom with a high bullying climate. However, the same group of students reported the largest degree of received bulling under conditions of a low bullying climate. We discuss the implications of our results and provide directions for future research.

P2S--Coupled simulation with the Precipitation-Runoff Modeling System (PRMS) and the Stream Temperature Network (SNTemp) Models

USGS Publications Warehouse

Markstrom, Steven L.

2012-01-01

A software program, called P2S, has been developed which couples the daily stream temperature simulation capabilities of the U.S. Geological Survey Stream Network Temperature model with the watershed hydrology simulation capabilities of the U.S. Geological Survey Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a modular, deterministic, distributed-parameter, physical-process watershed model that simulates hydrologic response to various combinations of climate and land use. Stream Network Temperature was developed to help aquatic biologists and engineers predict the effects of changes that hydrology and energy have on water temperatures. P2S will allow scientists and watershed managers to evaluate the effects of historical climate and projected climate change, landscape evolution, and resource management scenarios on watershed hydrology and in-stream water temperature.

Final Scientific/Technical Report from Hofstra University on DE-SC0001985

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

Farmer, E. Christa

The U.S. Department of Energy award DE-SC0001985 funded the Hofstra University Center for Climate Study (HUCCS) from 29 September 2009 through 1 October 2016. This support enabled several activities over the period of the grant, including 1) the pursuit of several research projects, including sediment coring of coastal marshes, analysis of habitat impact due to climate change, and effects of raindrops of CO2 transfer; 2) support for multiple graduate and undergraduate students, and sponsorship of research projects that involved high school students; 3) fostering mentoring relationships and networking; 4) the design, creation, and installation of an exhibit on climate changemore » at the Cradle of Aviation Museum in Garden City, NY as an effort of public outreach. A total of 11 presentations at conferences, one book, and one peer-reviewed journal article resulted from these activities.« less

A climate trend analysis of Chad

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Adoum, Alkhalil; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies significant decreases in rainfall and increases in air temperature across Chad, especially in the eastern part of the country. These analyses are based on quality-controlled station observations. Conclusions:* Summer rains have decreased in eastern Chad during the past 20 years. * Temperatures have increased by 0.8 °Celsius since 1975, amplifying the effect of droughts. * Crop yields are very low and stagnant. * The amount of farmland per person is low, and decliningrapidly.* Population growth combined with stagnating yieldscould lead to a 30 percent reduction in per capita cereal production by 2025.* In many cases, areas with changing climate are coincident with zones of substantial conflict, indicating some degree of association; however, the contribution of climate change to these conflicts is not currently understood.

Birmingham Urban Climate Laboratory (BUCL): Experiences, Challenges and Applications of an Urban Temperature Network

NASA Astrophysics Data System (ADS)

Muller, Catherine; Chapman, Lee; Young, Duick; Grimmond, Sue; Cai, Xiaoming

2013-04-01

The Birmingham Urban Climate Laboratory (BUCL) has recently been established by the University of Birmingham. BUCL is an in-situ, real-time urban network that will incorporate 3 nested networks - a wide-array of 25 weather stations, a dense array of 131 low-cost air temperature sensors and a fine-array of temperature sensor across the city-centre (50/km^2) - with the primary aim of monitoring air temperatures across a morphologically-heterogeneous urban conurbation for a variety of applications. During its installation there have been a number of challenges to overcome, including siting equipment in suitable urban locations, ensuring that the measurements were 'representative' of the local-scale climate, managing a large, near real-time data set and implementing QA/QC procedures. From these experiences, the establishment of a standardised urban meteorological network metadata protocol has been proposed in order to improve data quality, to ensure the end-user has access to all the supplementary information they would require for conducting valid analyses and to encourage the adequate recording and documentation of any changes to in-situ urban networks over time. This paper will provide an introduction to the BUCL in-situ network, give an overview of the challenges and experiences gained from its implementation, and finally discuss the proposed applications of the network, including its use in remote sensing observations of urban temperatures, as well as health and infrastructure applications.

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; McDermid, Sonali; Rosenzweig, Cynthia; Baigorria, Guillermo A.; Jones, James W.; Romero, Consuelo C.; Cecil, L. DeWayne

2014-01-01

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

Delta-Flux: An eddy covariance network for a climate-smart lower Mississippi basin

USDA-ARS?s Scientific Manuscript database

Networks of remotely monitored research sites are increasingly the model used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and Ameriflux lack contributions from the Lower Mississippi River Basin ...

A Probabilistic Analysis of Surface Water Flood Risk in London.

PubMed

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2018-06-01

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.

The impact of climate change on transportation in the gulf coast

USGS Publications Warehouse

Savonis, M.J.; Burkett, V.R.; Potter, J.R.; Kafalenos, R.; Hyman, R.; Leonard, K.

2009-01-01

Climate affects the design, construction, safety, operations, and maintenance of transportation infrastructure and systems. The prospect of a changing climate raises critical questions regarding how alterations in temperature, precipitation, storm events, and other aspects of the climate could affect the nation's transportation system. This regional assessment of climate change and its potential impacts on transportation systems addresses these questions for the central Gulf Coast between Houston and Mobile. Warming temperatures are likely to increase the costs of transportation construction, maintenance, and operations. More frequent extreme precipitation events will likely disrupt transportation networks with flooding and visibility problems. Relative sea level rise will make much of the existing infrastructure more prone to frequent or permanent inundation. Increased storm intensity may lead to increased service disruption and damage. Consideration of these factors in today's transportation decisions should lead to a more robust, resilient, and cost-effective transportation network in the coming decades. ?? 2009 ASCE.

Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)

NASA Astrophysics Data System (ADS)

Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.

2012-04-01

The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.

Implications of climate change on winter road networks in Ontario's Far North and northern Manitoba, Canada, based on climate model projections

NASA Astrophysics Data System (ADS)

Hori, Y.; Cheng, V. Y. S.; Gough, W. A.

2017-12-01

A network of winter roads in northern Canada connects a number of remote First Nations communities to all-season roads and rails. The extent of the winter road networks depends on the geographic features, socio-economic activities, and the numbers of remote First Nations so that it differs among the provinces. The most extensive winter road networks below the 60th parallel south are located in Ontario and Manitoba, serving 32 and 18 communities respectively. In recent years, a warmer climate has resulted in a shorter winter road season and an increase in unreliable road conditions; thus, limiting access among remote communities. This study focused on examining the future freezing degree-days (FDDs) accumulations during the winter road season at selected locations throughout Ontario's Far North and northern Manitoba using recent climate model projections from the multi-model ensembles of General Circulation Models (GCMs) under the Representative Concentration Pathway (RCP) scenarios. First, the non-parametric Mann-Kendall correlation test and the Theil-Sen method were used to identify any statistically significant trends between FDDs and time for the base period (1981-2010). Second, future climate scenarios are developed for the study areas using statistical downscaling methods. This study also examined the lowest threshold of FDDs during the winter road construction in a future period. Our previous study established the lowest threshold of 380 FDDs, which derived from the relationship between the FDDs and the opening dates of James Bay Winter Road near the Hudson-James Bay coast. Thus, this study applied the threshold measure as a conservative estimate of the minimum threshold of FDDs to examine the effects of climate change on the winter road construction period.

Climate Local Information over the Mediterranean to Respond User Needs

NASA Astrophysics Data System (ADS)

Ruti, P.

2012-12-01

CLIM-RUN aims at developing a protocol for applying new methodologies and improved modeling and downscaling tools for the provision of adequate climate information at regional to local scale that is relevant to and usable by different sectors of society (policymakers, industry, cities, etc.). Differently from current approaches, CLIM-RUN will develop a bottom-up protocol directly involving stakeholders early in the process with the aim of identifying well defined needs at the regional to local scale. The improved modeling and downscaling tools will then be used to optimally respond to these specific needs. The protocol is assessed by application to relevant case studies involving interdependent sectors, primarily tourism and energy, and natural hazards (wild fires) for representative target areas (mountainous regions, coastal areas, islands). The region of interest for the project is the Greater Mediterranean area, which is particularly important for two reasons. First, the Mediterranean is a recognized climate change hot-spot, i.e. a region particularly sensitive and vulnerable to global warming. Second, while a number of countries in Central and Northern Europe have already in place well developed climate service networks (e.g. the United Kingdom and Germany), no such network is available in the Mediterranean. CLIM-RUN is thus also intended to provide the seed for the formation of a Mediterranean basin-side climate service network which would eventually converge into a pan-European network. The general time horizon of interest for the project is the future period 2010-2050, a time horizon that encompasses the contributions of both inter-decadal variability and greenhouse-forced climate change. In particular, this time horizon places CLIM-RUN within the context of a new emerging area of research, that of decadal prediction, which will provide a strong potential for novel research.

Climate Science's Globally Distributed Infrastructure

NASA Astrophysics Data System (ADS)

Williams, D. N.

2016-12-01

The Earth System Grid Federation (ESGF) is primarily funded by the Department of Energy's (DOE's) Office of Science (the Office of Biological and Environmental Research [BER] Climate Data Informatics Program and the Office of Advanced Scientific Computing Research Next Generation Network for Science Program), the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF), the European Infrastructure for the European Network for Earth System Modeling (IS-ENES), and the Australian National University (ANU). Support also comes from other U.S. federal and international agencies. The federation works across multiple worldwide data centers and spans seven international network organizations to provide users with the ability to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a series of geographically distributed peer nodes that are independently administered and united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP; output used by the Intergovernmental Panel on Climate Change assessment reports), multiple model intercomparison projects (MIPs; endorsed by the World Climate Research Programme [WCRP]), and the Accelerated Climate Modeling for Energy (ACME; ESGF is included in the overarching ACME workflow process to store model output). ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs the global climate science community. Data served by ESGF includes not only model output but also observational data from satellites and instruments, reanalysis, and generated images.

Social capital in a regional inter-hospital network among trauma centers (trauma network): results of a qualitative study in Germany.

PubMed

Loss, Julika; Weigl, Johannes; Ernstberger, Antonio; Nerlich, Michael; Koller, Michael; Curbach, Janina

2018-02-26

As inter-hospital alliances have become increasingly popular in the healthcare sector, it is important to understand the challenges and benefits that the interaction between representatives of different hospitals entail. A prominent example of inter-hospital alliances are certified 'trauma networks', which consist of 5-30 trauma departments in a given region. Trauma networks are designed to improve trauma care by providing a coordinated response to injury, and have developed across the USA and multiple European countries since the 1960s. Their members need to interact regularly, e.g. develop joint protocols for patient transfer, or discuss patient safety. Social capital is a concept focusing on the development and benefits of relations and interactions within a network. The aim of our study was to explore how social capital is generated and used in a regional German trauma network. In this qualitative study, we performed semi-standardized face-to-face interviews with 23 senior trauma surgeons (2013-14). They were the official representatives of 23 out of 26 member hospitals of the Trauma Network Eastern Bavaria. The interviews covered the structure and functioning of the network, climate and reciprocity within the network, the development of social identity, and different resources and benefits derived from the network (e.g. facilitation of interactions, advocacy, work satisfaction). Transcripts were coded using thematic content analysis. According to the interviews, the studied trauma network became a group of surgeons with substantial bonding social capital. The surgeons perceived that the network's culture of interaction was flat, and they identified with the network due to a climate of mutual respect. They felt that the inclusive leadership helped establish a norm of reciprocity. Among the interviewed surgeons, the gain of technical information was seen as less important than the exchange of information on political aspects. The perceived resources derived from this social capital were smoother interactions, a higher medical credibility, and joint advocacy securing certain privileges. Apart from addressing quality of care, a trauma network may, by way of strengthening social capital among its members, serve as a valuable resource for the participating surgeons. Some member hospitals could exploit the social capital for strategic benefits.

Aquatic Nitrate Retention at River Network Scales Across Flow Conditions Determined Using Nested In Situ Sensors

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Mulukutla, G. K.; Cook, C.; Carey, R. O.

2017-11-01

Nonpoint pollution sources are strongly influenced by hydrology and are therefore sensitive to climate variability. Some pollutants entering aquatic ecosystems, e.g., nitrate, can be mitigated by in-stream processes during transport through river networks. Whole river network nitrate retention is difficult to quantify with observations. High frequency, in situ nitrate sensors, deployed in nested locations within a single watershed, can improve estimates of both nonpoint inputs and aquatic retention at river network scales. We deployed a nested sensor network and associated sampling in the urbanizing Oyster River watershed in coastal New Hampshire, USA, to quantify storm event-scale loading and retention at network scales. An end member analysis used the relative behavior of reactive nitrate and conservative chloride to infer river network fate of nitrate. In the headwater catchments, nitrate and chloride concentrations are both increasingly diluted with increasing storm size. At the mouth of the watershed, chloride is also diluted, but nitrate tended to increase. The end member analysis suggests that this pattern is the result of high retention during small storms (51-78%) that declines to zero during large storms. Although high frequency nitrate sensors did not alter estimates of fluxes over seasonal time periods compared to less frequent grab sampling, they provide the ability to estimate nitrate flux versus storm size at event scales that is critical for such analyses. Nested sensor networks can improve understanding of the controls of both loading and network scale retention, and therefore also improve management of nonpoint source pollution.

Toward a U.S. National Phenological Assessment

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey M.; Betancourt, Julio L.

