The Bern Simple Climate Model (BernSCM) v1.0: an extensible and fully documented open-source re-implementation of the Bern reduced-form model for global carbon cycle-climate simulations

NASA Astrophysics Data System (ADS)

Strassmann, Kuno M.; Joos, Fortunat

2018-05-01

The Bern Simple Climate Model (BernSCM) is a free open-source re-implementation of a reduced-form carbon cycle-climate model which has been used widely in previous scientific work and IPCC assessments. BernSCM represents the carbon cycle and climate system with a small set of equations for the heat and carbon budget, the parametrization of major nonlinearities, and the substitution of complex component systems with impulse response functions (IRFs). The IRF approach allows cost-efficient yet accurate substitution of detailed parent models of climate system components with near-linear behavior. Illustrative simulations of scenarios from previous multimodel studies show that BernSCM is broadly representative of the range of the climate-carbon cycle response simulated by more complex and detailed models. Model code (in Fortran) was written from scratch with transparency and extensibility in mind, and is provided open source. BernSCM makes scientifically sound carbon cycle-climate modeling available for many applications. Supporting up to decadal time steps with high accuracy, it is suitable for studies with high computational load and for coupling with integrated assessment models (IAMs), for example. Further applications include climate risk assessment in a business, public, or educational context and the estimation of CO2 and climate benefits of emission mitigation options.

Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany

NASA Astrophysics Data System (ADS)

Agarwal, Ankit; Marwan, Norbert; Rathinasamy, Maheswaran; Oeztuerk, Ugur; Merz, Bruno; Kurths, Jürgen

2017-04-01

Understanding of the climate sytems has been of tremendous importance to different branches such as agriculture, flood, drought and water resources management etc. In this regard, complex networks analysis and time series analysis attracted considerable attention, owing to their potential role in understanding the climate system through characteristic properties. One of the basic requirements in studying climate network dynamics is to identify connections in space or time or space-time, depending upon the purpose. Although a wide variety of approaches have been developed and applied to identify and analyse spatio-temporal relationships by climate networks, there is still further need for improvements in particular when considering precipitation time series or interactions on different scales. In this regard, recent developments in the area of network theory, especially complex networks, offer new avenues, both for their generality about systems and for their holistic perspective about spatio-temporal relationships. The present study has made an attempt to apply the ideas developed in the field of complex networks to examine connections in regional climate networks with particular focus on multiscale spatiotemporal connections. This paper proposes a novel multiscale understanding of regional climate networks using wavelets. The proposed approach is applied to daily precipitation records observed at 543 selected stations from south Germany for a period of 110 years (1901-2010). Further, multiscale community mining is performed on the same study region to shed more light on the underlying processes at different time scales. Various network measure and tools so far employed provide micro-level (individual station) and macro-level (community structure) information of the network. It is interesting to investigate how the result of this study can be useful for future climate predictions and for evaluating climate models on their implementation regarding heavy precipitation. Keywords: Complex network, event synchronization, wavelet, regional climate network, multiscale community mining

Linking Student Achievement and Teacher Science Content Knowledge about Climate Change: Ensuring the Nations 3 Million Teachers Understand the Science through an Electronic Professional Development System

NASA Astrophysics Data System (ADS)

Niepold, F.; Byers, A.

2009-12-01

The scientific complexities of global climate change, with wide-ranging economic and social significance, create an intellectual challenge that mandates greater public understanding of climate change research and the concurrent ability to make informed decisions. The critical need for an engaged, science literate public has been repeatedly emphasized by multi-disciplinary entities like the Intergovernmental Panel on Climate Change (IPCC), the National Academies (Rising Above the Gathering Storm report), and the interagency group responsible for the recently updated Climate Literacy: The Essential Principles of Climate Science. There is a clear need for an American public that is climate literate and for K-12 teachers confident in teaching relevant science content. A key goal in the creation of a climate literate society is to enhance teachers’ knowledge of global climate change through a national, scalable, and sustainable professional development system, using compelling climate science data and resources to stimulate inquiry-based student interest in science, technology, engineering, and mathematics (STEM). This session will explore innovative e-learning technologies to address the limitations of one-time, face-to-face workshops, thereby adding significant sustainability and scalability. The resources developed will help teachers sift through the vast volume of global climate change information and provide research-based, high-quality science content and pedagogical information to help teachers effectively teach their students about the complex issues surrounding global climate change. The Learning Center is NSTA's e-professional development portal to help the nations teachers and informal educators learn about the scientific complexities of global climate change through research-based techniques and is proven to significantly improve teacher science content knowledge.

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

NASA Technical Reports Server (NTRS)

Thiele, O. (Editor); Schiffer, R. A. (Editor)

1985-01-01

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Management of complex dynamical systems

NASA Astrophysics Data System (ADS)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

Service Center for Climate Change Adaptation in Agriculture - an initiative of the University of West Hungary

NASA Astrophysics Data System (ADS)

Matyas, Cs.; Berki, I.; Drüszler, A.; Eredics, A.; Galos, B.; Moricz, N.; Rasztovits, E.

2012-04-01

In whole Central Europe agricultural production is highly vulnerable and sensitive to impacts of projected climatic changes. The low-elevation regions of the Carpathian Basin (most of the territory of Hungary), where precipitation is the minimum factor of production, are especially exposed to climatic extremes, especially to droughts. Rainfed agriculture, animal husbandry on nature-close pastures and nature-close forestry are the most sensitive sectors due to limited possibilities to counterbalance moisture supply constraints. These sectors have to be best prepared to frequency increase of extreme events, disasters and economic losses. So far, there is a lack of information about the middle and long term consequences on regional and local level. Therefore the importance of complex, long term management planning and of land use optimation is increasing. The aim of the initiative is to set up a fine-scale, GIS-based, complex, integrated system for the definition of the most important regional and local challenges and tasks of climate change adaptation and mitigation in agriculture, forestry, animal husbandry and also nature protection. The Service Center for Climate Change Adaptation in Agriculture is planned to provide the following services: § Complex, GIS-supported database, which integrates the basic information about present and projected climates, extremes, hydrology and soil conditions; § Evaluation of existing satellite-based and earth-based monitoring systems; § GIS-supported information about the future trends of climate change impacts on the agroecological potential and sensitivity status on regional and local level (e.g. land cover/use and expectable changes, production, water and carbon cycle, biodiversity and other ecosystem services, potential pests and diseases, tolerance limits etc.) in fine-scale horizontal resolution, based first of all on natural produce, including also social and economic consequences; § Complex decision supporting system on regional and local scale for middle- and long term adaptation and mitigation strategies, providing information on optimum technologies and energy balances. Cooperation with already existing Climate Service Centres and national and international collaboration in monitoring and research are important elements of the activity of the Centre. In the future, the Centre is planned to form part of a national information system on climate change adaptation and mitigation, supported by the Ministry of Development. Keywords: climate change impacts, forestry, rainfed agriculture, animal husbandry

Seeing the future impacts of climate change and forest management: a landscape visualization system for forest managers

Treesearch

Eric J. Gustafson; Melissa Lucash; Johannes Liem; Helen Jenny; Rob Scheller; Kelly Barrett; Brian R. Sturtevant

2016-01-01

Forest managers are increasingly considering how climate change may alter forests' capacity to provide ecosystem goods and services. But identifying potential climate change effects on forests is difficult because interactions among forest growth and mortality, climate change, management, and disturbances are complex and uncertain. Although forest landscape models...

Transitions between multiple equilibria of paleo climate: a glimpse in to the dynamics of abrupt climate change

NASA Astrophysics Data System (ADS)

Ferreira, David; Marshall, John; Ito, Takamitsu; McGee, David; Moreno-Chamarro, Eduardo

2017-04-01

The dynamics regulating large climatic transitions such as glacial-interglacial cycles or DO events remains a puzzle. Forcings behind these transitions are not robustly identified and potential candidates (e.g. Milankovitch cycles, freshwater perturbations) often appear too weak to explain such dramatic transitions. A potential solution to this long-standing puzzle is that Earth's climate is endowed with multiple equilibrium states of global extent. Such states are commonly found in low-order or conceptual climate models, but it is unclear whether a system as complex as Earth's climate can sustain multiple equilibrium states. Here we report that multiple equilibrium states of the climate system are also possible in a complex, fully dynamical coupled ocean-atmosphere-sea ice GCM with idealized Earth-like geometry, resolved weather systems and a hydrological cycle. In our model, two equilibrium states coexist for the same parameters and external forcings: a Warm climate with a small Northern hemisphere sea ice cap and a large southern one and a Cold climate with large ice caps at both poles. The dynamical states of the Warm and Cold solutions exhibit striking similarities with our present-day climate and the climate of the Last Glacial Maximum, respectively. A carbon cycle model driven by the two dynamical states produces an atmospheric pCO2 draw-down of about 110 pm between the Warm and Cold states, close to Glacial-Interglacial differences found in ice cores. Mechanism controlling the existence of the multiple states and changes in the atmospheric CO2 will be briefly presented. Finally we willdescribe transition experiments from the Cold to the Warm state, focusing on the lead-lags in the system, notably between the Northern and Southern Hemispheres climates.

Arctic systems in the Quaternary: Ecological collision, faunal mosaics and the consequences of wobbling climate

USDA-ARS?s Scientific Manuscript database

Climate oscillations and episodic or recurrent processes interact with evolution, ecology and biogeography determining the structure and complex mosaic that is the biosphere. Parasites and parasite-host assemblages, within an expansive environmental matrix determined by climate, are key components...

Regional climate projection of the Maritime Continent using the MIT Regional Climate Model

NASA Astrophysics Data System (ADS)

IM, E. S.; Eltahir, E. A. B.