2010-01-01

Third USA National Phenology Network (USA-NPN) and Research Coordination Network (RCN) Annual Meeting; Milwaukee, Wisconsin, 5-9 October 2009; Directional climate change will have profound and lasting effects throughout society that are best understood through fundamental physical and biological processes. One such process is phenology: how the timing of recurring biological events is affected by biotic and abiotic forces. Phenology is an early and integrative indicator of climate change readily understood by nonspecialists. Phenology affects the planting, maturation, and harvesting of food and fiber; pollination; timing and magnitude of allergies and disease; recreation and tourism; water quantity and quality; and ecosystem function and resilience. Thus, phenology is the gateway to climatic effects on both managed and unmanaged ecosystems. Adaptation to climatic variability and change will require integration of phenological data and models with climatic forecasts at seasonal to decadal time scales. Changes in phenologies have already manifested myriad effects of directional climate change. As these changes continue, it is critical to establish a comprehensive suite of benchmarks that can be tracked and mapped at local to continental scales with observations and climate models.

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

Dermody, Brian; van Beek, Rens; Meeks, Elijah; Klein Goldewijk, Kees; Scheidel, Walter; van der Velde, Ype; Bierkens, Marc; Wassen, Martin; Dekker, Stefan

2015-04-01

The Romans were perhaps the most impressive exponents of water resource management in pre-industrial times with irrigation and virtual water trade facilitating unprecedented urbanisation and socio-economic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanisation and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we found that irrigation and virtual water trade increased Roman resilience to inter-annual climate variability. However, urbanisation and population growth arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and eroded its resilience to climate variability in the long term. Our newest findings also assess the impact that persistent climate change associated with Holocene climate anomalies had on Roman water resource management. Specifically we assess the impact of the change in climate from the Roman Warm Period to the Dark Ages Cold Period on the Roman food supply and whether it could have contributed to the fall of the Western Roman Empire.

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Impacts of Climate Change on Operation of the US Rail Network

EPA Science Inventory

The rail network in the US is the largest network within any single country at 140,000 miles of Class 1 tracks. The network is predominantly focused on freight traffic with the exception of key passenger corridors along the eastern seaboard and in the upper Midwest. This extens...

Representativeness of four precipitation observational networks of China

NASA Astrophysics Data System (ADS)

Ren, Yuyu; Ren, Guoyu

2012-08-01

Four precipitation observational networks with varied station densities are maintained in China. They are: the Global Climate Observation System (GCOS) Surface Network (GSN), the national Reference Climate Network (RCN), the national Basic Meteorological Network (BMN), and the national Ordinary Meteorological Network (OMN). The GSN, RCN, BMN, and the merged network of RCN and BMN (R&B) have been widely used in climatology and climate change studies. In this paper, the impact of the usage of different networks on the precipitation climatology of China is evaluated by using the merged dataset of All Station Network (ASN) as a benchmark. The results show that all networks can capture the main features of the country average precipitation and its changing trends. The differences of average annual precipitation of the various networks from that of the ASN are less than 50 mm (⩽ 10%). All networks can successfully detect the rising trend of the average annual precipitation during 1961-2009, with the R&B exhibiting the best representativeness (only 2.90% relative difference) and the GSN the poorest (39.77%). As to the change trends of country average monthly precipitation, the networks can be ranked in descending order as R&B (1.27%), RCN (2.35%), BMN (4.17%), and GSN (7.46%), and larger relative differences appear from August to November. The networks produce quite consistent spatial patterns of annual precipitation change trends, and all show an increasing trend of precipitation in Northwest and Southeast China, and a decreasing trend in North China, Northeast China, and parts of central China. However, the representativeness of the BMN and R&B are better in annual and seasonal precipitation trends, in spite of the fact that they are still far from satisfactory. The relative differences of trends in some months and regions even reach more than 50%. The results also show that the representativeness of the RCN for country average precipitation is higher than that of the BMN because the RCN has a more homogeneous distribution of stations.

Distributed Hydrologic Modeling of Semiarid Basins in Arizona: A Platform for Land Cover and Climate Change Assessments

NASA Astrophysics Data System (ADS)

Hawkins, G. A.; Vivoni, E. R.

2011-12-01

Watershed management is challenged by rising concerns over climate change and its potential to interact with land cover alterations to impact regional water supplies and hydrologic processes. The inability to conduct experimental manipulations that address climate and land cover change at watershed scales limits the capacity of water managers to make decisions to protect future supplies. As a result, spatially-explicit, physically-based models possess value for predicting the possible consequences on watershed hydrology. In this study, we apply a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, soils distribution and availability of hydrologic data in forested regions of northern Arizona. As such, it can serve as a demonstration study in the broader region to illustrate the utility of distributed models for change assessment studies. Through a model application to summertime conditions, we compare the hydrologic response from three sources of meteorological input: (1) an available network of ground-based stations, (2) weather radar rainfall estimates, and (3) the North American Land Data Assimilation System (NLDAS). Comparisons focus on analysis of spatiotemporal distributions of precipitation, soil moisture, runoff generation, evapotranspiration and recharge from the root zone at high resolution for an assessment of sustainable water supplies for agricultural and domestic purposes. We also present a preliminary analysis of the impact of vegetation change arising from historical treatments in the Beaver Creek to inform the hydrologic consequences in the form of soil moisture and evapotranspiration patterns with differing degrees of proposed forest thinning. Our results are discussed in the context of improved hydrologic predictions for sustainability and decision-making under the uncertainties induced by combined climate and land cover change.

CO2 Urban Synthesis and Analysis ("CO2-USA") Network

NASA Astrophysics Data System (ADS)

Lin, J. C.; Hutyra, L.; Loughner, C.; Stein, A. F.; Lusk, K.; Mitchell, L.; Gately, C.; Wofsy, S. C.

2017-12-01

Emissions of carbon associated with cities comprise a large component of the anthropogenic source. A number of cities have announced plans to reduce greenhouse gas emissions, but the scientific knowledge to quantitatively track emissions and assess the efficacy of mitigation is lacking. As the global population increasingly resides in urban regions, scientific knowledge about how much, where, and why a particular city emits carbon becomes increasingly important. To address this gap, researchers have initiated studies of carbon emissions and cycling in several U.S. cities, making it timely to develop a collaborative network to exchange information on community standards and common measurements, facilitate data sharing, and create analysis frameworks and cross-city syntheses to catalyze a new generation of researchers and enable new collaborations tackling important objectives that are difficult to address in isolation. We describe initial results from an incipient network focusing initially on cities in the U.S. with low barriers of entry that entrains a cross-section of U.S. urban centers with varying characteristics: size, population density, vegetation, urban form, infrastructure, development rates, climate, and meteorological patterns. Results will be reported that emerge from an initial workshop covering data harmonization & integration, inventory comparison, stakeholder outreach, network design, inverse modeling, and collaboration.

Resolving uncertainties in the urban air quality, climate, and vegetation nexus through citizen science, satellite imagery, and atmospheric modeling

NASA Astrophysics Data System (ADS)

Jenerette, D.; Wang, J.; Chandler, M.; Ripplinger, J.; Koutzoukis, S.; Ge, C.; Castro Garcia, L.; Kucera, D.; Liu, X.

2017-12-01

Large uncertainties remain in identifying the distribution of urban air quality and temperature risks across neighborhood to regional scales. Nevertheless, many cities are actively expanding vegetation with an expectation to moderate both climate and air quality risks. We address these uncertainties through an integrated analysis of satellite data, atmospheric modeling, and in-situ environmental sensor networks maintained by citizen scientists. During the summer of 2017 we deployed neighborhood-scale networks of air temperature and ozone sensors through three campaigns across urbanized southern California. During each five-week campaign we deployed six sensor nodes that included an EPA federal equivalent method ozone sensor and a suite of meteorological sensors. Each node was further embedded in a network of 100 air temperature sensors that combined a randomized design developed by the research team and a design co-created by citizen scientists. Between 20 and 60 citizen scientists were recruited for each campaign, with local partners supporting outreach and training to ensure consistent deployment and data gathering. We observed substantial variation in both temperature and ozone concentrations at scales less than 4km, whole city, and the broader southern California region. At the whole city scale the average spatial variation with our ozone sensor network just for city of Long Beach was 26% of the mean, while corresponding variation in air temperature was only 7% of the mean. These findings contrast with atmospheric model estimates of variation at the regional scale of 11% and 1%. Our results show the magnitude of fine-scale variation underestimated by current models and may also suggest scaling functions that can connect neighborhood and regional variation in both ozone and temperature risks in southern California. By engaging citizen science with high quality sensors, satellite data, and real-time forecasting, our results help identify magnitudes of climate and air quality risk variation across scales and can guide individual decisions and urban policies surrounding vegetation to moderate these risks.

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Ihli, Monica; Hendrick, Oscar; Delgado-Arias, Sabrina; Escobar, Vanessa M.; Griffith, Peter

2015-01-01

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

Phenology for science, resource management, decision making, and education

USGS Publications Warehouse

Nolan, V.P.; Weltzin, J.F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Phenology for Science, Resource Management, Decision Making, and Education

NASA Astrophysics Data System (ADS)

Nolan, Vivian P.; Weltzin, Jake F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Professional Development in Climate Science Education as a Model for Navigating the Next Generations Science Standards - A High School Science Teacher's Perspective

NASA Astrophysics Data System (ADS)

Manning, C.; Buhr, S. M.

2012-12-01

The Next Generation Science Standards attempt to move the American K12 education system into the 21st century by focusing on science and engineering practice, crosscutting concepts, and the core ideas of the different disciplines. Putting these standards into practice will challenge a deeply entrenched system and science educators will need significant financial support from state and local governments, professional development from colleges and universities, and the creation of collegial academic networks that will help solve the many problems that will arise. While all of this sounds overwhelming, there are proven strategies and mechanisms already in place. Educators who tackle challenging topics like global climate change are turning to scientists and other like-minded teachers. Many of these teachers have never taken a class in atmospheric science but are expected to know the basics of climate and understand the emerging science as well. Teachers need scientists to continue to reach out and provide rigorous and in-depth professional development opportunities that enable them to answer difficult student questions and deal with community misconceptions about climate science. Examples of such programs include Earthworks, ICEE (Inspiring Climate Education Excellence) and ESSEA (Earth System Science Education Alliance). Projects like CLEAN (Climate Literacy and Energy Awareness Network) provide excellent resources that teachers can integrate into their lessons. All of these benefit from the umbrella of documents like Climate Literacy: The Essential Principles of Climate Science. Support from the aforementioned networks has encouraged the development of effective approaches for teaching climate science. From the perspective of a Geoscience master teacher and instructional coach, this presentation will demonstrate how scientists, researchers, and science education professionals have created models for professional development that create long-term networks supporting teachers who are willing to change how science is being taught right now. There will be specific examples of clearly written, evidence-based tools that address the general public's lack of critical climate knowledge and help to identify and change students' misconceptions. Specific content areas that continue to be overlooked as "common knowledge" but that need to be addressed in both pre- and in-service teacher instruction, textbooks, and online resources will be identified.

Water management in the Roman world

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; van Beek, Rens L. P. H.; Meeks, Elijah; Klein Goldewijk, Kees; Bierkens, Marc F. P.; Scheidel, Walter; Wassen, Martin J.; van der Velde, Ype; Dekker, Stefan C.

2014-05-01

Climate variability can have extreme impacts on societies in regions that are water-limited for agriculture. A society's ability to manage its water resources in such environments is critical to its long-term viability. Water management can involve improving agricultural yields through in-situ irrigation or redistributing water resources through trade in food. Here, we explore how such water management strategies affected the resilience of the Roman Empire to climate variability in the water-limited region of the Mediterranean. Using the large-scale hydrological model PCR-GLOBWB and estimates of landcover based on the Historical Database of the Global Environment (HYDE) we generate potential agricultural yield maps under variable climate. HYDE maps of population density in conjunction with potential yield estimates are used to develop maps of agricultural surplus and deficit. The surplus and deficit regions are abstracted to nodes on a water redistribution network based on the Stanford Geospatial Network Model of the Roman World (ORBIS). This demand-driven, water redistribution network allows us to quantitatively explore how water management strategies such as irrigation and food trade improved the resilience of the Roman Empire to climate variability.

Last millennium Northern Hemisphere summer temperatures from tree rings: Part II, spatially resolved reconstructions

NASA Astrophysics Data System (ADS)

Anchukaitis, Kevin J.; Wilson, Rob; Briffa, Keith R.; Büntgen, Ulf; Cook, Edward R.; D'Arrigo, Rosanne; Davi, Nicole; Esper, Jan; Frank, David; Gunnarson, Björn E.; Hegerl, Gabi; Helama, Samuli; Klesse, Stefan; Krusic, Paul J.; Linderholm, Hans W.; Myglan, Vladimir; Osborn, Timothy J.; Zhang, Peng; Rydval, Milos; Schneider, Lea; Schurer, Andrew; Wiles, Greg; Zorita, Eduardo

2017-05-01

Climate field reconstructions from networks of tree-ring proxy data can be used to characterize regional-scale climate changes, reveal spatial anomaly patterns associated with atmospheric circulation changes, radiative forcing, and large-scale modes of ocean-atmosphere variability, and provide spatiotemporal targets for climate model comparison and evaluation. Here we use a multiproxy network of tree-ring chronologies to reconstruct spatially resolved warm season (May-August) mean temperatures across the extratropical Northern Hemisphere (40-90°N) using Point-by-Point Regression (PPR). The resulting annual maps of temperature anomalies (750-1988 CE) reveal a consistent imprint of volcanism, with 96% of reconstructed grid points experiencing colder conditions following eruptions. Solar influences are detected at the bicentennial (de Vries) frequency, although at other time scales the influence of insolation variability is weak. Approximately 90% of reconstructed grid points show warmer temperatures during the Medieval Climate Anomaly when compared to the Little Ice Age, although the magnitude varies spatially across the hemisphere. Estimates of field reconstruction skill through time and over space can guide future temporal extension and spatial expansion of the proxy network.

The GAW Aerosol Lidar Observation Network (GALION) as a source of near-real time aerosol profile data for model evaluation and assimilation

NASA Astrophysics Data System (ADS)

Hoff, R. M.; Pappalardo, G.

2010-12-01

In 2007, the WMO Global Atmospheric Watch’s Science Advisory Group on Aerosols described a global network of lidar networks called GAW Aerosol Lidar Observation Network (GALION). GALION has a purpose of providing expanded coverage of aerosol observations for climate and air quality use. Comprised of networks in Asia (AD-NET), Europe (EARLINET and CIS-LINET), North America (CREST and CORALNET), South America (ALINE) and with contribution from global networks such as MPLNET and NDACC, the collaboration provides a unique capability to define aerosol profiles in the vertical. GALION is designed to supplement existing ground-based and column profiling (AERONET, PHOTONS, SKYNET, GAWPFR) stations. In September 2010, GALION held its second workshop and one component of discussion focussed how the network would integrate into model needs. GALION partners have contributed to the Sand and Dust Storm Warning and Analysis System (SDS-WAS) and to assimilation in models such as DREAM. This paper will present the conclusions of those discussions and how these observations can fit into a global model analysis framework. Questions of availability, latency, and aerosol parameters that might be ingested into models will be discussed. An example of where EARLINET and GALION have contributed in near-real time observations was the suite of measurements during the Eyjafjallajokull eruption in Iceland and its impact on European air travel. Lessons learned from this experience will be discussed.

Natural resource manager perceptions of agency performance on climate change.

PubMed

Lemieux, Christopher J; Thompson, Jessica L; Dawson, Jackie; Schuster, Rudy M

2013-01-15

An important precursor to the adoption of climate change adaptation strategies is to understand the perceived capacity to implement and operationalize such strategies. Utilizing an importance-performance analysis (IPA) evaluation framework, this article presents a comparative case study of federal and state land and natural resource manager perceptions of agency performance on factors influencing adaptive capacity in two U.S. regions (northern Colorado and southwestern South Dakota). Results revealed several important findings with substantial management implications. First, none of the managers ranked the adaptive capacity factors as a low priority. Second, managers held the perception that their agencies were performing either neutrally or poorly on most factors influencing adaptive capacity. Third, gap analysis revealed that significant improvements are required to facilitate optimal agency functioning when dealing with climate change-related management issues. Overall, results suggest that a host of institutional and policy-oriented (e.g., lack of clear mandate to adapt to climate change), financial and human resource (e.g., inadequate staff and financial resources), informational (e.g., inadequate research and monitoring programs) and contextual barriers (e.g., sufficient regional networks to mitigate potential transboundary impacts) currently challenge the efficient and effective integration of climate change into decision-making and management within agencies working in these regions. The IPA framework proved to be an effective tool to help managers identify and understand agency strengths, areas of concern, redundancies, and areas that warrant the use of limited funds and/or resource re-allocation in order to enhance adaptive capacity and maximize management effectiveness with respect to climate change. Copyright © 2012 Elsevier Ltd. All rights reserved.

A climate change context for the decline of a foundation tree species in south-western Australia: insights from phylogeography and species distribution modelling.

PubMed

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.

Ecological Network Indicators of Ecosystem Status and Change in the Baltic Sea

PubMed Central

Tomczak, Maciej T.; Heymans, Johanna J.; Yletyinen, Johanna; Niiranen, Susa; Otto, Saskia A.; Blenckner, Thorsten

2013-01-01

Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing. Ecological network analysis was performed to calculate indices of ecosystem change. The model replicated the regime shift. The analyses of indicators suggested that the system’s resilience was higher prior to 1988 and lower thereafter. The ecosystem topology also changed from a web-like structure to a linearized food-web. PMID:24116045

Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

NASA Astrophysics Data System (ADS)

Besha, A. A.; Steele, C. M.; Fernald, A.

2014-12-01

Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

Fluvial valleys in the heavily cratered terrains of Mars: Evidence for paleoclimatic change?

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Baker, V. R.

1993-01-01

Whether the formation of the Martian valley networks provides unequivocal evidence for drastically different climatic conditions remains debatable. Recent theoretical climate modeling precludes the existence of a temperate climate early in Mars' geological history. An alternative hypothesis suggests that Mars had a globally higher heat flow early in its geological history, bringing water tables to within 350 m of the surface. While a globally higher heat flow would initiate ground water circulation at depth, the valley networks probably required water tables to be even closer to the surface. Additionally, it was previously reported that the clustered distribution of the valley networks within terrain types, particularly in the heavily cratered highlands, suggests regional hydrological processes were important. The case for localized hydrothermal systems is summarized and estimates of both erosion volumes and of the implied water volumes for several Martian valley systems are presented.

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

PubMed Central

Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

2012-01-01

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587

Anticipating flash-floods: Multi-scale aspects of the social response

NASA Astrophysics Data System (ADS)

Lutoff, Céline; Creutin, Jean-Dominique; Ruin, Isabelle; Borga, Marco

2016-10-01

This paper aims at exploring the anticipation phase before a flash flood, corresponding to the time between the first climatic signs and the peak-flow. We focus the analysis on people's behaviors observing how they use this period to organize themselves for facing the event. The analysis is made through the definition of three specific scales: the timeliness scale, an analytical scale of anticipatory actions and the scale of human response network. Using a cross-scale and cross level analysis enables to define different phases in the anticipation period where different kind of environmental precursors are mobilized by the actors in order to make sense of the situation and adapt. Three main points deserve attention at the end: firstly, the concepts of timeliness, anticipatory actions and crisis network scales enable to understand differently what happens both physically and socially during an extreme event; secondly, analyzing the precursors shows that each level of crisis network uses different kinds of signs for estimating the situation, organizing and reacting; thirdly, there is a potential for improvement in observation on both social and physical processes at different scales, for verifying the theory of the anticipatory phases.

Vulnerability of European freshwater catchments to climate change.

PubMed

Markovic, Danijela; Carrizo, Savrina F; Kärcher, Oskar; Walz, Ariane; David, Jonathan N W

2017-09-01

Climate change is expected to exacerbate the current threats to freshwater ecosystems, yet multifaceted studies on the potential impacts of climate change on freshwater biodiversity at scales that inform management planning are lacking. The aim of this study was to fill this void through the development of a novel framework for assessing climate change vulnerability tailored to freshwater ecosystems. The three dimensions of climate change vulnerability are as follows: (i) exposure to climate change, (ii) sensitivity to altered environmental conditions and (iii) resilience potential. Our vulnerability framework includes 1685 freshwater species of plants, fishes, molluscs, odonates, amphibians, crayfish and turtles alongside key features within and between catchments, such as topography and connectivity. Several methodologies were used to combine these dimensions across a variety of future climate change models and scenarios. The resulting indices were overlaid to assess the vulnerability of European freshwater ecosystems at the catchment scale (18 783 catchments). The Balkan Lakes Ohrid and Prespa and Mediterranean islands emerge as most vulnerable to climate change. For the 2030s, we showed a consensus among the applied methods whereby up to 573 lake and river catchments are highly vulnerable to climate change. The anthropogenic disruption of hydrological habitat connectivity by dams is the major factor reducing climate change resilience. A gap analysis demonstrated that the current European protected area network covers <25% of the most vulnerable catchments. Practical steps need to be taken to ensure the persistence of freshwater biodiversity under climate change. Priority should be placed on enhancing stakeholder cooperation at the major basin scale towards preventing further degradation of freshwater ecosystems and maintaining connectivity among catchments. The catchments identified as most vulnerable to climate change provide preliminary targets for development of climate change conservation management and mitigation strategies. © 2017 John Wiley & Sons Ltd.

Testing Earth System Models with Earth System Data: using C isotopes in atmospheric CO2 to probe stomatal response to future climate change

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Miller, J. B.; Bowling, D. R.; Tans, P. P.; Baker, I. T.

2013-12-01

The global cycles of water and carbon are inextricably linked through photosynthesis. This link is largely governed by stomatal conductance that regulates water loss to the atmosphere and carbon gain to the biosphere. Although extensive research has focused on the response of stomatal conductance to increased atmospheric CO2, much less research has focused on the response of stomatal conductance to concomitant climate change. Here we make use of intensive and extensive measurements of C isotopes in source CO2 to the atmosphere (del-bio) to make inferences about stomatal response to climatic factors at a single forest site and across a network of global observation sites. Based on intensive observations at the Niwot Ridge Ameriflux site we discover that del-bio is an excellent physical proxy of stomatal response during the growing season and this response is highly sensitive to atmospheric water vapor pressure deficit (VPD). We use these intensive single forest site observations to inform our analysis of the global observation network, focusing in on the growing season across an array of terrestrial sites. We find that stomatal response across most of these terrestrial sites is also highly sensitive to VPD. Lastly, we simulate the response of future climate change on stomatal response and discover that future increases in VPD may limit the biosphere's capacity to assimilate future CO2 emissions. These results have direct implications for the benchmarking of Earth System Models as stomatal conductance in many of these models does not vary as a function of VPD.

Adapting Agricultural Water Use to Climate Change in a Post-Soviet Context: Challenges and Opportunities in Southeast Kazakhstan.

PubMed

Barrett, Tristam; Feola, Giuseppe; Khusnitdinova, Marina; Krylova, Viktoria

2017-01-01

The convergence of climate change and post-Soviet socio-economic and institutional transformations has been underexplored so far, as have the consequences of such convergence on crop agriculture in Central Asia. This paper provides a place-based analysis of constraints and opportunities for adaptation to climate change, with a specific focus on water use, in two districts in southeast Kazakhstan. Data were collected by 2 multi-stakeholder participatory workshops, 21 semi-structured in-depth interviews, and secondary statistical data. The present-day agricultural system is characterised by enduring Soviet-era management structures, but without state inputs that previously sustained agricultural productivity. Low margins of profitability on many privatised farms mean that attempts to implement integrated water management have produced water users associations unable to maintain and upgrade a deteriorating irrigation infrastructure. Although actors engage in tactical adaptation measures, necessary structural adaptation of the irrigation system remains difficult without significant public or private investments. Market-based water management models have been translated ambiguously to this region, which fails to encourage efficient water use and hinders adaptation to water stress. In addition, a mutual interdependence of informal networks and formal institutions characterises both state governance and everyday life in Kazakhstan. Such interdependence simultaneously facilitates operational and tactical adaptation, but hinders structural adaptation, as informal networks exist as a parallel system that achieves substantive outcomes while perpetuating the inertia and incapacity of the state bureaucracy. This article has relevance for critical understanding of integrated water management in practice and adaptation to climate change in post-Soviet institutional settings more broadly.

Season-specific climate signal and reconstruction from a new tree-ring network in the southwestern U.S

NASA Astrophysics Data System (ADS)

Griffin, D.; Woodhouse, C. A.; Meko, D. M.; Stahle, D. W.; Faulstich, H.; Leavitt, S. W.; Touchan, R.; Castro, C. L.; Carrillo, C.

2011-12-01

Our research group has updated existing tree-ring collections from over 50 sampling sites in the southwestern U.S. The new and archived specimens, carefully dated with dendrochronology, have been analyzed for width variations of "earlywood" and "latewood." These are the two components of annual rings in conifers that form in spring and summer, respectively. The network of primary tree-ring data has been used to develop a suite of well-replicated chronologies that extend through the 2008 growing season and are sensitive to the season-specific climate variability of the Southwest. Correlation function analysis indicates that the earlywood chronologies are closely related to cool season (October-April) precipitation variability and the chronologies derived from latewood are generally sensitive to precipitation and temperature conditions during the warm season (June-August). These proxy data originate from biological organisms and are not without bias; however, they do constitute a new means for evaluating the recent paleoclimatic history of the North American summer monsoon. The monsoon is a major component of the region's climate, impacting social and environmental systems and delivering up to 60% of the annual precipitation in the southwestern U.S. We have developed latewood-based retrodictions of monsoon precipitation that explain over half of the variance in the instrumental record, pass standard verification tests, and point to periods of persistent drought and wetness during the last 300-500 years. These reconstructions are being used to evaluate the monsoon's long-term spatiotemporal variability and its relationship to cool season climate and the major modes of ocean-atmosphere variability.

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

DOT National Transportation Integrated Search

2016-12-01

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

Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: effects of scale and climate change

EPA Science Inventory

Climate-change driven increases in water temperature pose multiple challenges for aquatic organisms. Predictions of climate change impacts to biota typically do not account for fine-grained spatiotemporal patterns of stream networks; yet patches of cooler water within rivers c...