2014-12-01

Given that warming of the climate system is unequivocal (IPCC AR5), accurate assessment of future climate is essential to understand the impact of climate change due to global warming. Modelling the climate change of the Maritime Continent is particularly challenge, showing a high degree of uncertainty. Compared to other regions, model agreement of future projections in response to anthropogenic emission forcings is much less. Furthermore, the spatial and temporal behaviors of climate projections seem to vary significantly due to a complex geographical condition and a wide range of scale interactions. For the fine-scale climate information (27 km) suitable for representing the complexity of climate change over the Maritime Continent, dynamical downscaling is performed using the MIT regional climate model (MRCM) during two thirty-year period for reference (1970-1999) and future (2070-2099) climate. Initial and boundary conditions are provided by Community Earth System Model (CESM) simulations under the emission scenarios projected by MIT Integrated Global System Model (IGSM). Changes in mean climate as well as the frequency and intensity of extreme climate events are investigated at various temporal and spatial scales. Our analysis is primarily centered on the different behavior of changes in convective and large-scale precipitation over land vs. ocean during dry vs. wet season. In addition, we attempt to find the added value to downscaled results over the Maritime Continent through the comparison between MRCM and CESM projection. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

The CLEAN Workshop Series: Promoting Effective Pedagogy for Teaching Undergraduate Climate Science

NASA Astrophysics Data System (ADS)

Kirk, K. B.; Bruckner, M. Z.; Manduca, C. A.; Buhr, S. M.

2012-12-01

To prepare students to understand a changing climate, it is imperative that we equip educators with the best possible tools and methods for reaching their audience. As part of the Climate Literacy and Energy Awareness Network (CLEAN) professional development efforts, two workshops for undergraduate faculty were held in 2012. These workshops used a variety of activities to help faculty learn about recent climate research, take part in demonstrations of successful activities for teaching climate topics, and collaborate to create new teaching materials. The workshops also facilitated professional networking among participants. Both workshops were held online, eliminating the need for travel, encouraging participants without travel funds to attend, and allowing international collaborations and presentations. To create an authentic experience, the workshop used several technologies such as the Blackboard Collaborate web conferencing platform, SERC's web-based collaboration tools and online discussion threads, and conference calls. The workshop Communicating Climate Science in the Classroom, held in April 2012, explored practices for communicating climate science and policy in the classroom and provided strategies to improve student understanding of this complex and sensitive topic. Workshop presentations featured public opinion research on Americans' perceptions of climate change, tactics for identifying and resolving student misconceptions, and methods to address various "backfire effects" that can result from attempts to correct misinformation. Demonstrations of teaching approaches included a role-playing simulation of emissions negotiations, Princeton's climate stabilization wedges game, and an activity that allows students to use scientific principles to tackle misinformation. The workshop Teaching Climate Complexity was held in May 2012. Teaching the complexities of climate science requires an understanding of many facets of the Earth system and a robust pedagogic approach that fosters systems thinking. Workshop participants heard presentations from top climate scientists about topics such as the role of carbon dioxide in regulating Earth's climate, the silicate-weathering thermostat hypothesis, effects of water vapor in the climate system, and albedo effects from the loss of Artic sea ice. Demonstrations of classroom techniques allowed participants to use a jigsaw approach to understand poleward heat transport, plot atmospheric carbon dioxide concentrations, and use a mass balance model to explore the role of carbon dioxide in Earth's atmosphere. A hallmark of the CLEAN workshops is that participants are actively engaged in team projects to create new teaching materials. In the Communicating Climate workshop, John Cook led a demonstration of techniques featured in his Debunking Handbook and workshop participants created examples of how to respond to common climate myths in the classroom. In the Climate Complexities workshop, participants used existing elements within the CLEAN reviewed collection to create a comprehensive sequence of activities that can be used to teach elements of Earth's climate system. Activities from the workshop are archived on the CLEAN website, including screen cast recordings of all the presentations and materials created at each workshop. For more information, visit the workshop website at the URL below.

A Systems Approach to Climate, Water and Diarrhea in Hubli-Dharward, India

NASA Astrophysics Data System (ADS)

Mellor, J. E.; Zimmerman, J.

2014-12-01

Although evidence suggests that climate change will negatively impact water resources and hence diarrheal disease rates in the developing world, there is uncertainty surrounding prior studies. This is due to the complexity of the pathways by which climate impacts diarrhea rates making it difficult to develop interventions. Therefore, our goal was to develop a mechanistic systems approach that incorporates the complex climate, human, engineered and water systems to relate climate change to diarrhea rates under future climate scenarios.To do this, we developed an agent-based model (ABM). Our agents are households and children living in Hubli-Dharward, India. The model was informed with 15 months of weather, water quality, ethnographic and diarrhea incidence data. The model's front end is a stochastic weather simulator incorporating 15 global climate models to simulate rainfall and temperature. The water quality available to agents (residents) on a model "day" is a function of the simulated day's weather and is fully validated with field data. As with the field data, as the ambient temperature increases or it rains, the quality of water available to residents in the model deteriorates. The propensity for an resident to get diarrhea is calculated with an integrated Quantitative Microbial Risk Assessment model with uncertainty simulated with a bootstrap method. Other factors include hand-washing, improved water sources, household water treatment and improved sanitation.The benefits of our approach are as follows: Our mechanistic method allows us to develop scientifically derived adaptation strategies. We can quantitatively link climate scenarios with diarrhea incidence over long time periods. We can explore the complex climate and water system dynamics, rank risk factor importance, examine a broad range of scenarios and identify tipping points. Our approach is modular and expandable such that new datasets can be integrated to study climate impacts on a larger scale. Our results indicate that climate change will have a serious effect on diarrhea incidence in the region. However, adaptation strategies including more reliable water supplies and household water treatment can mitigate these impacts.

Using conceptual maps to assess students' climate change understanding and misconceptions

NASA Astrophysics Data System (ADS)

Gautier, C.

2011-12-01

The complex and interdisciplinary nature of climate change science poses special challenges for educators in helping students understand the climate system, and how it is evolving under natural and anthropogenic forcing. Students and citizens alike have existing mental models that may limit their perception and processing of the multiple relationships between processes (e.g., feedback) that arise in global change science, and prevent adoption of complex scientific concepts. Their prior knowledge base serves as the scaffold for all future learning and grasping its range and limitations serves as an important basis upon which to anchor instruction. Different instructional strategies can be adopted to help students understand the inherently interdisciplinary topic of global climate change, its interwoven human and natural causes, and the connections it has with society through a complex range of political, social, technological and economic factors. One assessment method for students' understanding of global climate change with its many uncertainties, whether associated with the workings of the climate system or with respect to social, cultural and economic processes that mediate human responses to changes within the system, is through the use of conceptual maps. When well designed, they offer a representation of students' mental model prior and post instruction. We will present two conceptual mapping activities used in the classroom to assess students' knowledge and understanding about global climate change and uncover misconceptions. For the first one, concept maps will be used to demonstrate evidence of learning and conceptual change, while for the second we will show how conceptual maps can provide information about gaps in knowledge and misconceptions students have about the topic.

Synchronous Motions Across the Instrumental Climate Record

NASA Astrophysics Data System (ADS)

Carl, Peter

The Earth's climate system bears a rich variety of feedback mechanisms that may give rise to complex, evolving modal structures under internal and external control. Various types of synchronization may be identified in the system's motion when looking at representative time series of the instrumental period through the glasses of an advanced technique of sparse data approximation, the Matching Pursuit (MP) approach. To disentangle the emerging network of oscillatory modes to the degree that climate dynamics turns out to be separable, a large dictionary of "Gaussian logons," i.e. frequency modulated (FM) Gabor atoms, is applied. Though the extracted modes make up linear decompositions, this flexible analyzing signal matches highly nonlinear waveforms. Univariate analyses over the period 1870-1997 are presented of a set of customary time series in annual resolution, comprising global and regional climate, central European synoptic systems, German precipitation, and runoff of the Elbe river near Dresden. All the evidence from this first-generation MP-FM study, obtained in subsequent multivariate syntheses, points to dynamically excited regimes of an organized yet complex climate system under permanent change—perhaps a (pre)chaotic one at centennial timescales, suggesting a "chaos control" perspective on global climate dynamics and change. Findings and conclusions include, among others, internal structure of reconstructed insolation, the episodic nature of global warming as reflected in multidecadal temperature modes, their swarm of "interdomain" companions across the whole system that unveils an unknown regime character of interannual climate dynamics, and the apparent onset early in the 1990s of the present thermal stagnation.

Climate and dengue transmission: evidence and implications.

PubMed

Morin, Cory W; Comrie, Andrew C; Ernst, Kacey

2013-01-01

Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host-species interactions. Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.

Climate Literacy: Supporting Teacher Professional Development

NASA Astrophysics Data System (ADS)

Haddad, N.; Ledley, T. S.; Dunlap, C.; Bardar, E.; Youngman, B.; Ellins, K. K.; McNeal, K. S.; Libarkin, J.

2012-12-01

Confronting the Challenges of Climate Literacy (CCCL) is an NSF-funded (DRK-12) project that includes curriculum development, teacher professional development, teacher leadership development, and research on student learning, all directed at high school teachers and students. The project's evaluation efforts inform and guide all major components of the project. The research effort addresses the question of what interventions are most effective in helping high school students grasp the complexities of the Earth system and climate processes, which occur over a range of spatial and temporal scales. The curriculum unit includes three distinct but related modules: Climate and the Cryosphere; Climate, Weather, and the Biosphere; and Climate and the Carbon Cycle. Climate-related themes that cut across all three modules include the Earth system, with the complexities of its positive and negative feedback loops; the range of temporal and spatial scales at which climate, weather, and other Earth system processes occur; and the recurring question, "How do we know what we know about Earth's past and present climate?" which addresses proxy data and scientific instrumentation. The professional development component of the project includes online science resources to support the teaching of the curriculum modules, summer workshops for high school teachers, and a support system for developing the teacher leaders who plan and implement those summer workshops. When completed, the project will provide a model high school curriculum with online support for implementing teachers and a cadre of leaders who can continue to introduce new teachers to the resource. This presentation will introduce the curriculum and the university partnerships that are key to the project's success, and describe how the project addresses the challenge of helping teachers develop their understanding of climate science and their ability to convey climate-related concepts articulated in the Next Generation Science Standards to their students. We will also describe the professional development and support system to develop teacher leaders and explain some of the challenges that accompany this approach of developing teacher leaders in the area of climate literacy.

A network-base analysis of CMIP5 "historical" experiments

NASA Astrophysics Data System (ADS)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

Collaborative Observation and Research (CORE) Watersheds: new strategies for tracking the regional effects of climate change on complex systems

NASA Astrophysics Data System (ADS)

Murdoch, P. S.