Ten Tales of Betrayal: The Threat to Corporate Infrastructure by Information Technology Insiders Analysis and Observations

DTIC Science & Technology

2005-09-01

for traditional social networks. Often the computer is used to mediate their social interactions at work. This lack of social skills tends to...substance of the case narratives. These issue areas are: Subject and Attack Characteristics, Screening, Attack Detection, Organizational and Social ...strong relationship between personal stress as well as adverse social climates and the level of risk for systems abuse in any organization that relies

Supercomputing '91; Proceedings of the 4th Annual Conference on High Performance Computing, Albuquerque, NM, Nov. 18-22, 1991

NASA Technical Reports Server (NTRS)

1991-01-01

Various papers on supercomputing are presented. The general topics addressed include: program analysis/data dependence, memory access, distributed memory code generation, numerical algorithms, supercomputer benchmarks, latency tolerance, parallel programming, applications, processor design, networks, performance tools, mapping and scheduling, characterization affecting performance, parallelism packaging, computing climate change, combinatorial algorithms, hardware and software performance issues, system issues. (No individual items are abstracted in this volume)

Survival of Norway spruce remains higher in mixed stands under a dryer and warmer climate.

PubMed

Neuner, Susanne; Albrecht, Axel; Cullmann, Dominik; Engels, Friedrich; Griess, Verena C; Hahn, W Andreas; Hanewinkel, Marc; Härtl, Fabian; Kölling, Christian; Staupendahl, Kai; Knoke, Thomas

2015-02-01

Shifts in tree species distributions caused by climatic change are expected to cause severe losses in the economic value of European forestland. However, this projection disregards potential adaptation options such as tree species conversion, shorter production periods, or establishment of mixed species forests. The effect of tree species mixture has, as yet, not been quantitatively investigated for its potential to mitigate future increases in production risks. For the first time, we use survival time analysis to assess the effects of climate, species mixture and soil condition on survival probabilities for Norway spruce and European beech. Accelerated Failure Time (AFT) models based on an extensive dataset of almost 65,000 trees from the European Forest Damage Survey (FDS)--part of the European-wide Level I monitoring network--predicted a 24% decrease in survival probability for Norway spruce in pure stands at age 120 when unfavorable changes in climate conditions were assumed. Increasing species admixture greatly reduced the negative effects of unfavorable climate conditions, resulting in a decline in survival probabilities of only 7%. We conclude that future studies of forest management under climate change as well as forest policy measures need to take this, as yet unconsidered, strongly advantageous effect of tree species mixture into account. © 2014 John Wiley & Sons Ltd.

Systematic Conservation Planning in the Face of Climate Change: Bet-Hedging on the Columbia Plateau

PubMed Central

Schloss, Carrie A.; Lawler, Joshua J.; Larson, Eric R.; Papendick, Hilary L.; Case, Michael J.; Evans, Daniel M.; DeLap, Jack H.; Langdon, Jesse G. R.; Hall, Sonia A.; McRae, Brad H.

2011-01-01

Systematic conservation planning efforts typically focus on protecting current patterns of biodiversity. Climate change is poised to shift species distributions, reshuffle communities, and alter ecosystem functioning. In such a dynamic environment, lands selected to protect today's biodiversity may fail to do so in the future. One proposed approach to designing reserve networks that are robust to climate change involves protecting the diversity of abiotic conditions that in part determine species distributions and ecological processes. A set of abiotically diverse areas will likely support a diversity of ecological systems both today and into the future, although those two sets of systems might be dramatically different. Here, we demonstrate a conservation planning approach based on representing unique combinations of abiotic factors. We prioritize sites that represent the diversity of soils, topographies, and current climates of the Columbia Plateau. We then compare these sites to sites prioritized to protect current biodiversity. This comparison highlights places that are important for protecting both today's biodiversity and the diversity of abiotic factors that will likely determine biodiversity patterns in the future. It also highlights places where a reserve network designed solely to protect today's biodiversity would fail to capture the diversity of abiotic conditions and where such a network could be augmented to be more robust to climate-change impacts. PMID:22174897

The National Climate Assessment: A Treasure Trove for Education, Communications and Outreach

NASA Astrophysics Data System (ADS)

McCaffrey, M.; Berbeco, M.; Connolly, R.; Niepold, F., III; Poppleton, K. L. I.; Cloyd, E.; Ledley, T. S.

2014-12-01

Required by Congress under the Global Change Act of 1990 to inform the nation on the findings of current climate research, the Third U.S. National Climate Assessment (NCA), released in May 2014, is a rich resource for climate change education, communications and outreach (ECO). Using a website design with mobile applications in mind, NCA takes advantage of mobile learning technology which is revolutionizing how, when and where learning occurs. In an effort to maximize the "teachable moments" inherent in the assessment, a community of experts from the National Center for Science Education and the CLEAN Network, working under the auspices of the National Climate Assessment Network (NCAnet) Education Affinity Group, have developed a series of NCA Learning Pathways that match key NCA messages and resources with reviewed educational materials and trusted online information sources, thereby adding pedagogical depth to the assessment. The NCA Learning Pathways, which focus on the regional chapters of the report, are designed make climate change science more local, human, relevant and, if properly framed by educators and communicators, hopeful for learners. This paper touches on the challenges and opportunities of infusing climate education, communications and outreach into curriculum and society, and details the development and content of NCA Learning Pathways, which are available online through NOAA's Climate.gov website: http://www.climate.gov/teaching

The Climate Change Education Partnership Alliance: Building a Network for Effective Collaboration and Impact (Invited)

NASA Astrophysics Data System (ADS)

Scowcroft, G.

2013-12-01

The mission of the Climate Change Education Partnership Alliance (The Alliance), funded by the National Science Foundation (NSF), is to advance exemplary climate change education through research and innovative partnerships. Through six unique regional projects, The Alliance is reaching wide and diverse audiences across the U.S., while linking groups and institutions that might not otherwise be connected by a common focus on climate change education. The goals for The Alliance include building collaborations between projects and institutions, sharing effective practices, and leveraging resources to create a community in which the whole is greater than the sum of its parts. To foster these goals, NSF has funded a central hub, the Alliance Office. Currently, the Alliance Office is building the infrastructure necessary to support activities and communication between the projects. Successful networks need objectives for their interactions and a common vision held by the partners. In the first national meeting of The Alliance members, held in June 2013, the foundation was laid to begin this work. The Alliance now has a common mission and vision to guide the next four years of activities. An initial 'mapping' of the network has identified the scope and diversity of the network, how members are connected, current boundaries of the network, network strengths and weaknesses, and network needs. This information will serve as a baseline as the network develops. The Alliance has also identified the need for key 'working groups' which provide an opportunity for members to work across the projects on common goals. As The Alliance evolves, building blocks identified by the field of network science will be used to forge a strong and successful collaborative enterprise. Infrastructure is being established to support widespread engagement; social ties are being fostered through face-to-face meetings and monthly teleconferences; time is provided to build and share knowledge; the sharing of new and diverse perspectives is encouraged; and resources will be leveraged across and beyond the projects. This presentation will provide an overview of The Alliance activities, lessons learned thus far, and plans for the future.

A Lightweight Remote Parallel Visualization Platform for Interactive Massive Time-varying Climate Data Analysis

NASA Astrophysics Data System (ADS)

Li, J.; Zhang, T.; Huang, Q.; Liu, Q.

2014-12-01

Today's climate datasets are featured with large volume, high degree of spatiotemporal complexity and evolving fast overtime. As visualizing large volume distributed climate datasets is computationally intensive, traditional desktop based visualization applications fail to handle the computational intensity. Recently, scientists have developed remote visualization techniques to address the computational issue. Remote visualization techniques usually leverage server-side parallel computing capabilities to perform visualization tasks and deliver visualization results to clients through network. In this research, we aim to build a remote parallel visualization platform for visualizing and analyzing massive climate data. Our visualization platform was built based on Paraview, which is one of the most popular open source remote visualization and analysis applications. To further enhance the scalability and stability of the platform, we have employed cloud computing techniques to support the deployment of the platform. In this platform, all climate datasets are regular grid data which are stored in NetCDF format. Three types of data access methods are supported in the platform: accessing remote datasets provided by OpenDAP servers, accessing datasets hosted on the web visualization server and accessing local datasets. Despite different data access methods, all visualization tasks are completed at the server side to reduce the workload of clients. As a proof of concept, we have implemented a set of scientific visualization methods to show the feasibility of the platform. Preliminary results indicate that the framework can address the computation limitation of desktop based visualization applications.

High altitude environmental monitoring: the SHARE project and CEOP-HE

NASA Astrophysics Data System (ADS)

Tartari, G.

2009-04-01

Mountain areas above 2,500 m a.s.l. constitute about 25% of the Earth's surface and play a fundamental role in the global water balance, while influencing global climate and atmospheric circulation systems. Several millions, including lowlanders, are directly affected by the impacts of climate change on glaciers and water resource distribution. Mountains and high altitude plateaus are subject to the highest rate of temperature increase (e.g., Tibetan Plateau) and are recognized as particularly vulnerable to the effects of climate change. In spite of this, the number of permanent monitoring sites in the major environmental networks decreases with altitude. On a sample of two hundred high altitude automatic weather stations located above 2,500 m a.s.l., less than 20% are over 4,000 m, while there are only 24 stations in the world that could be considered "complete" high altitude observatories. Furthermore, entire mountain areas are left uncovered, creating significant data gaps which make reliable modelling and forecasting nearly impossible. In response to these problems, Ev-K2-CNR has developed the project SHARE (Stations at High Altitude for Research on the Environment) with the support of the Italian government and in collaboration with UNEP. This integrated environmental monitoring and research project aims to improve knowledge on the local, regional and global consequences of climate change in mountain regions and on the influence of high elevations on climate, atmospheric circulation and hydrology. SHARE today boasts a network of 13 permanent monitoring stations between 2,165 m and 8,000 m. Affiliated researchers have produced over 150 scientific publications in atmospheric sciences, meteorology and climate, glaciology, limnology and paleolimnology and geophysics. SHARE network data is also contributed to international programs (UNEP-ABC, WMO-GAW, WCRP-GEWEX-CEOP, NASA-AERONET, ILTER, EU-EUSAAR, EU-ACCENT). Within this context, the CEOP-High Elevations (CEOP-HE) element of regional focus was developed under the GEWEX CEOP programme to study multi-scale variability in water and energy cycles in high elevation areas, and to help improve observations, modelling and data management. Future plans include expansion of the SHARE network, addition of other key research areas including hydrology, and creation of mechanisms to favour exchange of data amongst high altitude networks. In coordination with other global research and monitoring projects (CliC, etc.), SHARE and CEOP-HE could provide a more organic and well-distributed interdisciplinary network, thus allowing governments and international agencies to better face impacts of climate change effects on energy and water budgets and elaborate appropriate adaptation strategies.

The Phenological Network of Catalonia: an historical perspective

NASA Astrophysics Data System (ADS)

Busto, Montserrat; Cunillera, Jordi; de Yzaguirre, Xavier

2017-04-01

The Meteorological Service of Catalonia (SMC) began systematic phenological observation in 1932. Forty-four observers registered the phenophases of 45 plant species, the first or last sighting of six bird species and the first sighting of one species of butterfly. The study First results of phenological observation in Catalonia was published in 1936, showing the different behaviour of the vegetal species and birds according to geographical location. The SMC worked against the military fascist uprising during the Spanish Civil War (1936-1939). Therefore, once the war was finished, the organisation was quickly closed by the Franco dictatorship and the National Meteorological Service became the official institution in Spain. This organization created the Spanish Phenological Network in 1943 following similar standards to the former Catalan network. The reintroduction of democracy and the return of the Catalan self-government structures (1977) allowed the re-foundation of the SMC in 1996. The Climatology Department needed phenological data to complement the study of climatic indicators and realised the fragile situation of phenology observations in Catalonia, with very few operational series. Following a preliminary analysis of the different systems of recording and saving data, the Phenological network of Catalonia (Fenocat) was re-established in 2013. Fenocat is an active partner of the Pan European Phenology Database (PEP725) that uses BBCH-scale coding and the USA National Phenology Network observation system. It is an example of citizen science. As at December 2016, Fenocat had recorded more than 450,000 data. The extension of summer climatic conditions in the Western Mediterranean region has resulted in repetition of phenopases in the same year, such as the second flowering of the holm oak (Quercus ilex), almond tree (Prunus dulcis) and sweet cherry tree (Prunus avium), or the delay in the departure data of the swallow (Hirundo rustica) and hoopoe (Upupa epops). Fenocat technicians are also involved in data rescue initiatives that allow the study of historical phenological series. The La Serra d'Almos (near Tarragona) phenological series is an example that shows the life cycle trends for plants and birds observed since 1971. The Phenological Network of Catalonia has marked a turning point in the recording of the rhythms of nature in Catalonia and works to preserve sensitive information for the study of climate change in the fragile Mediterranean ecosystem.

Spatial performance of RegEM climate field reconstruction techniques in a realistic pseudoproxy context

NASA Astrophysics Data System (ADS)

Wang, J.; Emile-Geay, J.; Guillot, D.