2007-12-01

The past 30 years of environmental research have shown that our world is not made up of discrete components acting independently, but rather of a mosaic of complex relations among air, land, water, living resources, and human activities. Recent warming of the climate is having a significant effect on the functioning of those systems. A national imperative is developing to quickly establish local, regional, and national systems for anticipating environmental degradation from a changing climate and developing cost-effective adaptation or mitigation strategies. In these circumstances, the debate over research versus monitoring becomes moot--there is a clear need for the integrated application of both across a range of temporal and spatial scales. A national framework that effectively addresses the multiple scales and complex multi-disciplinary processes of climate change is being assembled largely from existing programs through collaboration among Federal, State, local, and NGO organizations. The result will be an observation and research network capable of interpreting complex environmental changes at a range of spatial and temporal scales, but at less cost than if the network were funded as an independent initiative. A pilot implementation of the collaborative framework in the Delaware River Basin yielded multi-scale assessments of carbon storage and flux, and the effects of forest fragmentation and soil calcium depletion on ecosystem function. A prototype of a national climate-effects observation and research network linking research watersheds, regional surveys, remote sensing, and ecosystem modeling is being initiated in the Yukon River Basin where carbon flux associated with permafrost thaw could accelerate global warming.

The current evolution of complex high mountain debris-covered glacier systems and its relation with ground ice nature and distribution: the case of Rognes and Pierre Ronde area (Mont-Blanc range, France).

NASA Astrophysics Data System (ADS)

Bosson, Jean-Baptiste; Lambiel, Christophe

2014-05-01

The current climate forcing, through negative glacier mass balance and rockfall intensification, is leading to the rapid burring of many small glacier systems. When the debris mantle exceeds some centimeters of thickness, the climate control on ice melt is mitigated and delayed. As well, debris-covered glaciers respond to climate forcing in a complex way. This situation is emphasised in high mountain environments, where topo-climatic conditions, such as cold temperatures, amount of solid precipitation, duration of snow cover, nebulosity or shadow effect of rockwalls, limit the influence of rising air temperatures in the ground. Beside, due to Holocene climate history, glacier-permafrost interactions are not rare within the periglacial belt. Glacier recurrence may have removed and assimilated former ice-cemented sediments, the negative mass balance may have led to the formation of ice-cored rock glaciers and neopermafrost may have formed recently under cold climate conditions. Hence, in addition to sedimentary ice, high mountain debris-covered glacier systems can contain interstitial magmatic ice. Especially because of their position at the top of alpine cascade systems and of the amount of water and (unconsolidated) sediment involved, it is important to understand and anticipate the evolution of these complex landforms. Due to the continuous and thick debris mantle and to the common existence of dead ice in deglaciated areas, the current extent of debris-covered glacier can be difficult to point out. Thus, the whole system, according to Little Ice Age (LIA) extent, has sometimes to be investigated to understand the current response of glacier systems to the climate warming. In this context, two neighbouring sites, Rognes and Pierre Ronde systems (45°51'38''N, 6°48'40''E; 2600-3100m a.s.l), have been studied since 2011. These sites are almost completely debris-covered and only few ice outcrops in the upper slopes still witness the existence of former glaciers. Electrical resistivity tomographies, kinematic data and ground surface temperature show that heterogeneous responses to climate forcing are occurring despites their small areas (> 0.3 km2). This complex situation is related to Holocene climate history and especially to glacier systems evolution since LIA. The current dynamics depend of ground ice nature and distribution. Five main behaviours can be highlighted: - Debris covered glacier areas are the most active. Their responses to climate forcing are relatively fast, especially through massive ice melt-out each summer. - Ice-cored rock glacier areas are quite active. The existence of massive glacier ice under few meters of debris explain the important surface lowering during the snow free period . - Ice-cemented rock glacier areas are characterised by winter and summer subhorizontal downslope creeping. - Moraine areas containing dead ice have heterogeneous activities (directions and values of detected movements) related to the ice vanishing. - Deglaciated moraine areas are almost inactive, except modest superficial paraglacial rebalancing.

Interpretation of Recent Temperature Trends in California

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

Duffy, P B; Bonfils, C; Lobell, D

2007-09-21

Regional-scale climate change and associated societal impacts result from large-scale (e.g. well-mixed greenhouse gases) and more local (e.g. land-use change) 'forcing' (perturbing) agents. It is essential to understand these forcings and climate responses to them, in order to predict future climate and societal impacts. California is a fine example of the complex effects of multiple climate forcings. The State's natural climate is diverse, highly variable, and strongly influenced by ENSO. Humans are perturbing this complex system through urbanization, irrigation, and emission of multiple types of aerosols and greenhouse gases. Despite better-than-average observational coverage, we are only beginning to understand themore » manifestations of these forcings in California's temperature record.« less

Contrasting model complexity under a changing climate in a headwaters catchment.

NASA Astrophysics Data System (ADS)

Foster, L.; Williams, K. H.; Maxwell, R. M.

2017-12-01

Alpine, snowmelt-dominated catchments are the source of water for more than 1/6th of the world's population. These catchments are topographically complex, leading to steep weather gradients and nonlinear relationships between water and energy fluxes. Recent evidence suggests that alpine systems are more sensitive to climate warming, but these regions are vastly simplified in climate models and operational water management tools due to computational limitations. Simultaneously, point-scale observations are often extrapolated to larger regions where feedbacks can both exacerbate or mitigate locally observed changes. It is critical to determine whether projected climate impacts are robust to different methodologies, including model complexity. Using high performance computing and an integrated model of a representative headwater catchment we determined the hydrologic response from 30 projected climate changes to precipitation, temperature and vegetation for the Rocky Mountains. Simulations were run with 100m and 1km resolution, and with and without lateral subsurface flow in order to vary model complexity. We found that model complexity alters nonlinear relationships between water and energy fluxes. Higher-resolution models predicted larger changes per degree of temperature increase than lower resolution models, suggesting that reductions to snowpack, surface water, and groundwater due to warming may be underestimated in simple models. Increases in temperature were found to have a larger impact on water fluxes and stores than changes in precipitation, corroborating previous research showing that mountain systems are significantly more sensitive to temperature changes than to precipitation changes and that increases in winter precipitation are unlikely to compensate for increased evapotranspiration in a higher energy environment. These numerical experiments help to (1) bracket the range of uncertainty in published literature of climate change impacts on headwater hydrology; (2) characterize the role of precipitation and temperature changes on water supply for snowmelt-dominated downstream basins; and (3) identify which climate impacts depend on the scale of simulation.

Bayesian versus politically motivated reasoning in human perception of climate anomalies

NASA Astrophysics Data System (ADS)

Ripberger, Joseph T.; Jenkins-Smith, Hank C.; Silva, Carol L.; Carlson, Deven E.; Gupta, Kuhika; Carlson, Nina; Dunlap, Riley E.

2017-11-01

In complex systems where humans and nature interact to produce joint outcomes, mitigation, adaptation, and resilience require that humans perceive feedback—signals of health and distress—from natural systems. In many instances, humans readily perceive feedback. In others, feedback is more difficult to perceive, so humans rely on experts, heuristics, biases, and/or identify confirming rationalities that may distort perceptions of feedback. This study explores human perception of feedback from natural systems by testing alternate conceptions about how individuals perceive climate anomalies, a form of feedback from the climate system. Results indicate that individuals generally perceive climate anomalies, especially when the anomalies are relatively extreme and persistent. Moreover, this finding is largely robust to political differences that generate predictable but small biases in feedback perception at extreme ends of the partisan spectrum. The subtlety of these biases bodes well for mitigation, adaptation, and resilience as human systems continue to interact with a changing climate system.

Ocean Hydrodynamics Numerical Model in Curvilinear Coordinates for Simulating Circulation of the Global Ocean and its Separate Basins.

NASA Astrophysics Data System (ADS)

Gusev, Anatoly; Diansky, Nikolay; Zalesny, Vladimir

2010-05-01

The original program complex is proposed for the ocean circulation sigma-model, developed in the Institute of Numerical Mathematics (INM), Russian Academy of Sciences (RAS). The complex can be used in various curvilinear orthogonal coordinate systems. In addition to ocean circulation model, the complex contains a sea ice dynamics and thermodynamics model, as well as the original system of the atmospheric forcing implementation on the basis of both prescribed meteodata and atmospheric model results. This complex can be used as the oceanic block of Earth climate model as well as for solving the scientific and practical problems concerning the World ocean and its separate oceans and seas. The developed program complex can be effectively used on parallel shared memory computational systems and on contemporary personal computers. On the base of the complex proposed the ocean general circulation model (OGCM) was developed. The model is realized in the curvilinear orthogonal coordinate system obtained by the conformal transformation of the standard geographical grid that allowed us to locate the system singularities outside the integration domain. The horizontal resolution of the OGCM is 1 degree on longitude, 0.5 degree on latitude, and it has 40 non-uniform sigma-levels in depth. The model was integrated for 100 years starting from the Levitus January climatology using the realistic atmospheric annual cycle calculated on the base of CORE datasets. The experimental results showed us that the model adequately reproduces the basic characteristics of large-scale World Ocean dynamics, that is in good agreement with both observational data and results of the best climatic OGCMs. This OGCM is used as the oceanic component of the new version of climatic system model (CSM) developed in INM RAS. The latter is now ready for carrying out the new numerical experiments on climate and its change modelling according to IPCC (Intergovernmental Panel on Climate Change) scenarios in the scope of the CMIP-5 (Coupled Model Intercomparison Project). On the base of the complex proposed the Pacific Ocean circulation eddy-resolving model was realized. The integration domain covers the Pacific from Equator to Bering Strait. The model horizontal resolution is 0.125 degree and it has 20 non-uniform sigma-levels in depth. The model adequately reproduces circulation large-scale structure and its variability: Kuroshio meandering, ocean synoptic eddies, frontal zones, etc. Kuroshio high variability is shown. The distribution of contaminant was simulated that is admittedly wasted near Petropavlovsk-Kamchatsky. The results demonstrate contaminant distribution structure and provide us understanding of hydrological fields formation processes in the North-West Pacific.

Visualizing interconnections among climate risks

NASA Astrophysics Data System (ADS)

Tanaka, K.; Yokohata, T.; Nishina, K.; Takahashi, K.; Emori, S.; Kiguchi, M.; Iseri, Y.; Honda, Y.; Okada, M.; Masaki, Y.; Yamamoto, A.; Shigemitsu, M.; Yoshimori, M.; Sueyoshi, T.; Hanasaki, N.; Ito, A.; Sakurai, G.; Iizumi, T.; Nishimori, M.; Lim, W. H.; Miyazaki, C.; Kanae, S.; Oki, T.

2015-12-01

It is now widely recognized that climate change is affecting various sectors of the world. Climate change impact on one sector may spread out to other sectors including those seemingly remote, which we call "interconnections of climate risks". While a number of climate risks have been identified in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), there has been no attempt to explore their interconnections comprehensively. Here we present a first and most exhaustive visualization of climate risks drawn based on a systematic literature survey. Our risk network diagrams depict that changes in the climate system impact natural capitals (terrestrial water, crop, and agricultural land) as well as social infrastructures, influencing the socio-economic system and ultimately our access to food, water, and energy. Our findings suggest the importance of incorporating climate risk interconnections into impact and vulnerability assessments and call into question the widely used damage function approaches, which address a limited number of climate change impacts in isolation. Furthermore, the diagram is useful to educate decision makers, stakeholders, and general public about cascading risks that can be triggered by the climate change. Socio-economic activities today are becoming increasingly more inter-dependent because of the rapid technological progress, urbanization, and the globalization among others. Equally complex is the ecosystem that is susceptible to climate change, which comprises interwoven processes affecting one another. In the context of climate change, a number of climate risks have been identified and classified according to regions and sectors. These reports, however, did not fully address the inter-relations among risks because of the complexity inherent in this issue. Climate risks may ripple through sectors in the present inter-dependent world, posing a challenge ahead of us to maintain the resilience of the system. It is therefore imperative to improve our understanding on how climate change may induce a chain of impacts. Our study is a first step toward this goal by mapping out climate risks and their cause-effect relationships based on current literature.

NASA and the U.S. climate program - A problem in data management

NASA Technical Reports Server (NTRS)

Quann, J. J.

1978-01-01

NASA's contribution to the total data base for the National Climate Plan will be to produce climate data sets from its experimental space observing systems and to maximize the value of these data for climate analysis and prediction. Validated data sets will be provided to NOAA for inclusion into their overall diagnostic data base. NASA data management for the Climate Plan will involve: (1) cataloging and retrieval of large integrated and distributed data sets upon user demand, and (2) the storage equivalent of 100,000 digital data tapes. It will be the largest, most complex data system ever developed by NASA

The aerosol-monsoon climate system of Asia: A new paradigm

NASA Astrophysics Data System (ADS)

Lau, William K. M.

2016-02-01

This commentary is based on a series of recent lectures on aerosol-monsoon interactions I gave at the Beijing Normal University in August 2015. A main theme of the lectures is on a new paradigm of "An Aerosol-Monsoon-Climate-System", which posits that aerosol, like rainfall, cloud, and wind, is an integral component of the monsoon climate system, influencing monsoon weather and climate on all timescales. Here, salient issues discussed in my lectures and my personal perspective regarding interactions between atmospheric dynamics and aerosols from both natural and anthropogenic sources are summarized. My hope is that under this new paradigm, we can break down traditional disciplinary barriers, advance a deeper understanding of weather and climate in monsoon regions, as well as entrain a new generation of geoscientists to strive for a sustainable future for one of the most complex and challenging human-natural climate sub-system of the earth.

Analytically tractable climate-carbon cycle feedbacks under 21st century anthropogenic forcing

NASA Astrophysics Data System (ADS)

Lade, Steven J.; Donges, Jonathan F.; Fetzer, Ingo; Anderies, John M.; Beer, Christian; Cornell, Sarah E.; Gasser, Thomas; Norberg, Jon; Richardson, Katherine; Rockström, Johan; Steffen, Will

2018-05-01

Changes to climate-carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate-carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate-carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate-carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate-carbon feedback; and concentration-carbon feedbacks may be more sensitive to future climate change than climate-carbon feedbacks. Simple models such as that developed here also provide workbenches for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.

Noise-induced transitions and shifts in a climate-vegetation feedback model.

PubMed

Alexandrov, Dmitri V; Bashkirtseva, Irina A; Ryashko, Lev B

2018-04-01

Motivated by the extremely important role of the Earth's vegetation dynamics in climate changes, we study the stochastic variability of a simple climate-vegetation system. In the case of deterministic dynamics, the system has one stable equilibrium and limit cycle or two stable equilibria corresponding to two opposite (cold and warm) climate-vegetation states. These states are divided by a separatrix going across a point of unstable equilibrium. Some possible stochastic scenarios caused by different externally induced natural and anthropogenic processes inherit properties of deterministic behaviour and drastically change the system dynamics. We demonstrate that the system transitions across its separatrix occur with increasing noise intensity. The climate-vegetation system therewith fluctuates, transits and localizes in the vicinity of its attractor. We show that this phenomenon occurs within some critical range of noise intensities. A noise-induced shift into the range of smaller global average temperatures corresponding to substantial oscillations of the Earth's vegetation cover is revealed. Our analysis demonstrates that the climate-vegetation interactions essentially contribute to climate dynamics and should be taken into account in more precise and complex models of climate variability.

Sink or Swim: Adapting to the Hydrologic Impacts of Climate Change

NASA Astrophysics Data System (ADS)

Gleick, P. H.

2014-12-01

Climate changes lead to a wide range of societal and environmental impacts; indeed, strong evidence has accrued that such impacts are already occurring, as summarized by the newest National Climate Assessment and other analyses. Among the most important will be alterations in the hydrologic cycle, changes in water supply and demand, and impacts on existing water-related infrastructure. Because of the complexity of our water systems, adaptation responses will be equally complex. This problem has made it difficult for water managers and planners to develop and implement adaptation strategies. This talk will address three ways to think about water-related adaptation approaches to climate change: (1) strategies that are already being implemented to address population and economic changes without climate change; (2) whether these first-line strategies are appropriate for additional impacts that might result from climatic changes; and (3) new approaches that might be necessary for new, non-linear, or threshold impacts. An effort will also be made to differentiate between adaptation strategies that influence the hydrologic cycle directly (e.g., cloud seeding), those that influence supply management (e.g., construction of additional reservoirs or water-distribution systems), and those that affect water demand (e.g., removal of outdoor landscaping, installation of efficient irrigation systems).

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.

Building Systems from Scratch: An Exploratory Study of Students Learning about Climate Change

ERIC Educational Resources Information Center

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual…

ClimateSpark: An in-memory distributed computing framework for big climate data analytics

NASA Astrophysics Data System (ADS)

Hu, Fei; Yang, Chaowei; Schnase, John L.; Duffy, Daniel Q.; Xu, Mengchao; Bowen, Michael K.; Lee, Tsengdar; Song, Weiwei

2018-06-01

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple-dimensional, array-based datasets in various geoscience domains.

System's flips in climate-related energy (CRE) systems

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Creutin, Jean-Dominique; Engeland, Kolbjørn; François, Baptiste; Renard, Benjamin

2014-05-01

Several modern environmental questions invite to explore the complex relationships between natural phenomena and human behaviour at a range of space and time scales. This usually involves a number of cause-effect (causal) relationships, linking actions and events. In lay terms, 'effect' can be defined as 'what happened' and 'cause', 'why something happened.' In a changing world or merely moving from one scale to another, shifts in perspective are expected, bringing some phenomena into the foreground and putting others to the background. Systems can thus flip from one set of causal structures to another in response to environmental perturbations and human innovations or behaviors, for instance, as space-time signatures are modified. The identification of these flips helps in better understanding and predicting how societies and stakeholders react to a shift in perspective. In this study, our motivation is to investigate possible consequences of the shift to a low carbon economy in terms of socio-technico systems' flips. The focus is on the regional production of Climate-Related Energy (CRE) (hydro-, wind- and solar-power). We search for information on historic shifts that may help defining the forcing conditions of abrupt changes and extreme situations. We identify and present a series of examples in which we try to distinguish the various tipping points, thresholds, breakpoints and regime shifts that are characteristic of complex systems in the CRE production domain. We expect that with these examples our comprehension of the question will be enriched, providing us the elements needed to better validate modeling attempts, to predict and manage flips of complex CRE production systems. The work presented is part of the FP7 project COMPLEX (Knowledge based climate mitigation systems for a low carbon economy; http://www.complex.ac.uk/).

Nonlinear dynamics in ecosystem response to climatic change: Case studies and policy implications

USGS Publications Warehouse

Burkett, Virginia R.; Wilcox, Douglas A.; Stottlemyer, Robert; Barrow, Wylie; Fagre, Dan; Baron, Jill S.; Price, Jeff; Nielsen, Jennifer L.; Allen, Craig D.; Peterson, David L.; Ruggerone, Greg; Doyle, Thomas

2005-01-01

Many biological, hydrological, and geological processes are interactively linked in ecosystems. These ecological phenomena normally vary within bounded ranges, but rapid, nonlinear changes to markedly different conditions can be triggered by even small differences if threshold values are exceeded. Intrinsic and extrinsic ecological thresholds can lead to effects that cascade among systems, precluding accurate modeling and prediction of system response to climate change. Ten case studies from North America illustrate how changes in climate can lead to rapid, threshold-type responses within ecological communities; the case studies also highlight the role of human activities that alter the rate or direction of system response to climate change. Understanding and anticipating nonlinear dynamics are important aspects of adaptation planning since responses of biological resources to changes in the physical climate system are not necessarily proportional and sometimes, as in the case of complex ecological systems, inherently nonlinear.

Geometric state space uncertainty as a new type of uncertainty addressing disparity in ';emergent properties' between real and modeled systems

NASA Astrophysics Data System (ADS)

Montero, J. T.; Lintz, H. E.; Sharp, D.