2011-12-01

Several methods of climate field reconstructions (CFRs) have been introduced in the past few years to estimate past climate variability from proxy data over the Common Era. The pseudoproxy framework has become a tool of choice for assessing the relative merits of such methods. Here we compare four variants of the RegEM algorithm [Schneider, 2001], using a pseudoproxy network mimicking the key spatio-temporal characteristics of the network of Mann et al., 2008 (hereinafter M08); the methods are (1) RegEM TTLS (2) RegEM iTTLS (3) GraphEM and (4) RegEM iRIDGE. To ensure continuity with previous work [Smerdon et al. 2011], pseudoproxy series are designed as a white-noise degraded version of the simulated temperature field [Amman et al. 2007] over 850-1980 C.E. colocated with 1138 M08 proxies. We use signal-to-noise ratios (SNRs) of: ∞ (no noise), 1.0, 0.5 and 0.25, to simulate differences in proxy quality. Two novelties in pseudoproxy design are introduced here: (1) the decrease in proxy availability over time follows that found in M08, (2) a realistic case where the SNR is empirically derived from correlations between each M08 proxy and the HadCRUT3v temperature field. It is found that this realistic SNR is clustered around 0.3, but ranges from 0.1 to 0.8. Verification statistics such as RE, CE, r2, bias, standard deviation ratio and RMSE are presented for each method at each SNR level. The results show that all methods perform relatively well at SNR levels higher than 0.5, but display drastically different performances at lower SNR levels. Compared with results using pseudoproxy network of Mann et al., 1998, (hereinafter MBH98), the reconstruction skill of the M08 network is relatively improved, in line with the findings of Smerdon et al., 2011. Overall, we find that GraphEM and iTTLS tend to produce more robust estimates of the temperature field at low SNR levels than other schemes, while preserving a higher amount of variance in the target field. Ammann, C. M., F. Joos, D. S. Schimel, B. L. Otto-Bliesner, and R. A. Tomas (2007), Solar influence on climate during the past millennium: Results from transient simulations with the NCAR Climate System Model, Proc. Natl. Acad. Sci. U. S. A., 104, 3713-3718, doi:10.1073/pnas.0605064103. Mann, M. E., R. S. Bradley, and M. K. Hughes (1998), Global-scale temperaturepatterns and climate forcing over the past six centuries, Nature, 392, 779-787, doi:10.1038/33859. Mann, M. E., S. Rutherford, E. Wahl, and C. Ammann (2007), Robustness of proxy-based climate field reconstruction methods, J. Geophys. Res., 112, D12109, doi:10.1029/2006JD008272. Mann, M. E., et al. (2008), Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia, Proc. Natl. Acad. Sci. U. S. A., 105, 13,252-13,257, doi:10.1073/pnas.0805721105. Schneider, T. (2001), Analysis of incomplete climate data: Estimation of mean values and covariance matrices and imputation of missing values, J. Clim., 14, 853-871, doi:10.1175/1520-0442(2001)014<0853: AOICDE>2.0.CO;2. Smerdon, J. E., A. Kaplan, E. Zorita, J. F. González-Rouco, and M. N. Evans (2011), Spatial performance of four climate field reconstruction methods targeting the Common Era, Geophys. Res. Lett., 38, L11705, doi:10.1029/2011GL047372.

Use of artificial neural network for spatial rainfall analysis

NASA Astrophysics Data System (ADS)

Paraskevas, Tsangaratos; Dimitrios, Rozos; Andreas, Benardos

2014-04-01

In the present study, the precipitation data measured at 23 rain gauge stations over the Achaia County, Greece, were used to estimate the spatial distribution of the mean annual precipitation values over a specific catchment area. The objective of this work was achieved by programming an Artificial Neural Network (ANN) that uses the feed-forward back-propagation algorithm as an alternative interpolating technique. A Geographic Information System (GIS) was utilized to process the data derived by the ANN and to create a continuous surface that represented the spatial mean annual precipitation distribution. The ANN introduced an optimization procedure that was implemented during training, adjusting the hidden number of neurons and the convergence of the ANN in order to select the best network architecture. The performance of the ANN was evaluated using three standard statistical evaluation criteria applied to the study area and showed good performance. The outcomes were also compared with the results obtained from a previous study in the area of research which used a linear regression analysis for the estimation of the mean annual precipitation values giving more accurate results. The information and knowledge gained from the present study could improve the accuracy of analysis concerning hydrology and hydrogeological models, ground water studies, flood related applications and climate analysis studies.

Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

PubMed Central

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results. PMID:22389597

Simulation of greenhouse climate monitoring and control with wireless sensor network and event-based control.

PubMed

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

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

Wu, Chase Qishi; Zhu, Michelle Mengxia

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models featuremore » diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific workflows with the convenience of a few mouse clicks while hiding the implementation and technical details from end users. Particularly, we will consider two types of applications with distinct performance requirements: data-centric and service-centric applications. For data-centric applications, the main workflow task involves large-volume data generation, catalog, storage, and movement typically from supercomputers or experimental facilities to a team of geographically distributed users; while for service-centric applications, the main focus of workflow is on data archiving, preprocessing, filtering, synthesis, visualization, and other application-specific analysis. We will conduct a comprehensive comparison of existing workflow systems and choose the best suited one with open-source code, a flexible system structure, and a large user base as the starting point for our development. Based on the chosen system, we will develop and integrate new components including a black box design of computing modules, performance monitoring and prediction, and workflow optimization and reconfiguration, which are missing from existing workflow systems. A modular design for separating specification, execution, and monitoring aspects will be adopted to establish a common generic infrastructure suited for a wide spectrum of science applications. We will further design and develop efficient workflow mapping and scheduling algorithms to optimize the workflow performance in terms of minimum end-to-end delay, maximum frame rate, and highest reliability. We will develop and demonstrate the SWAMP system in a local environment, the grid network, and the 100Gpbs Advanced Network Initiative (ANI) testbed. The demonstration will target scientific applications in climate modeling and high energy physics and the functions to be demonstrated include workflow deployment, execution, steering, and reconfiguration. Throughout the project period, we will work closely with the science communities in the fields of climate modeling and high energy physics including Spallation Neutron Source (SNS) and Large Hadron Collider (LHC) projects to mature the system for production use.« less

The uncertain climate footprint of wetlands under human pressure

PubMed Central

Petrescu, Ana Maria Roxana; Lohila, Annalea; Tuovinen, Juha-Pekka; Baldocchi, Dennis D.; Roulet, Nigel T.; Vesala, Timo; Dolman, Albertus Johannes; Oechel, Walter C.; Marcolla, Barbara; Friborg, Thomas; Rinne, Janne; Matthes, Jaclyn Hatala; Merbold, Lutz; Meijide, Ana; Kiely, Gerard; Sottocornola, Matteo; Sachs, Torsten; Zona, Donatella; Varlagin, Andrej; Lai, Derrick Y. F.; Veenendaal, Elmar; Parmentier, Frans-Jan W.; Skiba, Ute; Lund, Magnus; Hensen, Arjan; van Huissteden, Jacobus; Flanagan, Lawrence B.; Shurpali, Narasinha J.; Grünwald, Thomas; Humphreys, Elyn R.; Jackowicz-Korczyński, Marcin; Aurela, Mika A.; Laurila, Tuomas; Grüning, Carsten; Corradi, Chiara A. R.; Schrier-Uijl, Arina P.; Christensen, Torben R.; Tamstorf, Mikkel P.; Mastepanov, Mikhail; Martikainen, Pertti J.; Verma, Shashi B.; Bernhofer, Christian; Cescatti, Alessandro

2015-01-01

Significant climate risks are associated with a positive carbon–temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the “cost” of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse–response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange. PMID:25831506

The uncertain climate footprint of wetlands under human pressure.

PubMed

Petrescu, Ana Maria Roxana; Lohila, Annalea; Tuovinen, Juha-Pekka; Baldocchi, Dennis D; Desai, Ankur R; Roulet, Nigel T; Vesala, Timo; Dolman, Albertus Johannes; Oechel, Walter C; Marcolla, Barbara; Friborg, Thomas; Rinne, Janne; Matthes, Jaclyn Hatala; Merbold, Lutz; Meijide, Ana; Kiely, Gerard; Sottocornola, Matteo; Sachs, Torsten; Zona, Donatella; Varlagin, Andrej; Lai, Derrick Y F; Veenendaal, Elmar; Parmentier, Frans-Jan W; Skiba, Ute; Lund, Magnus; Hensen, Arjan; van Huissteden, Jacobus; Flanagan, Lawrence B; Shurpali, Narasinha J; Grünwald, Thomas; Humphreys, Elyn R; Jackowicz-Korczyński, Marcin; Aurela, Mika A; Laurila, Tuomas; Grüning, Carsten; Corradi, Chiara A R; Schrier-Uijl, Arina P; Christensen, Torben R; Tamstorf, Mikkel P; Mastepanov, Mikhail; Martikainen, Pertti J; Verma, Shashi B; Bernhofer, Christian; Cescatti, Alessandro

2015-04-14

Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

Changing currents: a strategy for understanding and predicting the changing ocean circulation.

PubMed

Bryden, Harry L; Robinson, Carol; Griffiths, Gwyn

2012-12-13

Within the context of UK marine science, we project a strategy for ocean circulation research over the next 20 years. We recommend a focus on three types of research: (i) sustained observations of the varying and evolving ocean circulation, (ii) careful analysis and interpretation of the observed climate changes for comparison with climate model projections, and (iii) the design and execution of focused field experiments to understand ocean processes that are not resolved in coupled climate models so as to be able to embed these processes realistically in the models. Within UK-sustained observations, we emphasize smart, cost-effective design of the observational network to extract maximum information from limited field resources. We encourage the incorporation of new sensors and new energy sources within the operational environment of UK-sustained observational programmes to bridge the gap that normally separates laboratory prototype from operational instrument. For interpreting the climate-change records obtained through a variety of national and international sustained observational programmes, creative and dedicated UK scientists should lead efforts to extract the meaningful signals and patterns of climate change and to interpret them so as to project future changes. For the process studies, individual scientists will need to work together in team environments to combine observational and process modelling results into effective improvements in the coupled climate models that will lead to more accurate climate predictions.

Climate-driven trends in the occurrence of major floods across North America and Europe

NASA Astrophysics Data System (ADS)

Hodgkins, Glenn A.; Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Renard, Benjamin; Stahl, Kerstin; Fleig, Anne K.; Madsen, Henrik; Mediero, Luis; Korhonen, Johanna; Murphy, Conor; Crochet, Philippe; Wilson, Donna

2016-04-01

Every year river floods cause enormous damage around the world. Recent major floods in North America and Europe, for example, have received much press, with some concluding that these floods are more frequent in recent years as a result of anthropogenic warming. There has been considerable scientific effort invested in establishing whether observed flood records show evidence of trends or variability in flood frequency, and to determine whether these patterns can be linked to climatic changes. However, the river catchments used in many published studies are influenced by direct human alteration such as reservoir regulation and urbanisation, which can confound the interpretation of climate-driven variability. Furthermore, a majority of previous studies have analysed changes in low magnitude floods, such as the annual peak flow, at a national scale. Few studies are known that have analysed changes in large floods (greater than 25-year floods) on a continental scale. To fill this research gap, we present a study analysing flood flows from reference hydrologic networks (RHNs) or RHN-like gauges across a large study domain embracing North America and much of Europe. RHNs comprise gauging stations with minimally disturbed catchment conditions, which have a near-natural flow regime and provide good quality data; RHN analyses thus allow hydro-climatic variability to be distinguished from direct artificial disturbances or data inhomogeneities. One of the key innovations in this study is the definition of an RHN-like network consisting of 1204 catchments on a continental scale. The network incorporates existing, well-established RHNs in Canada, the US, the UK, Ireland and Norway, alongside RHN-like catchments from Europe (France, Switzerland, Iceland, Denmark, Sweden, Finland, Spain), which have been incorporated in the network following a major effort to ensure RHN-like status of candidate gauges through consultation with local experts. As the aim of the study is to examine long-term variability in the number of major floods, annual exceedances of 25-, 50-, and 100-year floods during the last 50 - 80 years are estimated for all study gauges across North America and Europe, and for smaller groups of gauges defined by catchment size, location, climate, flood threshold, and period of record. Trends are computed using logistic regression techniques, supported by a suite of methods used to test the assumptions used in the analysis. We also analyse relationships between major flood occurrence and atmosphere/ocean indices (the AMO, NAO, PDO and SOI). Our analysis finds no compelling evidence for consistent changes over time in major-flood occurrence across North America and Europe, indicating that generalizations about major-flood occurrence trends across large domains or a diversity of catchment types are ungrounded. There are in fact more significant relationships between major-flood occurrence and the AMO than between flood occurrence and time. Flood occurrence overall (based on data from all 1204 gauges in our study) increased from 1961 to 2010 but not significantly, driven primarily by European increases. Non-significant increases were also found overall from 1931 to 2010 (322 gauges) but driven primarily by North American increases. Flood occurrence increased and decreased (including some significant changes) for the various sub-groups of gauges. Overall this study demonstrates that past changes in major-flood occurrence are highly complex and future changes will be likewise. International hydrologic networks containing minimally altered catchments will play a key role in understanding these complexities.

Governing for a Healthy Population: Towards an Understanding of How Decision-Making Will Determine Our Global Health in a Changing Climate

PubMed Central

Bowen, Kathryn J.; Friel, Sharon; Ebi, Kristie; Butler, Colin D.; Miller, Fiona; McMichael, Anthony J.

2011-01-01

Enhancing the adaptive capacity of individuals, communities, institutions and nations is pivotal to protecting and improving human health and well-being in the face of systemic social inequity plus dangerous climate change. However, research on the determinants of adaptive capacity in relation to health, particularly concerning the role of governance, is in its infancy. This paper highlights the intersections between global health, climate change and governance. It presents an overview of these key concerns, their relation to each other, and the potential that a greater understanding of governance may present opportunities to strengthen policy and action responses to the health effects of climate change. Important parallels between addressing health inequities and sustainable development practices in the face of global environmental change are also highlighted. We propose that governance can be investigated through two key lenses within the earth system governance theoretical framework; agency and architecture. These two governance concepts can be evaluated using methods of social network research and policy analysis using case studies and is the subject of further research. PMID:22470278

Translating Research into Practice: Establishing a Network of Climate Change Practitioners in Ontario, Canada

NASA Astrophysics Data System (ADS)

Milner, G. A.

2017-12-01

Climate research and information continues to emerge at a rapid pace from the academic and scientific community. Decisions being made today by planners, engineers and staff across the Province of Ontario rely on science and information to plan and build our systems for the long term. Of course, as scientific information evolves continuously to produce lessons learned and new evidence, on the ground decisions often become entrenched in outdated information and need updating. Given this, bridging the gap between research to policy, and research to practice is of critical importance as the Province of Ontario upgrades its infrastructure, plans for long term growth in population within the Great Lakes Basin, and manages its natural systems and resources responsibly. The Ontario Climate Consortium (OCC) is an interdisciplinary network of academics and practitioners established in 2011 in the province that works to mobilize climate research findings towards building capacity, inspiring climate action, and training end-users with the latest science. The OCC has collaborated with more than 39 organizations throughout Ontario and across Canada, including government agencies at all levels (local, provincial and federal), non-profit organizations and private sector companies. This presentation will describe the foundations of climate action in Ontario, Canada including the landscape of climate adaptation practitioners from both public and private organizations. Furthermore, this presentation will feature lessons learned from the OCC network, including: 1) What comprises effective partnerships to undertake climate change adaptation planning for cities; 2) How to build the foundation for capacity at agencies with limited resources or expertise in the climate change field; and 3) How to successfully mobilize complex climate data for end-users to produce usable tools (through a case study research project). The latter will present findings from a two-year research project undertaken with OCC and the City of Vaughan, just northwest of Toronto, which examined vulnerability and risks of climate change to the city's stormwater infrastructure system and produced key tools and information for managers to begin building climate resilience into their planning and operations.

The European Science Foundation (ESF) Network SEDIFLUX — An introduction and overview

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Etienne, Samuel; Etzelmüller, Bernd; Gordeev, Vyacheslav V.; Käyhkö, Jukka; Rachold, Volker; Russell, Andrew J.; Schmidt, Karl-Heinz; Sæmundsson, Þorsteinn; Tweed, Fiona S.; Warburton, Jeff

2006-10-01

Climate change will cause major changes in the Earth surface systems, especially in high-latitude and high-altitude cold environments. Geomorphological processes operating at the Earth's surface, transferring sediments and changing landforms are dependent on climate and will be significantly affected by climate change. More reliable modelling of sediment transfer processes operating under present-day climatic settings is needed to determine the consequences of climate change. It is necessary to collect and to compare data and knowledge from a wide range of different high-latitude and high-altitude cold environments and to develop more standardized methods and approaches for future research on sediment fluxes and relationships between climate and sedimentary transfer processes. In Europe, the wide range of high-latitude and high-altitude cold environments provides great potential to investigate climate-process relationships and to model the effects of climate change by using space for time substitution. The European Science Foundation (ESF) Network (01.01.2004-31.12.2006) "Sedimentary Source-to-Sink-Fluxes in Cold Environments" ( SEDIFLUX) is bringing together leading scientists, young scientists and research teams from different fields. SEDIFLUX forms a framework for an integrated and multidisciplinary investigation of the addressed topic and is a major catalyst for strengthening and extending contacts, collaborative research activities and mobility of scientists in Europe. It also points to areas within Europe that would benefit from wider research collaboration (e.g. Russia, Poland). The SEDIFLUX Steering Committee consists of scientists from seven European countries: Achim A. Beylich, Co-ordinator of SEDIFLUX (Trondheim, Norway), Samuel Etienne (Clermont-Ferrand, France), Bernd Etzelmüller (Oslo, Norway), Vyacheslav V. Gordeev (Moscow, Russia), Jukka Käyhkö (Turku, Finland), Volker Rachold (Potsdam, Germany), Andrew J. Russell (Newcastle, England, UK), Karl-Heinz Schmidt (Halle/S., Germany), Þorsteinn Sæmundsson (Sauðárkrókur, Iceland), Fiona S. Tweed (Staffordshire, England, UK) and Jeff Warburton (Durham, England, UK). SEDIFLUX activities include four Science Meetings: in Sauðárkrókur, Iceland (June 18th-June 21st, 2004), Clermont-Ferrand, France (January 20th-22nd, 2005), Durham, England, UK (December 15th-20th, 2005) and Trondheim, Norway (October 29th-November 1st, 2006), Steering Committee Meetings attached to these Science Meetings, a Session co-organized by SEDIFLUX at the Second European Permafrost Conference, June 12th-17th, 2005, in Potsdam, Germany, publication of Scientific Reports and Abstract Volumes, publication of Special Issues of Journals and of a SEDIFLUX Handbook, creation of a SEDIFLUX Database, an effective diffusion and dissemination of SEDIFLUX activities and outputs by using electronic media (Websites, Newsletters, Forum), invitations of leading experts from other parts of the world, policy makers and land managers to the Science Meetings. The ESF Network SEDIFLUX is organized in four Working Groups: I: Selection of critical test catchments; II: Analysis of geographical and geological settings of test catchments; III: Analysis of present-day fluxes; IV: Integration and data management. The major outputs from the Working Groups will be published in the SEDIFLUX Handbook, including guidelines for future monitoring programmes and a section, which is particularly targeted at end-users. A strong monitoring and operational data collection and more standardized methods provide a baseline for the development of reliable models and for future research in the changing high-latitude and high-altitude cold environments. ESF SEDIFLUX will continue and will be extended as I.A.G./A.I.G. Working Group on Sediment Budgets in Cold Environments (SEDIBUD). Apart from further collaborations and collaborative research activities project and programme applications at both the national and the European level following the three-year ESF Network are discussed and initiated.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

WSN system design by using an innovative neural network model to perform thermals forecasting in a urban canyon scenario

NASA Astrophysics Data System (ADS)

Giuseppina, Nicolosi; Salvatore, Tirrito

2015-12-01

Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.

How has climate change altered network connectivity in a mountain stream network?

NASA Astrophysics Data System (ADS)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Johnson, S.

2017-12-01

Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish migration) and indirectly (e.g., stream temperature modeling). Additionally, our results inform management and regulatory needs such as estimating connectivity for entire river networks as a basis for regulation, and identifying the complexity of a shifting baseline in identifying a regulatory basis.

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

NASA Astrophysics Data System (ADS)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows differences among basins previously classified as the same type, which are not noticeable in their horizontal properties and helps reduce misclassifications within the old clusters. Additional hydro-geomorphological metrics are to be considered in the classification method to improve the effectiveness of it.

The Use of Convolutional Neural Network in Relating Precipitation to Circulation

NASA Astrophysics Data System (ADS)

Pan, B.; Hsu, K. L.; AghaKouchak, A.; Sorooshian, S.

2017-12-01

Precipitation prediction in dynamical weather and climate models depends on 1) the predictability of pressure or geopotential height for the forecasting period and 2) the successive work of interpreting the pressure field in terms of precipitation events. The later task is represented as parameterization schemes in numerical models, where detailed computing inevitably blurs the hidden cause-and-effect relationship in precipitation generation. The "big data" provided by numerical simulation, reanalysis and observation networks requires better causation analysis for people to digest and realize their use. While classic synoptical analysis methods are very-often insufficient for spatially distributed high dimensional data, a Convolutional Neural Network(CNN) is developed here to directly relate precipitation with circulation. Case study carried over west coast United States during boreal winter showed that CNN can locate and capture key pressure zones of different structures to project precipitation spatial distribution with high accuracy across hourly to monthly scales. This direct connection between atmospheric circulation and precipitation offers a probe for attributing precipitation to the coverage, location, intensity and spatial structure of characteristic pressure zones, which can be used for model diagnosis and improvement.

Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls

NASA Astrophysics Data System (ADS)

Zou, Yong; Donner, Reik V.; Kurths, Jürgen

2015-02-01

Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm [Liu et al. Phys. Rev. E 89, 032814 (2014), 10.1103/PhysRevE.89.032814] are mainly due to an inappropriate treatment disregarding the intrinsic nonstationarity of such processes. Complementarily, we analyze some RN properties of the closely related stationary fractional Gaussian noise (fGn) processes and find that the resulting network properties are well-defined and behave as one would expect from basic conceptual considerations. Our results demonstrate that RN analysis can indeed provide meaningful results for stationary stochastic processes, given a proper selection of its intrinsic methodological parameters, whereas it is prone to fail to uniquely retrieve RN properties for nonstationary stochastic processes like fBm.

Upper Colorado River Basin Climate Effects Network

USGS Publications Warehouse

Belnap, Jayne; Campbell, Donald; Kershner, Jeff

2011-01-01

The Upper Colorado River Basin (UCRB) Climate Effects Network (CEN) is a science team established to provide information to assist land managers in future decision making processes by providing a better understanding of how future climate change, land use, invasive species, altered fire cycles, human systems, and the interactions among these factors will affect ecosystems and the services they provide to human communities. The goals of this group are to (1) identify science needs and provide tools to assist land managers in addressing these needs, (2) provide a Web site where users can access information pertinent to this region, and (3) provide managers technical assistance when needed. Answers to the team's working science questions are intended to address how interactions among climate change, land use, and management practices may affect key aspects of water availability, ecosystem changes, and societal needs within the UCRB.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Population genetic structure and phylogeographical pattern of rice grasshopper, Oxya hyla intricata, across Southeast Asia.

PubMed

Li, Tao; Zhang, Min; Qu, Yanhua; Ren, Zhumei; Zhang, Jianzhen; Guo, Yaping; Heong, K L; Villareal, Bong; Zhong, Yang; Ma, Enbo

2011-04-01

The rice grasshopper, Oxya hyla intricata, is a rice pest in Southeast Asia. In this study, population genetic diversity and structure of this Oxya species was examined using both DNA sequences and AFLP technology. The samples of 12 populations were collected from four Southeast Asian countries, among which 175 individuals were analysed using mitochondrial DNA cytochrome c oxidase subunit I (COI) sequences, and 232 individuals were examined using amplified fragment length polymorphisms (AFLP) to test whether the phylogeographical pattern and population genetics of this species are related to past geological events and/or climatic oscillations. No obvious trend of genetic diversity was found along a latitude/longitude gradient among different geographical groups. Phylogenetic analysis indicated three deep monophyletic clades that approximately correspond to three geographical regions separated by high mountains and a deep strait, and TCS analysis also revealed three disconnected networks, suggesting that spatial and temporal separations by vicariance, which were also supported by AMOVA as a source of the molecular variance presented among groups. Gene flow analysis showed that there had been frequent historical gene flow among local populations in different regions, but the networks exhibited no shared haplotype among populations. In conclusion, the past geological events and climatic fluctuations are the most important factor on the phylogeographical structure and genetic patterns of O. hyla intricata in Southeast Asia. Habitat, vegetation, and anthropogenic effect may also contribute to gene flow and introgression of this species. Moreover, temperature, abundant rainfall and a diversity of graminaceous species are beneficial for the migration of O. hyla intricata. High haplotype diversity, deep phylogenetic division, negative Fu's F (s) values and unimodal and multimodal distribution shapes all suggest a complicated demographic expansion pattern of these O. hyla intricata populations, which might have been caused by climatic oscillations during glacial periods in the Quaternary.

Analysis of surface-water data network in Kansas for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Medina, K.D.; Tasker, Gary D.

1985-01-01

The surface water data network in Kansas was analyzed using generalized least squares regression for its effectiveness in providing regional streamflow information. The correlation and time-sampling error of the streamflow characteristic are considered in the generalized least squares method. Unregulated medium-flow, low-flow and high-flow characteristics were selected to be representative of the regional information that can be obtained from streamflow gaging station records for use in evaluating the effectiveness of continuing the present network stations, discontinuing some stations; and/or adding new stations. The analysis used streamflow records for all currently operated stations that were not affected by regulation and discontinued stations for which unregulated flow characteristics , as well as physical and climatic characteristics, were available. The state was divided into three network areas, western, northeastern, and southeastern Kansas, and analysis was made for three streamflow characteristics in each area, using three planning horizons. The analysis showed that the maximum reduction of sampling mean square error for each cost level could be obtained by adding new stations and discontinuing some of the present network stations. Large reductions in sampling mean square error for low-flow information could be accomplished in all three network areas, with western Kansas having the most dramatic reduction. The addition of new stations would be most beneficial for man- flow information in western Kansas, and to lesser degrees in the other two areas. The reduction of sampling mean square error for high-flow information would benefit most from the addition of new stations in western Kansas, and the effect diminishes to lesser degrees in the other two areas. Southeastern Kansas showed the smallest error reduction in high-flow information. A comparison among all three network areas indicated that funding resources could be most effectively used by discontinuing more stations in northeastern and southeastern Kansas and establishing more new stations in western Kansas. (Author 's abstract)

Automated extraction of natural drainage density patterns for the conterminous United States through high performance computing

USGS Publications Warehouse

Stanislawski, Larry V.; Falgout, Jeff T.; Buttenfield, Barbara P.