2013-12-01

Do emergent properties that result from models of complex systems match emergent properties from real systems? This question targets a type of uncertainty that we argue requires more attention in system modeling and validation efforts. We define an ';emergent property' to be an attribute or behavior of a modeled or real system that can be surprising or unpredictable and result from complex interactions among the components of a system. For example, thresholds are common across diverse systems and scales and can represent emergent system behavior that is difficult to predict. Thresholds or other types of emergent system behavior can be characterized by their geometry in state space (where state space is the space containing the set of all states of a dynamic system). One way to expedite our growing mechanistic understanding of how emergent properties emerge from complex systems is to compare the geometry of surfaces in state space between real and modeled systems. Here, we present an index (threshold strength) that can quantify a geometric attribute of a surface in state space. We operationally define threshold strength as how strongly a surface in state space resembles a step or an abrupt transition between two system states. First, we validated the index for application in greater than three dimensions of state space using simulated data. Then, we demonstrated application of the index in measuring geometric state space uncertainty between a real system and a deterministic, modeled system. In particular, we looked at geometric space uncertainty between climate behavior in 20th century and modeled climate behavior simulated by global climate models (GCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5). Surfaces from the climate models came from running the models over the same domain as the real data. We also created response surfaces from a real, climate data based on an empirical model that produces a geometric surface of predicted values in state space. We used a kernel regression method designed to capture the geometry of real data pattern without imposing shape assumptions a priori on the data; this kernel regression method is known as Non-parametric Multiplicative Regression (NPMR). We found that quantifying and comparing a geometric attribute in more than three dimensions of state space can discern whether the emergent nature of complex interactions in modeled systems matches that of real systems. Further, this method has potentially wider application in contexts where searching for abrupt change or ';action' in any hyperspace is desired.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Edge states in the climate system: exploring global instabilities and critical transitions

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Bódai, Tamás

2017-07-01

Multistability is a ubiquitous feature in systems of geophysical relevance and provides key challenges for our ability to predict a system’s response to perturbations. Near critical transitions small causes can lead to large effects and—for all practical purposes—irreversible changes in the properties of the system. As is well known, the Earth climate is multistable: present astronomical and astrophysical conditions support two stable regimes, the warm climate we live in, and a snowball climate characterized by global glaciation. We first provide an overview of methods and ideas relevant for studying the climate response to forcings and focus on the properties of critical transitions in the context of both stochastic and deterministic dynamics, and assess strengths and weaknesses of simplified approaches to the problem. Following an idea developed by Eckhardt and collaborators for the investigation of multistable turbulent fluid dynamical systems, we study the global instability giving rise to the snowball/warm multistability in the climate system by identifying the climatic edge state, a saddle embedded in the boundary between the two basins of attraction of the stable climates. The edge state attracts initial conditions belonging to such a boundary and, while being defined by the deterministic dynamics, is the gate facilitating noise-induced transitions between competing attractors. We use a simplified yet Earth-like intermediate complexity climate model constructed by coupling a primitive equations model of the atmosphere with a simple diffusive ocean. We refer to the climatic edge states as Melancholia states and provide an extensive analysis of their features. We study their dynamics, their symmetry properties, and we follow a complex set of bifurcations. We find situations where the Melancholia state has chaotic dynamics. In these cases, we have that the basin boundary between the two basins of attraction is a strange geometric set with a nearly zero codimension, and relate this feature to the time scale separation between instabilities occurring on weather and climatic time scales. We also discover a new stable climatic state that is similar to a Melancholia state and is characterized by non-trivial symmetry properties.

Climate Informatics

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; Alexander, Francis J.; Niculescu-Mizil, Alexandru; Steinhaeuser, Karsten; Tippett, Michael; Banerjee, Arindam; Blumenthal, M. Benno; Ganguly, Auroop R.; Smerdon, Jason E.;

Software Testing and Verification in Climate Model Development

NASA Technical Reports Server (NTRS)

Clune, Thomas L.; Rood, RIchard B.

2011-01-01

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Seasonal forecasting and health impact models: challenges and opportunities.

PubMed

Ballester, Joan; Lowe, Rachel; Diggle, Peter J; Rodó, Xavier

2016-10-01

After several decades of intensive research, steady improvements in understanding and modeling the climate system have led to the development of the first generation of operational health early warning systems in the era of climate services. These schemes are based on collaborations across scientific disciplines, bringing together real-time climate and health data collection, state-of-the-art seasonal climate predictions, epidemiological impact models based on historical data, and an understanding of end user and stakeholder needs. In this review, we discuss the challenges and opportunities of this complex, multidisciplinary collaboration, with a focus on the factors limiting seasonal forecasting as a source of predictability for climate impact models. © 2016 New York Academy of Sciences.

Undergraduate Students' Mental Models of the Climate System

ERIC Educational Resources Information Center

Mehta, Jignesh

2017-01-01

The climate, being a complex system, is difficult for people to understand. If better education is to be designed to improve the public's understanding of the subject, educators must be aware of the prior knowledge that students bring with them to the classroom since it is through that prism that people make sense of the world. As such, the aim of…

Assessing Climate Vulnerability and Resilience of a Major Water Resource System - Inverting the Paradigm for Specific Risk Quantification at Decision Making Points of Impact

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.; Skindlov, J. A.

2015-12-01

Water resource systems have provided vital support to transformative growth in the Southwest United States and the Phoenix, Arizona metropolitan area where the Salt River Project (SRP) currently satisfies 40% of the area's water demand from reservoir storage and groundwater. Large natural variability and expectations of climate changes have sensitized water management to risks posed by future periods of excess and drought. The conventional approach to impacts assessment has been downscaled climate model simulations translated through hydrologic models; but, scenario ranges enlarge as uncertainties propagate through sequential levels of modeling complexity. The research often does not reach the stage of specific impact assessments, rendering future projections frustratingly uncertain and unsuitable for complex decision-making. Alternatively, this study inverts the common approach by beginning with the threatened water system and proceeding backwards to the uncertain climate future. The methodology is built upon reservoir system response modeling to exhaustive time series of climate-driven net basin supply. A reservoir operations model, developed with SRP guidance, assesses cumulative response to inflow variability and change. Complete statistical analyses of long-term historical watershed climate and runoff data are employed for 10,000-year stochastic simulations, rendering the entire range of multi-year extremes with full probabilistic characterization. Sets of climate change projections are then translated by temperature sensitivity and precipitation elasticity into future inflow distributions that are comparatively assessed with the reservoir operations model. This approach provides specific risk assessments in pragmatic terms familiar to decision makers, interpretable within the context of long-range planning and revealing a clearer meaning of climate change projections for the region. As a transferable example achieving actionable findings, the approach can guide other communities confronting water resource planning challenges.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, E.; Sokolov, A. P.; Schlosser, C. A.; Scott, J. R.; Gao, X.

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity, with a two-dimensional zonal-mean atmosphere, to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three dimensional atmospheric model; and a statistical downscaling, where a pattern scaling algorithm uses climate-change patterns from 17 climate models. This framework allows for key sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections; climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate); natural variability; and structural uncertainty. Results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also nd that dierent initial conditions lead to dierences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider all sources of uncertainty when modeling climate impacts over Northern Eurasia.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

Toward a formal definition of water scarcity in natural human systems

Treesearch

W.K. Jaeger; A.J. Plantinga; H. Chang; K. Dello; G. Grant; D. Hulse; J.J. McDonnell; S. Lancaster; H. Moradkhani; A.T. Morzillo; P. Mote; A. Nolin; M. Santlemann; J. Wu

2013-01-01

Water scarcity may appear to be a simple concept, but it can be difficult to apply to complex natural-human systems. While aggregate scarcity indices are straightforward to compute, they do not adequately represent the spatial and temporal variations in water scarcity that arise from complex systems interactions. The uncertain effects of future climate change on water...

Linking climate projections to performance: A yield-based decision scaling assessment of a large urban water resources system

NASA Astrophysics Data System (ADS)

Turner, Sean W. D.; Marlow, David; Ekström, Marie; Rhodes, Bruce G.; Kularathna, Udaya; Jeffrey, Paul J.

2014-04-01

Despite a decade of research into climate change impacts on water resources, the scientific community has delivered relatively few practical methodological developments for integrating uncertainty into water resources system design. This paper presents an application of the "decision scaling" methodology for assessing climate change impacts on water resources system performance and asks how such an approach might inform planning decisions. The decision scaling method reverses the conventional ethos of climate impact assessment by first establishing the climate conditions that would compel planners to intervene. Climate model projections are introduced at the end of the process to characterize climate risk in such a way that avoids the process of propagating those projections through hydrological models. Here we simulated 1000 multisite synthetic monthly streamflow traces in a model of the Melbourne bulk supply system to test the sensitivity of system performance to variations in streamflow statistics. An empirical relation was derived to convert decision-critical flow statistics to climatic units, against which 138 alternative climate projections were plotted and compared. We defined the decision threshold in terms of a system yield metric constrained by multiple performance criteria. Our approach allows for fast and simple incorporation of demand forecast uncertainty and demonstrates the reach of the decision scaling method through successful execution in a large and complex water resources system. Scope for wider application in urban water resources planning is discussed.

Challenges in the analysis of complex systems: introduction and overview

NASA Astrophysics Data System (ADS)

Hastings, Harold M.; Davidsen, Jörn; Leung, Henry

2017-12-01

One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.

Standardized research protocols enable transdisciplinary research of climate variation impacts in corn production systems

USDA-ARS?s Scientific Manuscript database

The important questions about agriculture, climate, and sustainability have become increasingly complex and require a coordinated, multi-faceted approach for developing new knowledge and understanding. A multi-state, transdisciplinary project was begun in 2011 to study the potential for both mitigat...

Understanding the Impacts of Soil, Climate, and Farming Practices on Soil Organic Carbon Sequestration: A Simulation Study in Australia.

PubMed

Godde, Cécile M; Thorburn, Peter J; Biggs, Jody S; Meier, Elizabeth A

2016-01-01

Carbon sequestration in agricultural soils has the capacity to mitigate greenhouse gas emissions, as well as to improve soil biological, physical, and chemical properties. The review of literature pertaining to soil organic carbon (SOC) dynamics within Australian grain farming systems does not enable us to conclude on the best farming practices to increase or maintain SOC for a specific combination of soil and climate. This study aimed to further explore the complex interactions of soil, climate, and farming practices on SOC. We undertook a modeling study with the Agricultural Production Systems sIMulator modeling framework, by combining contrasting Australian soils, climates, and farming practices (crop rotations, and management within rotations, such as fertilization, tillage, and residue management) in a factorial design. This design resulted in the transposition of contrasting soils and climates in our simulations, giving soil-climate combinations that do not occur in the study area to help provide insights into the importance of the climate constraints on SOC. We statistically analyzed the model's outputs to determinate the relative contributions of soil parameters, climate, and farming practices on SOC. The initial SOC content had the largest impact on the value of SOC, followed by the climate and the fertilization practices. These factors explained 66, 18, and 15% of SOC variations, respectively, after 80 years of constant farming practices in the simulation. Tillage and stubble management had the lowest impacts on SOC. This study highlighted the possible negative impact on SOC of a chickpea phase in a wheat-chickpea rotation and the potential positive impact of a cover crop in a sub-tropical climate (QLD, Australia) on SOC. It also showed the complexities in managing to achieve increased SOC, while simultaneously aiming to minimize nitrous oxide (N2O) emissions and nitrate leaching in farming systems. The transposition of contrasting soils and climates in our simulations revealed the importance of the climate constraints on SOC.

Understanding the Impacts of Soil, Climate, and Farming Practices on Soil Organic Carbon Sequestration: A Simulation Study in Australia

PubMed Central

Godde, Cécile M.; Thorburn, Peter J.; Biggs, Jody S.; Meier, Elizabeth A.

2016-01-01

Carbon sequestration in agricultural soils has the capacity to mitigate greenhouse gas emissions, as well as to improve soil biological, physical, and chemical properties. The review of literature pertaining to soil organic carbon (SOC) dynamics within Australian grain farming systems does not enable us to conclude on the best farming practices to increase or maintain SOC for a specific combination of soil and climate. This study aimed to further explore the complex interactions of soil, climate, and farming practices on SOC. We undertook a modeling study with the Agricultural Production Systems sIMulator modeling framework, by combining contrasting Australian soils, climates, and farming practices (crop rotations, and management within rotations, such as fertilization, tillage, and residue management) in a factorial design. This design resulted in the transposition of contrasting soils and climates in our simulations, giving soil–climate combinations that do not occur in the study area to help provide insights into the importance of the climate constraints on SOC. We statistically analyzed the model’s outputs to determinate the relative contributions of soil parameters, climate, and farming practices on SOC. The initial SOC content had the largest impact on the value of SOC, followed by the climate and the fertilization practices. These factors explained 66, 18, and 15% of SOC variations, respectively, after 80 years of constant farming practices in the simulation. Tillage and stubble management had the lowest impacts on SOC. This study highlighted the possible negative impact on SOC of a chickpea phase in a wheat–chickpea rotation and the potential positive impact of a cover crop in a sub-tropical climate (QLD, Australia) on SOC. It also showed the complexities in managing to achieve increased SOC, while simultaneously aiming to minimize nitrous oxide (N2O) emissions and nitrate leaching in farming systems. The transposition of contrasting soils and climates in our simulations revealed the importance of the climate constraints on SOC. PMID:27242862

Climate variability and vulnerability to climate change: a review

PubMed Central

Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

2014-01-01

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

Modeling U.S. water resources under climate change

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

2014-04-01

Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

Complexity of Tropical Pacific Ecosystem and Biogeochemistry: Diurnal to Decadal, Plankters to Penguins

NASA Astrophysics Data System (ADS)

Murtugudde, R. G.; Wang, X.; Valsala, V.; Karnauskas, K. B.

2016-12-01

Tropical Pacific spans nearly 50% of the global tropics allowing to have its own mind in terms of climate variability and physical-biogeochemical interactions. While the El Niño-Southern Oscillation (ENSO) and its flavors get much attention, it is fairly clear by now that any further improvements in ENSO prediction skills and reliability of global warming projections must begin to observe and represent bio-physical interactions in the climate and Earth System models. Coupled climate variability over the tropical Pacific has a global reach with its diurnal to decadal timescales being manifest in ecosystem and biogechemistry. Zonal and meridional contrasts in biogeochemistry across the tropical Pacific is closely related to seasonal variability, ENSO diversity and the PDO. Apparent dominance of ocean dynamic controls on biogeochemistry belies the potential biogeochemical feedbacks on ocean dynamics which may well explain some of the chronic biases in the state-of-the-art climate models. The east Pacific cold-tongue is the most productive open ocean region in the world and home to a unique physical-biogeochmical laboratory, viz., the Galapagos. The Galapagos islands not only control the coupled climate variability via their ability to terminate the equatorial undercurrent but also offer a clear example of a biological loophole in terms of their impact on local upwelling and an expanding penguin habitat in the face of global warming. The complex bio-physical interactions in the cold-tongue and their influence on climate predictions and projections require a holisti thinking on future observing systems. Tropical Pacific offers a natural laboratory for designing a robust and sustained physical-biogeochemical observation system that can effectively bridge climate predictions and projections into a unified framework for subseasonal to multidecadal timescales. Such a system will be a foundation for establishing similar systems over the rest of the World ocean to seemlessly merge climate predictions and projections with the need to constantly monitor climate impacts on marine resources. This talk will focus on the zonal contrasts of the ocean dynamics and biogechemistry across the tropical Pacific to make a case for integrated physical-biogeochemical observations for climate predictions and projections.

An Automated Method to Identify Mesoscale Convective Complexes in the Regional Climate Model Evaluation System

NASA Astrophysics Data System (ADS)

Whitehall, K. D.; Jenkins, G. S.; Mattmann, C. A.; Waliser, D. E.; Kim, J.; Goodale, C. E.; Hart, A. F.; Ramirez, P.; Whittell, J.; Zimdars, P. A.

2012-12-01

Mesoscale convective complexes (MCCs) are large (2 - 3 x 105 km2) nocturnal convectively-driven weather systems that are generally associated with high precipitation events in short durations (less than 12hrs) in various locations through out the tropics and midlatitudes (Maddox 1980). These systems are particularly important for climate in the West Sahel region, where the precipitation associated with them is a principal component of the rainfall season (Laing and Fritsch 1993). These systems occur on weather timescales and are historically identified from weather data analysis via manual and more recently automated processes (Miller and Fritsch 1991, Nesbett 2006, Balmey and Reason 2012). The Regional Climate Model Evaluation System (RCMES) is an open source tool designed for easy evaluation of climate and Earth system data through access to standardized datasets, and intrinsic tools that perform common analysis and visualization tasks (Hart et al. 2011). The RCMES toolkit also provides the flexibility of user-defined subroutines for further metrics, visualization and even dataset manipulation. The purpose of this study is to present a methodology for identifying MCCs in observation datasets using the RCMES framework. TRMM 3 hourly datasets will be used to demonstrate the methodology for 2005 boreal summer. This method promotes the use of open source software for scientific data systems to address a concern to multiple stakeholders in the earth sciences. A historical MCC dataset provides a platform with regards to further studies of the variability of frequency on various timescales of MCCs that is important for many including climate scientists, meteorologists, water resource managers, and agriculturalists. The methodology of using RCMES for searching and clipping datasets will engender a new realm of studies as users of the system will no longer be restricted to solely using the datasets as they reside in their own local systems; instead will be afforded rapid, effective, and transparent access, processing and visualization of the wealth of remote sensing datasets and climate model outputs available.

How Did Climate and Humans Respond to Past Volcanic Eruptions?

NASA Technical Reports Server (NTRS)

Toohey, Matthew; Ludlow, Francis; Legrande, Allegra N.

2016-01-01

To predict and prepare for future climate change, scientists are striving to understand how global-scale climatic change manifests itself on regional scales and also how societies adapt or don't to sometimes subtle and complex climatic changes. In this regard, the strongest volcanic eruptions of the past are powerful test cases, showcasing how the broad climate system responds to sudden changes in radiative forcing and how societies have responded to the resulting climatic shocks. These issues were at the heart of the inaugural workshop of the Volcanic Impacts on Climate and Society (VICS) Working Group, convened in June 2016 at the Lamont-Doherty Earth Observatory of Columbia University in Palisades, N.Y. The 3-day meeting gathered approximately 50 researchers, who presented work intertwining the history of volcanic eruptions and the physical processes that connect eruptions with human and natural systems on a global scale.

Uncertainty Quantification in Climate Modeling and Projection

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

Qian, Yun; Jackson, Charles; Giorgi, Filippo

The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less

A multistage decision support framework to guide tree species management under climate change via habitat suitability and colonization models, and a knowledge-based scoring system

Treesearch

Anantha M. Prasad; Louis R. Iverson; Stephen N. Matthews; Matthew P. Peters

2016-01-01

Context. No single model can capture the complex species range dynamics under changing climates--hence the need for a combination approach that addresses management concerns. Objective. A multistage approach is illustrated to manage forested landscapes under climate change. We combine a tree species habitat model--DISTRIB II, a species colonization model--SHIFT, and...

Multiple causes of the Younger Dryas cold period: new insights from coupled model experiments constrained by data assimilation

NASA Astrophysics Data System (ADS)

Renssen, Hans; Mairesse, Aurélien; Goosse, Hugues; Mathiot, Pierre; Heiri, Oliver; Roche, Didier M.; Nisancioglu, Kerim H.; Valdes, Paul J.

2016-04-01

The Younger Dryas cooling event disrupted the overall warming trend in the North Atlantic region during the last deglaciation. Climate change during the Younger Dryas was abrupt, and thus provides insights into the sensitivity of the climate system to perturbations. The sudden Younger Dryas cooling has traditionally been attributed to a shut-down of the Atlantic meridional overturning circulation by meltwater discharges. However, alternative explanations such as strong negative radiative forcing and a shift in atmospheric circulation have also been offered. In this study we investigate the importance of these different forcings in coupled climate model experiments constrained by data assimilation. We find that the Younger Dryas climate signal as registered in proxy evidence is best simulated using a combination of processes: a weakened Atlantic meridional overturning circulation, moderate negative radiative forcing and an altered atmospheric circulation. We conclude that none of the individual mechanisms alone provide a plausible explanation for the Younger Dryas cold period. We suggest that the triggers for abrupt climate changes like the Younger Dryas are more complex than suggested so far, and that studies on the response of the climate system to perturbations should account for this complexity. Reference: Renssen, H. et al. (2015) Multiple causes of the Younger Dryas cold period. Nature Geoscience 8, 946-949.