2015-01-01

Hydrographic networks form an important data foundation for cartographic base mapping and for hydrologic analysis. Drainage density patterns for these networks can be derived to characterize local landscape, bedrock and climate conditions, and further inform hydrologic and geomorphological analysis by indicating areas where too few headwater channels have been extracted. But natural drainage density patterns are not consistently available in existing hydrographic data for the United States because compilation and capture criteria historically varied, along with climate, during the period of data collection over the various terrain types throughout the country. This paper demonstrates an automated workflow that is being tested in a high-performance computing environment by the U.S. Geological Survey (USGS) to map natural drainage density patterns at the 1:24,000-scale (24K) for the conterminous United States. Hydrographic network drainage patterns may be extracted from elevation data to guide corrections for existing hydrographic network data. The paper describes three stages in this workflow including data pre-processing, natural channel extraction, and generation of drainage density patterns from extracted channels. The workflow is concurrently implemented by executing procedures on multiple subbasin watersheds within the U.S. National Hydrography Dataset (NHD). Pre-processing defines parameters that are needed for the extraction process. Extraction proceeds in standard fashion: filling sinks, developing flow direction and weighted flow accumulation rasters. Drainage channels with assigned Strahler stream order are extracted within a subbasin and simplified. Drainage density patterns are then estimated with 100-meter resolution and subsequently smoothed with a low-pass filter. The extraction process is found to be of better quality in higher slope terrains. Concurrent processing through the high performance computing environment is shown to facilitate and refine the choice of drainage density extraction parameters and more readily improve extraction procedures than conventional processing.

Statistical assessment on a combined analysis of GRYN-ROMN-UCBN upland vegetation vital signs

USGS Publications Warehouse

Irvine, Kathryn M.; Rodhouse, Thomas J.

2014-01-01

As of 2013, Rocky Mountain and Upper Columbia Basin Inventory and Monitoring Networks have multiple years of vegetation data and Greater Yellowstone Network has three years of vegetation data and monitoring is ongoing in all three networks. Our primary objective is to assess whether a combined analysis of these data aimed at exploring correlations with climate and weather data is feasible. We summarize the core survey design elements across protocols and point out the major statistical challenges for a combined analysis at present. The dissimilarity in response designs between ROMN and UCBN-GRYN network protocols presents a statistical challenge that has not been resolved yet. However, the UCBN and GRYN data are compatible as they implement a similar response design; therefore, a combined analysis is feasible and will be pursued in future. When data collected by different networks are combined, the survey design describing the merged dataset is (likely) a complex survey design. A complex survey design is the result of combining datasets from different sampling designs. A complex survey design is characterized by unequal probability sampling, varying stratification, and clustering (see Lohr 2010 Chapter 7 for general overview). Statistical analysis of complex survey data requires modifications to standard methods, one of which is to include survey design weights within a statistical model. We focus on this issue for a combined analysis of upland vegetation from these networks, leaving other topics for future research. We conduct a simulation study on the possible effects of equal versus unequal probability selection of points on parameter estimates of temporal trend using available packages within the R statistical computing package. We find that, as written, using lmer or lm for trend detection in a continuous response and clm and clmm for visually estimated cover classes with “raw” GRTS design weights specified for the weight argument leads to substantially different results and/or computational instability. However, when only fixed effects are of interest, the survey package (svyglm and svyolr) may be suitable for a model-assisted analysis for trend. We provide possible directions for future research into combined analysis for ordinal and continuous vital sign indictors.

A Planning Guide for Instructional Networks, Part II.

ERIC Educational Resources Information Center

Daly, Kevin F.

1994-01-01

This second in a series of articles on planning for instructional computer networks focuses on site preparation, installation, service, and support. Highlights include an implementation schedule; classroom and computer lab layouts; electrical power needs; workstations; network cable; telephones; furniture; climate control; and security. (LRW)

Mapping Climate Science Information Needs and Networks in the Northwest, USA through Evaluating the Northwest Climate Science Center Climate Science Digest

NASA Astrophysics Data System (ADS)

Gergel, D. R.; Watts, L. H.; Salathe, E. P.; Mankowski, J. D.

2017-12-01

Climate science, already a highly interdisciplinary field, is rapidly evolving, and natural resource managers are increasingly involved in policymaking and adaptation decisions to address climate change that need to be informed by state-of-the-art climate science. Consequently, there is a strong demand for unique organizations that engender collaboration and cooperation between government, non-profit, academic and for-profit sectors that are addressing issues relating to natural resources management and climate adaptation and resilience. These organizations are often referred to as boundary organizations. The Northwest Climate Science Center (NW CSC) and the North Pacific Landscape Conservation Cooperative (NP LCC) are two such boundary organizations operating in different contexts. Together, the NW CSC and the NP LCC fulfill the need for sites of co-production between researchers and managers working on climate-related issues, and a key component of this work is a monthly climate science newsletter that includes recent climate science journal articles, reports, and climate-related events. Our study evaluates the effectiveness of the climate science digest (CSD) through a three-pronged approach: a) in-depth interviews with natural resource managers who use the CSD, b) poll questions distributed to CSD subscribers, and c) quantitative analysis of CSD effectiveness using analytics from MailChimp distribution. We aim to a) map the reach of the CSD across the Northwest and at a national level; b) understand the efficacy of the CSD at communicating climate science to diverse audiences; c) evaluate the usefulness of CSD content for diverse constituencies of subscribers; d) glean transferrable knowledge for future evaluations of boundary management tools; and e) establish a protocol for designing climate science newsletters for other agencies disseminating climate science information. We will present results from all three steps of our evaluation process and describe their implications for future evaluations of climate science communications products and other boundary management tools in the field of natural resources management.

Estimating missing hourly climatic data using artificial neural network for energy balance based ET mapping applications

USDA-ARS?s Scientific Manuscript database

Remote sensing based evapotranspiration (ET) mapping is an important improvement for water resources management. Hourly climatic data and reference ET are crucial for implementing remote sensing based ET models such as METRIC and SEBAL. In Turkey, data on all climatic variables may not be available ...

Compilation of climate data from heterogeneous networks across the Hawaiian Islands

Treesearch

Ryan J. Longman; Thomas W. Giambelluca; Michael A. Nullet; Abby G. Frazier; Kevin Kodama; Shelley D. Crausbay; Paul D. Krushelnycky; Susan Cordell; Martyn P. Clark; Andy J. Newman; Jeffrey R. Arnold

2018-01-01

Long-term, accurate observations of atmospheric phenomena are essential for a myriad of applications, including historic and future climate assessments, resource management, and infrastructure planning. In Hawai‘i, climate data are available from individual researchers, local, State, and Federal agencies, and from large electronic repositories such as the National...

Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets

USDA-ARS?s Scientific Manuscript database

Precipitation and temperature are two primary drivers that significantly affect hydrologic processes in a watershed. A network of land-based National Climatic Data Center (NCDC) weather stations has been typically used as a primary source of climate input for agro-ecosystem models. However, the ne...

Climateurope: a network to support Europe's research and innovation activities in the fields of Earth-System modeling and climate services

NASA Astrophysics Data System (ADS)

Bessembinder, Janette; Kotova, Lola; Manez, Maria; Jacob, Daniela; Hewitt, Chris; Garrett, Natalie; Monfray, Patrick; Doescher, Ralf; Doblas Reyes, Francisco; Joussaume, Sylvie; Toumi, Ralf; Buonocore, Mauro; Gualdi, Silvio; Nickovic, Slobodan

2017-04-01

Changes in the climate are affecting many sectors but the audience of decision- and policy-makers is so wide and varied that the requirements from each application can be quite different. There are a growing number of initiatives at the international and European level, from research networks of data providers, operational services, impact assessments, to coordination of government initiatives and provision of policy relevant recommendations; all provided on a wide range of timescales. The landscape of activities is very diverse. Users and providers of climate information currently face significant challenges in understanding this complex landscape. If we are to maximize the benefits of the investments and provide European citizens with the information and technology to develop a climate-smart society, then a mechanism is needed to coordinate the impressive and varied research and innovation effort. The overall concept behind the EU-project Climateurope is to create and manage a framework to coordinate, integrate and support Europe's research and innovation activities in the fields of Earth-System modeling and climate services. The purpose of this concept is to create greater social and economic value for Europe through improved preparation for, and management of, climate-related risks and opportunities arising from making European world-class knowledge more useable and thus more applicable to policy- and decision-making. This value will be felt by a range of actors including the public sector, governments, business and industry. Climateurope will provide a comprehensive overview of all the relevant activities to ensure the society at large can take full advantage of the investment Europe is making in research and innovation and associated development of services. The Climateurope network will facilitate dialog among climate science communities, funding bodies, climate service providers and users. Through the communication and dissemination activities, Climateurope will establish multidisciplinary expert groups to access the state-of-the-art of Earth system modeling and climate services and will identify existing gaps, new challenges and emerging needs. During this presentation the activities and progress of the project (website, webinars, discussion platform, festivals, state-of-the-art report) will be presented shortly and we will indicate how interested people can join the network.

Envisioning the future of wildlife in a changing climate: Collaborative learning for adaptation planning

USGS Publications Warehouse

LeDee, Olivia E.; Karasov, W.H.; Martin, Karl J.; Meyer, Michael W.; Ribic, Christine; Van Deelen, Timothy R.

2011-01-01

Natural resource managers are tasked with assessing the impacts of climate change on conservation targets and developing adaptation strategies to meet agency goals. The complex, transboundary nature of climate change demands the collaboration of scientists, managers, and stakeholders in this effort. To share, integrate, and apply knowledge from these diverse perspectives, we must engage in social learning. In 2009, we initiated a process to engage university researchers and agency scientists and managers in collaborative learning to assess the impacts of climate change on terrestrial fauna in the state of Wisconsin, USA. We constructed conceptual Bayesian networks to depict the influence of climate change, key biotic and abiotic factors, and existing stressors on the distribution and abundance of 3 species: greater prairie-chicken (Tympanuchus cupido), wood frog (Lithobates sylvaticus), and Karner blue butterfly (Plebejus melissa samuelis). For each species, we completed a 2-stage expert review that elicited dialogue on information gaps, management opportunities, and research priorities. From our experience, collaborative network modeling proved to be a powerful tool to develop a common vision of the potential impacts of climate change on conservation targets.

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2015-01-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. These relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño-Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.

Northern protected areas will become important refuges for biodiversity tracking suitable climates.

PubMed

Berteaux, Dominique; Ricard, Marylène; St-Laurent, Martin-Hugues; Casajus, Nicolas; Périé, Catherine; Beauregard, Frieda; de Blois, Sylvie

2018-03-15

The Northern Biodiversity Paradox predicts that, despite its globally negative effects on biodiversity, climate change will increase biodiversity in northern regions where many species are limited by low temperatures. We assessed the potential impacts of climate change on the biodiversity of a northern network of 1,749 protected areas spread over >600,000 km 2 in Quebec, Canada. Using ecological niche modeling, we calculated potential changes in the probability of occurrence of 529 species to evaluate the potential impacts of climate change on (1) species gain, loss, turnover, and richness in protected areas, (2) representativity of protected areas, and (3) extent of species ranges located in protected areas. We predict a major species turnover over time, with 49% of total protected land area potentially experiencing a species turnover >80%. We also predict increases in regional species richness, representativity of protected areas, and species protection provided by protected areas. Although we did not model the likelihood of species colonising habitats that become suitable as a result of climate change, northern protected areas should ultimately become important refuges for species tracking climate northward. This is the first study to examine in such details the potential effects of climate change on a northern protected area network.

On the data-driven inference of modulatory networks in climate science: An application to West African rainfall

DOE PAGES

Gonzalez, II, D. L.; Angus, M. P.; Tetteh, I. K.; ...

2015-01-13

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression,more » and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.« less

Foundations of data-intensive science: Technology and practice for high throughput, widely distributed, data management and analysis systems

NASA Astrophysics Data System (ADS)

Johnston, William; Ernst, M.; Dart, E.; Tierney, B.

2014-04-01

Today's large-scale science projects involve world-wide collaborations depend on moving massive amounts of data from an instrument to potentially thousands of computing and storage systems at hundreds of collaborating institutions to accomplish their science. This is true for ATLAS and CMS at the LHC, and it is true for the climate sciences, Belle-II at the KEK collider, genome sciences, the SKA radio telescope, and ITER, the international fusion energy experiment. DOE's Office of Science has been collecting science discipline and instrument requirements for network based data management and analysis for more than a decade. As a result of this certain key issues are seen across essentially all science disciplines that rely on the network for significant data transfer, even if the data quantities are modest compared to projects like the LHC experiments. These issues are what this talk will address; to wit: 1. Optical signal transport advances enabling 100 Gb/s circuits that span the globe on optical fiber with each carrying 100 such channels; 2. Network router and switch requirements to support high-speed international data transfer; 3. Data transport (TCP is still the norm) requirements to support high-speed international data transfer (e.g. error-free transmission); 4. Network monitoring and testing techniques and infrastructure to maintain the required error-free operation of the many R&E networks involved in international collaborations; 5. Operating system evolution to support very high-speed network I/O; 6. New network architectures and services in the LAN (campus) and WAN networks to support data-intensive science; 7. Data movement and management techniques and software that can maximize the throughput on the network connections between distributed data handling systems, and; 8. New approaches to widely distributed workflow systems that can support the data movement and analysis required by the science. All of these areas must be addressed to enable large-scale, widely distributed data analysis systems, and the experience of the LHC can be applied to other scientific disciplines. In particular, specific analogies to the SKA will be cited in the talk.