Interactive, process-oriented climate modeling with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2016-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

Harmonizing human-hydrological system under climate change: A scenario-based approach for the case of the headwaters of the Tagus River

NASA Astrophysics Data System (ADS)

Lobanova, Anastasia; Liersch, Stefan; Tàbara, J. David; Koch, Hagen; Hattermann, Fred F.; Krysanova, Valentina

2017-05-01

Conventional water management strategies, that serve solely socio-economic demands and neglect changing natural conditions of the river basins, face significant challenges in governing complex human-hydrological systems, especially in the areas with constrained water availability. In this study we assess the possibility to harmonize the inter-sectoral water allocation scheme within a highly altered human-hydrological system under reduction in water availability, triggered by projected climate change applying scenario-based approach. The Tagus River Basin headwaters, with significant disproportion in the water resources allocation between the environmental and socio-economic targets were taken as a perfect example of such system out of balance. We propose three different water allocation strategies for this region, including two conventional schemes and one imposing shift to sustainable water management and environmental restoration of the river. We combine in one integrated modelling framework the eco-hydrological process-based Soil and Water Integrated Model (SWIM), coupled with the conceptual reservoir and water allocation modules driven by the latest bias-corrected climate projections for the region and investigate possible water allocation scenarios in the region under constrained water availability in the future. Our results show that the socio-economic demands have to be re-considered and lowered under any water allocation strategy, as the climate impacts may significantly reduce water availability in the future. Further, we show that a shift to sustainable water management strategy and river restoration is possible even under reduced water availability. Finally, our results suggest that the adaptation of complex human-hydrological systems to climate change and a shift to a more sustainable water management are likely to be parts of one joint strategy to cope with climate change impacts.

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.

It's a Sooty Problem: Black Carbon and Aerosols from Space

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2005-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with solar radiation, clouds and precipitation is lacking despite decades of research. Just recently we recognized that understanding the global aerosol system is fundamental for progress in climate change and hydrological cycle research. While a single instrument was used to demonstrate 50 yrs ago that the global CO2 levels are rising, posing thread to our climate, we need an may of satellites, surface networks of radiometers, elaborated laboratory and field experiments coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week), variability of the chemical composition and complex chemical and physical processes in the atmosphere. The result is a heterogeneous distribution of aerosol and their properties. The new generation of satellites and surface networks of radiometers provides exciting opportunities to measure the aerosol properties and their interaction with clouds and climate. However farther development in the satellite capability, aerosol chemical models and climate models is needed to fully decipher the aerosol secrets with accuracy required to predict future climates.

A user-friendly earth system model of low complexity: the ESCIMO system dynamics model of global warming towards 2100

NASA Astrophysics Data System (ADS)

Randers, Jorgen; Golüke, Ulrich; Wenstøp, Fred; Wenstøp, Søren

2016-11-01

We have made a simple system dynamics model, ESCIMO (Earth System Climate Interpretable Model), which runs on a desktop computer in seconds and is able to reproduce the main output from more complex climate models. ESCIMO represents the main causal mechanisms at work in the Earth system and is able to reproduce the broad outline of climate history from 1850 to 2015. We have run many simulations with ESCIMO to 2100 and beyond. In this paper we present the effects of introducing in 2015 six possible global policy interventions that cost around USD 1000 billion per year - around 1 % of world GDP. We tentatively conclude (a) that these policy interventions can at most reduce the global mean surface temperature - GMST - by up to 0.5 °C in 2050 and up to 1.0 °C in 2100 relative to no intervention. The exception is injection of aerosols into the stratosphere, which can reduce the GMST by more than 1.0 °C in a decade but creates other serious problems. We also conclude (b) that relatively cheap human intervention can keep global warming in this century below +2 °C relative to preindustrial times. Finally, we conclude (c) that run-away warming is unlikely to occur in this century but is likely to occur in the longer run. The ensuing warming is slow, however. In ESCIMO, it takes several hundred years to lift the GMST to +3 °C above preindustrial times through gradual self-reinforcing melting of the permafrost. We call for research to test whether more complex climate models support our tentative conclusions from ESCIMO.

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

A bottom-up approach to identifying the maximum operational adaptive capacity of water resource systems to a changing climate

NASA Astrophysics Data System (ADS)

Culley, S.; Noble, S.; Yates, A.; Timbs, M.; Westra, S.; Maier, H. R.; Giuliani, M.; Castelletti, A.

2016-09-01

Many water resource systems have been designed assuming that the statistical characteristics of future inflows are similar to those of the historical record. This assumption is no longer valid due to large-scale changes in the global climate, potentially causing declines in water resource system performance, or even complete system failure. Upgrading system infrastructure to cope with climate change can require substantial financial outlay, so it might be preferable to optimize existing system performance when possible. This paper builds on decision scaling theory by proposing a bottom-up approach to designing optimal feedback control policies for a water system exposed to a changing climate. This approach not only describes optimal operational policies for a range of potential climatic changes but also enables an assessment of a system's upper limit of its operational adaptive capacity, beyond which upgrades to infrastructure become unavoidable. The approach is illustrated using the Lake Como system in Northern Italy—a regulated system with a complex relationship between climate and system performance. By optimizing system operation under different hydrometeorological states, it is shown that the system can continue to meet its minimum performance requirements for more than three times as many states as it can under current operations. Importantly, a single management policy, no matter how robust, cannot fully utilize existing infrastructure as effectively as an ensemble of flexible management policies that are updated as the climate changes.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

System Dynamics to Climate-Driven Water Budget Analysis in the Eastern Snake Plains Aquifer

NASA Astrophysics Data System (ADS)

Ryu, J.; Contor, B.; Wylie, A.; Johnson, G.; Allen, R. G.

2010-12-01

Climate variability, weather extremes and climate change continue to threaten the sustainability of water resources in the western United States. Given current climate change projections, increasing temperature is likely to modify the timing, form, and intensity of precipitation events, which consequently affect regional and local hydrologic cycles. As a result, drought, water shortage, and subsequent water conflicts may become an increasing threat in monotone hydrologic systems in arid lands, such as the Eastern Snake Plain Aquifer (ESPA). The ESPA, in particular, is a critical asset in the state of Idaho. It is known as the economic lifeblood for more than half of Idaho’s population so that water resources availability and aquifer management due to climate change is of great interest, especially over the next few decades. In this study, we apply system dynamics as a methodology with which to address dynamically complex problems in ESPA’s water resources management. Aquifer recharge and discharge dynamics are coded in STELLA modeling system as input and output, respectively to identify long-term behavior of aquifer responses to climate-driven hydrological changes.

Weather, Climate, Web 2.0: 21st Century Students Speak Climate Science Well

ERIC Educational Resources Information Center

Sundberg, Cheryl White; Kennedy, Teresa; Odell, Michael R. L.

2013-01-01

Problem-based learning (PBL) and inquiry learning (IL) employ extensive scaffolding that results in cognitive load reduction and allows students to learn in complex domains. Hybrid teacher professional development models (PDM) using 21st century social collaboration tools embedding PBL and IL shows promise as a systemic approach for increasing…

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

AgMIP Climate Data and Scenarios for Integrated Assessment. Chapter 3

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; Winter, Jonathan M.; McDermid, Sonali P.; Hudson, Nicholas I.

2015-01-01

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

Does Climate Care about Land?

NASA Astrophysics Data System (ADS)

Dawson, E.; Lague, M. M.; Swann, A. L. S.

2017-12-01

Everyone knows that plants are influenced by the climate they live in. However, the reverse is also true: plants can influence climate both locally and globally by changing atmospheric circulation. Uncovering the role that plants play in climate has been challenging—the interactions are complex and vary greatly in different regions of the world. We lack a systematic understanding of the role of vegetation in the climate system. Using a new simplified land model coupled to a modern Earth System Model (ESM), we are able to separate the individual influences of the land system in the context of modern ESMs. For example, with our model we are able to test how the capacity of the land to hold water influences the atmosphere. If less water is able to evaporate, this could lead to substantial warming, and could even influence clouds. Understanding specifically where and how the atmosphere is influenced by the land surface improves our understanding of how future changes in the land surface will in turn feedback on climate, and how that will impact people. This improved understanding also advances our knowledge of the key role biology plays in driving the global climate system.

Planning for climate change: the need for mechanistic systems-based approaches to study climate change impacts on diarrheal diseases

PubMed Central

Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara

2016-01-01

Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. PMID:26799810

a System Dynamics Approach for Looking at the Human and Environmental Interactions of Community-Based Irrigation Systems in New Mexico

NASA Astrophysics Data System (ADS)

Ochoa, C. G.; Tidwell, V. C.

2012-12-01

In the arid southwestern United States community water management systems have adapted to cope with climate variability and with socio-cultural and economic changes that have occurred since the establishment of these systems more than 300 years ago. In New Mexico, the community-based irrigation systems were established by Spanish settlers and have endured climate variability in the form of low levels of precipitation and have prevailed over important socio-political changes including the transfer of territory between Spain and Mexico, and between Mexico and the United States. Because of their inherent nature of integrating land and water use with society involvement these community-based systems have multiple and complex economic, ecological, and cultural interactions. Current urban population growth and more variable climate conditions are adding pressure to the survival of these systems. We are conducting a multi-disciplinary research project that focuses on characterizing these intrinsically complex human and natural interactions in three community-based irrigation systems in northern New Mexico. We are using a system dynamics approach to integrate different hydrological, ecological, socio-cultural and economic aspects of these three irrigation systems. Coupled with intensive field data collection, we are building a system dynamics model that will enable us to simulate important linkages and interactions between environmental and human elements occurring in each of these water management systems. We will test different climate variability and population growth scenarios and the expectation is that we will be able to identify critical tipping points of these systems. Results from this model can be used to inform policy recommendations relevant to the environment and to urban and agricultural land use planning in the arid southwestern United States.