Measurement of agricultural parameters using wireless sensor network (WSN)

NASA Astrophysics Data System (ADS)

Guaña-Moya, Javier; Sánchez-Almeida, Tarquino; Salgado-Reyes, Nelson

2018-04-01

The technological advances have allowed to create new applications in telecommunications, applying low power and reduced costs in their equipment, thus achieving the evolution of new wireless networks or also denominated Wireless Sensor Network. These technologies allow the generation of measurements and analysis of environmental parameter data and soil. Precision agriculture requires parameters for the improvement of production, obtained through WSN technologies. This research analyzes the climatic requirements and soil parameters in a rose plantation in a greenhouse at an altitude of 3,100 meters above sea level. In the present investigation, maximum parameters were obtained in the production of roses, which are in the optimum range of production, whereas the minimum parameters of temperature, humidity and luminosity, evidenced that these parameters can damage the plants, since temperatures less than 10 °C slow down the growth of the plant and allow the proliferation of diseases and fungi.

Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

USGS Publications Warehouse

Elliott, Caroline M.; Jacobson, Robert B.; Freeman, Mary C.

2014-01-01

A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth. On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition. The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.

The Tribal Lands Collaboratory: Building partnerships and developing tools to support local Tribal community response to climate change.

NASA Astrophysics Data System (ADS)

Jones, K. D.; Wee, B.; Kuslikis, A.

2015-12-01

Response of Tribal nations and Tribal communities to current and emerging climate change challenges requires active participation of stakeholders who have effective access to relevant data, information and analytical tools. The Tribal Lands Collaboratory (TLC), currently under development, is a joint effort between the American Indian Higher Education Consortium (AIHEC), the Environmental Systems Research Institute (Esri), and the National Ecological Observatory Network (NEON). The vision of the TLC is to create an integrative platform that enables coordination between multiple stakeholders (e.g. Tribal resource managers, Tribal College faculty and students, farmers, ranchers, and other local community members) to collaborate on locally relevant climate change issues. The TLC is intended to facilitate the transformation of data into actionable information that can inform local climate response planning. The TLC will provide the technical mechanisms to access, collect and analyze data from both internal and external sources (e.g. NASA's Giovanni climate data portal, Ameriflux or USA National Phenology Network) while also providing the social scaffolds to enable collaboration across Tribal communities and with members of the national climate change research community. The prototype project focuses on phenology, a branch of science focused on relationships between climate and the seasonal timing of biological phenomena. Monitoring changes in the timing and duration of phenological stages in plant and animal co­­­­mmunities on Tribal lands can provide insight to the direct impacts of climate change on culturally and economically significant Tribal resources . The project will leverage existing phenological observation protocols created by the USA-National Phenology Network and NEON to direct data collection efforts and will be tailored to the specific needs and concerns of the community. Phenology observations will be captured and managed within the Collaboratory environment where these data may then be correlated with regional climate data to investigate interactions between large-scale environmental changes and local impacts. Esri's Story Maps is a candidate mechanism for sharing of those findings among Tribal stakeholders.

Climate change communication through networks and partnerships: A successful model of engaging and educating non-specialist audience in India

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.

A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

NASA Astrophysics Data System (ADS)

Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

2017-04-01

Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.

Geocode of River Networks in Global Plateaus

NASA Astrophysics Data System (ADS)

Ni, J.; Wang, Y.; Wang, T.

2017-12-01

As typical hierarchical systems, river networks are of great significance to aquatic organisms and its diversity. Different aspects of river networks have been investigated in previous studies such as network structure, formation cause, material transport, nutrient cycle and habitat variation. Nevertheless, river networks function as biological habitat is far from satisfactory in plateau areas. This paper presents a hierarchical method for habitat characterization of plateau river networks with the geocode extracted from abiotic factors including historical geologic period, climate zone, water source and geomorphic process at different spatial scales. As results, characteristics of biological response with vertical differentiation within typical plateau river networks are elucidated. Altitude, climate and landform are of great influence to habitat and thereby structure of aquatic community, while diverse water source and exogenic action would influence biological abundance or spatiotemporal distribution. Case studies are made in the main stream of the Yellow River and the Yangtze River, respectively extended to the river source to Qinghai-Tibet Plateau, which demonstrate high potentials for decision making support to river protection, ecological rehabilitation and sustainable management of river ecosystems.

Delta-Flux: An eddy covariance network for a climate-smart Lower Mississippi Basin

USGS Publications Warehouse

Runkle, Benjamin R. K.; Rigby, James R.; Reba, Michele L.; Anapalli, Saseendran S.; Bhattacharjee, Joydeep; Krauss, Ken W.; Liang, Lu; Locke, Martin A.; Novick, Kimberly A.; Sui, Ruixiu; Suvočarev, Kosana; White, Paul M.

2017-01-01

Networks of remotely monitored research sites are increasingly the tool used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and AmeriFlux lack contributions from the Lower Mississippi River Basin (LMRB), a highly productive agricultural area with opportunities for soil carbon sequestration through conservation practices. The authors describe the rationale to create the new Delta-Flux network, which will coordinate efforts to quantify carbon and water budgets at seventeen eddy covariance flux tower sites in the LMRB. The network structure will facilitate climate-smart management strategies based on production-scale and continuous measurements of carbon and water fluxes from the landscape to the atmosphere under different soil and water management conditions. The seventeen instrumented field sites are expected to monitor fluxes within the most characteristic landscapes of the target area: row-crop fields, pasture, grasslands, forests, and marshes. The network participants are committed to open collaboration and efficient regionalization of site-level findings to support sustainable agricultural and forestry management and conservation of natural resources.

The Swedish Regional Climate Modelling Programme, SWECLIM: a review.

PubMed

Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael

2004-06-01

The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.

Evaluation of temperature differences for paired stations of the U.S. Climate Reference Network

USGS Publications Warehouse

Gallo, K.P.

2005-01-01

Adjustments to data observed at pairs of climate stations have been recommended to remove the biases introduced by differences between the stations in time of observation, temperature instrumentatios, latitude, and elevation. A new network of climate stations, located in rural settings, permits comparisons of temperatures for several pairs of stations without two of the biases (time of observation and instrurtientation). The daily, monthly, and annual minimum, maximum, and mean temperatures were compared for five pairs of stations included in the U.S. Climate Reference Network. Significant differences were found between the paired stations in the annual minimum, maximum, and mean temperatures for all five pairs of stations. Adjustments for latitude and elevation differences contributed to greater differences in mean annual temperature for four of the five stations. Lapse rates computed from the mean annual temperature differences between station pairs differed from a constant value, whether or not latitude adjustments were made to the data. The results suggest that microclimate influences on temperatures observed at nearby (horizontally and vertically) stations are potentially much greater than influences that might be due to latitude or elevation differences between the stations. ?? 2005 American Meteorological Society.

Prediction of River Flooding using Geospatial and Statistical Analysis in New York, USA and Kent, UK

NASA Astrophysics Data System (ADS)

Marsellos, A.; Tsakiri, K.; Smith, M.

2014-12-01

Flooding in the rivers normally occurs during periods of excessive precipitation (i.e. New York, USA; Kent, UK) or ice jams during the winter period (New York, USA). For the prediction and mapping of the river flooding, it is necessary to evaluate the spatial distribution of the water (volume) in the river as well as study the interaction between the climatic and hydrological variables. Two study areas have been analyzed; one in Mohawk River, New York and one in Kent, United Kingdom (UK). A high resolution Digital Elevation Model (DEM) of the Mohawk River, New York has been used for a GIS flooding simulation to determine the maximum elevation value of the water that cannot continue to be restricted in the trunk stream and as a result flooding in the river may be triggered. The Flooding Trigger Level (FTL) is determined by incremental volumetric and surface calculations from Triangulated Irregular Network (TIN) with the use of GIS software and LiDAR data. The prediction of flooding in the river can also be improved by the statistical analysis of the hydrological and climatic variables in Mohawk River and Kent, UK. A methodology of time series analysis has been applied for the decomposition of the hydrological (water flow and ground water data) and climatic data in both locations. The KZ (Kolmogorov-Zurbenko) filter is used for the decomposition of the time series into the long, seasonal, and short term components. The explanation of the long term component of the water flow using the climatic variables has been improved up to 90% for both locations. Similar analysis has been performed for the prediction of the seasonal and short term component. This methodology can be applied for flooding of the rivers in multiple sites.

Long-term forecasting of meteorological time series using Nonlinear Canonical Correlation Analysis (NLCCA)

NASA Astrophysics Data System (ADS)

Woldesellasse, H. T.; Marpu, P. R.; Ouarda, T.

2016-12-01

Wind is one of the crucial renewable energy sources which is expected to bring solutions to the challenges of clean energy and the global issue of climate change. A number of linear and nonlinear multivariate techniques has been used to predict the stochastic character of wind speed. A wind forecast with good accuracy has a positive impact on the reduction of electricity system cost and is essential for the effective grid management. Over the past years, few studies have been done on the assessment of teleconnections and its possible effects on the long-term wind speed variability in the UAE region. In this study Nonlinear Canonical Correlation Analysis (NLCCA) method is applied to study the relationship between global climate oscillation indices and meteorological variables, with a major emphasis on wind speed and wind direction, of Abu Dhabi, UAE. The wind dataset was obtained from six ground stations. The first mode of NLCCA is capable of capturing the nonlinear mode of the climate indices at different seasons, showing the symmetry between the warm states and the cool states. The strength of the nonlinear canonical correlation between the two sets of variables varies with the lead/lag time. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE) and Mean absolute error (MAE). The results indicated that NLCCA models provide more accurate information about the nonlinear intrinsic behaviour of the dataset of variables than linear CCA model in terms of the correlation and root mean square error. Key words: Nonlinear Canonical Correlation Analysis (NLCCA), Canonical Correlation Analysis, Neural Network, Climate Indices, wind speed, wind direction

Quantifying Hydro-biogeochemical Model Sensitivity in Assessment of Climate Change Effect on Hyporheic Zone Processes

NASA Astrophysics Data System (ADS)

Song, X.; Chen, X.; Dai, H.; Hammond, G. E.; Song, H. S.; Stegen, J.

2016-12-01

The hyporheic zone is an active region for biogeochemical processes such as carbon and nitrogen cycling, where the groundwater and surface water mix and interact with each other with distinct biogeochemical and thermal properties. The biogeochemical dynamics within the hyporheic zone are driven by both river water and groundwater hydraulic dynamics, which are directly affected by climate change scenarios. Besides that, the hydraulic and thermal properties of local sediments and microbial and chemical processes also play important roles in biogeochemical dynamics. Thus for a comprehensive understanding of the biogeochemical processes in the hyporheic zone, a coupled thermo-hydro-biogeochemical model is needed. As multiple uncertainty sources are involved in the integrated model, it is important to identify its key modules/parameters through sensitivity analysis. In this study, we develop a 2D cross-section model in the hyporheic zone at the DOE Hanford site adjacent to Columbia River and use this model to quantify module and parametric sensitivity on assessment of climate change. To achieve this purpose, We 1) develop a facies-based groundwater flow and heat transfer model that incorporates facies geometry and heterogeneity characterized from a field data set, 2) derive multiple reaction networks/pathways from batch experiments with in-situ samples and integrate temperate dependent reactive transport modules to the flow model, 3) assign multiple climate change scenarios to the coupled model by analyzing historical river stage data, 4) apply a variance-based global sensitivity analysis to quantify scenario/module/parameter uncertainty in hierarchy level. The objectives of the research include: 1) identifing the key control factors of the coupled thermo-hydro-biogeochemical model in the assessment of climate change, and 2) quantify the carbon consumption in different climate change scenarios in the hyporheic zone.

A probabilistic method for streamflow projection and associated uncertainty analysis in a data sparse alpine region

NASA Astrophysics Data System (ADS)

Ren, Weiwei; Yang, Tao; Shi, Pengfei; Xu, Chong-yu; Zhang, Ke; Zhou, Xudong; Shao, Quanxi; Ciais, Philippe

2018-06-01

Climate change imposes profound influence on regional hydrological cycle and water security in many alpine regions worldwide. Investigating regional climate impacts using watershed scale hydrological models requires a large number of input data such as topography, meteorological and hydrological data. However, data scarcity in alpine regions seriously restricts evaluation of climate change impacts on water cycle using conventional approaches based on global or regional climate models, statistical downscaling methods and hydrological models. Therefore, this study is dedicated to development of a probabilistic model to replace the conventional approaches for streamflow projection. The probabilistic model was built upon an advanced Bayesian Neural Network (BNN) approach directly fed by the large-scale climate predictor variables and tested in a typical data sparse alpine region, the Kaidu River basin in Central Asia. Results show that BNN model performs better than the general methods across a number of statistical measures. The BNN method with flexible model structures by active indicator functions, which reduce the dependence on the initial specification for the input variables and the number of hidden units, can work well in a data limited region. Moreover, it can provide more reliable streamflow projections with a robust generalization ability. Forced by the latest bias-corrected GCM scenarios, streamflow projections for the 21st century under three RCP emission pathways were constructed and analyzed. Briefly, the proposed probabilistic projection approach could improve runoff predictive ability over conventional methods and provide better support to water resources planning and management under data limited conditions as well as enable a facilitated climate change impact analysis on runoff and water resources in alpine regions worldwide.

Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey

2017-06-01

Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.