Impacts of climate change on the formation and stability of late Quaternary sand sheets and falling dunes, Black Mesa region, southern Colorado Plateau, USA

USGS Publications Warehouse

Ellwein, Amy L.; Mahan, Shannon; McFadden, Leslie D.

2015-01-01

Widely used predictive models of eolian system dynamics are typically based entirely on climatic variables and do not account for landscape complexity and geomorphic history. Climate-only assumptions fail to give accurate predictions of the dynamics of this and many other dune fields. A growing body of work suggests that eolian deposits in wind-driven semiarid climates may be more strongly related to increases in sediment supply than to increases in aridity.

Complex agro-ecosystems for food security in a changing climate

PubMed Central

Khumairoh, Uma; Groot, Jeroen CJ; Lantinga, Egbert A

2012-01-01

Attempts to increase food crop yields by intensifying agricultural systems using high inputs of nonrenewable resources and chemicals frequently lead to de-gradation of natural resources, whereas most technological innovations are not accessible for smallholders that represent the majority of farmers world wide. Alternatively, cocultures consisting of assemblages of plant and animal species can support ecological processes of nutrient cycling and pest control, which may lead to increasing yields and declining susceptibility to extreme weather conditions with increasing complexity of the systems. Here we show that enhancing the complexity of a rice production system by adding combinations of compost, azolla, ducks, and fish resulted in strongly increased grain yields and revenues in a season with extremely adverse weather conditions on East Java, Indonesia. We found that azolla, duck, and fish increased plant nutrient content, tillering and leaf area expansion, and strongly reduced the density of six different pests. In the most complex system comprising all components the highest grain yield was obtained. The net revenues of this system from sales of rice grain, fish, and ducks, after correction for extra costs, were 114% higher than rice cultivation with only compost as fertilizer. These results provide more insight in the agro-ecological processes and demonstrate how complex agricultural systems can contribute to food security in a changing climate. If smallholders can be trained to manage these systems and are supported for initial investments by credits, their livelihoods can be improved while producing in an ecologically benign way. PMID:22957173

Understanding Student Cognition about Complex Earth System Processes Related to Climate Change

NASA Astrophysics Data System (ADS)

McNeal, K. S.; Libarkin, J.; Ledley, T. S.; Dutta, S.; Templeton, M. C.; Geroux, J.; Blakeney, G. A.

2011-12-01

The Earth's climate system includes complex behavior and interconnections with other Earth spheres that present challenges to student learning. To better understand these unique challenges, we have conducted experiments with high-school and introductory level college students to determine how information pertaining to the connections between the Earth's atmospheric system and the other Earth spheres (e.g., hydrosphere and cryosphere) are processed. Specifically, we include psychomotor tests (e.g., eye-tracking) and open-ended questionnaires in this research study, where participants were provided scientific images of the Earth (e.g., global precipitation and ocean and atmospheric currents), eye-tracked, and asked to provide causal or relational explanations about the viewed images. In addition, the students engaged in on-line modules (http://serc.carleton.edu/eslabs/climate/index.html) focused on Earth system science as training activities to address potential cognitive barriers. The developed modules included interactive media, hands-on lessons, links to outside resources, and formative assessment questions to promote a supportive and data-rich learning environment. Student eye movements were tracked during engagement with the materials to determine the role of perception and attention on understanding. Students also completed a conceptual questionnaire pre-post to determine if these on-line curriculum materials assisted in their development of connections between Earth's atmospheric system and the other Earth systems. The pre-post results of students' thinking about climate change concepts, as well as eye-tracking results, will be presented.

Building Systems from Scratch: an Exploratory Study of Students Learning About Climate Change

NASA Astrophysics Data System (ADS)

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual programming environment, Scratch, to design games to teach others about climate change. The experience was carefully constructed so that girls of widely differing levels of experience were able to engage in a cycle of game design. This qualitative study aimed to explore the representational choices the girls made as they took up aspects of climate change systems and modeled them in their games. Evidence points to the ways in which designing games about climate science fostered emergent systems thinking and engagement in modeling practices as learners chose what to represent in their games, grappled with the realism of their respective representations, and modeled interactions among systems components. Given the girls' levels of programming skill, parts of systems were more tractable to create than others. The educational purpose of the games was important to the girls' overall design experience, since it influenced their choice of topic, and challenged their emergent understanding of climate change as a systems problem.

The impacts of climate change in coastal marine systems.

PubMed

Harley, Christopher D G; Randall Hughes, A; Hultgren, Kristin M; Miner, Benjamin G; Sorte, Cascade J B; Thornber, Carol S; Rodriguez, Laura F; Tomanek, Lars; Williams, Susan L

2006-02-01

Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.

Design for waste-management system

NASA Technical Reports Server (NTRS)

Guarneri, C. A.; Reed, A.; Renman, R.

1973-01-01

Study was made and system defined for water-recovery and solid-waste processing for low-rise apartment complexes. System can be modified to conform with unique requirements of community, including hydrology, geology, and climate. Reclamation is accomplished by treatment process that features reverse-osmosis membranes.

A common framework for greenhouse gas assessment protocols in temperate agroforestry systems: Connecting via GRACEnet

USDA-ARS?s Scientific Manuscript database

Agroforestry systems offer many ecosystem benefits, but such systems have previously been marginalized in temperate environments due to overriding economic goals and perceived management complexity. In view of adaptation to a changing climate, agroforestry systems offer advantages that require quan...

The anthroposphere as an anticipatory system: Open questions on steering the climate.

PubMed

Scolozzi, Rocco; Geneletti, Davide

2017-02-01

Climate change research and action counteracting it affect everyone and would involve cross-societal transformations reshaping the anthroposphere in its entirety. Scrutinizing climate-related science and policies, we recognize attempts to steer the evolution of climate according to expected (or modelled) futures. Such attempts would turn the anthroposphere into a large "anticipatory system", in which human society seeks to anticipate and, possibly, to govern climate dynamics. The chief aim of this discussion paper is to open a critical debate on the climate change paradigm (CCP) drawing on a strategic and systemic framework grounded in the concept of anticipatory system sensu Rosen (1991). The proposed scheme is ambitiously intended to turn an intricate issue into a complex but structured problem that is to say, to make such complexity clear and manageable. This framework emerges from concepts borrowed from different scientific fields (including future studies and system dynamics) and its background lies in a simple quantitative literature overview, relying upon a broad level of analysis. The proposed framework will assist researchers and policy makers in thinking of CCP in terms of an anticipatory system, and in disentangling its interrelated (and sometimes intricate) aspects. In point of fact, several strategic questions related to CCP were not subjected to an adequate transdisciplinary discussion: what are the interplays between physical processes and social-political interventions, who is the observer (what he/she is looking for), and which paradigm is being used (or who defines the desirable future). The proposed scheme allows to structure such various topics in an arrangement which is easier to communicate, highlighting the linkages in between, and making them intelligible and open to verification and discussion. Furthermore, ideally developments will help scientists and policy makers address the strategic gaps between the evidence-based climatological assessments and the plurality of possible answers as applied to the geopolitical contingencies. Copyright © 2016 Elsevier B.V. All rights reserved.

Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2015-04-01

Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

NASA Astrophysics Data System (ADS)

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-12-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

PubMed Central

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-01-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model.

PubMed

Boulton, Chris A; Allison, Lesley C; Lenton, Timothy M

2014-12-08

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Heating up Climate Literacy Education: Understanding Teachers' and Students' Motivational and Affective Response to Climate Change

NASA Astrophysics Data System (ADS)

Sinatra, G. M.

2011-12-01

Changing students' ideas about controversial scientific issues, such as human-induced climate change, presents unique challenges for educators (Lombardi & Sinatra, 2010; Sinatra & Mason, 2008). First, climate science is complex and requires "systems thinking," or the ability to think and reason abstractly about emergent systems (Goldstone & Sakamoto, 2003). Appreciating the intricacies of complex systems and emergent processes has proven challenging for students (Chi, 2005). In addition to these challenges, there are specific misconceptions that may lead thinking astray on the issue of global climate change, such as the distinction between weather and climate (Lombardi & Sinatra, 2010). As an example, when students are asked about their views on climate change, they often recall individual storm events or very cold periods and use their personal experiences and recollections of short-term temperature fluctuations to assess whether the planet is warming. Beyond the conceptual difficulties, controversial topics offer another layer of challenge. Such topics are often embedded in complex socio-cultural and political contexts, have a high degree of uncertainty, and may be perceived by individuals as in conflict with their personal or religious beliefs (Levinson, 2006, Sinatra, Kardash, Taasoobshirazi, & Lombardi, 2011). Individuals are often committed to their own views on socio-scientific issues and this commitment may serve as a motivation to actively resist new ideas (Dole & Sinatra, 1998). Individuals may also have strong emotions associated with their misconceptions (Broughton, Pekrun, & Sinatra, 2011). Negative emotions, misconceptions, and resistance do not make a productive combination for learning. Further, teachers who find human-induced climate change implausible have been shown to hold negative emotions about having to teach about climate change (Lombardi & Sinatra, in preparation), which could affect how they present the topic to students. In this presentation, findings from a research program exploring the role of "hot constructs" such as motivation and emotion in teaching and learning about climate change will be shared. In these studies, we have explored constructs such as emotions, misconceptions, plausibility perceptions, understanding deep time, and dispositions towards uncertainty. Results from four studies will be highlighted. In the first study, we demonstrated that comfort with ambiguity and a willingness to think deeply about issues predicted both change in attitudes towards climate change and expressed willingness to take mitigative action in college students (Sinatra, et al. 2011). In another study with college students, we demonstrated that knowledge of deep time and plausibility perceptions of human-induced climate change were related to students' understanding of weather and climate distinctions (Lombardi & Sinatra, 2010). In a study with graduate education students, we found that misconceptions about climate change were associated with strong emotions (Broughton, et al., 2011). With practicing teachers we have found that emotions, specifically anger and hopelessness, were significant predictors of plausibility perceptions of human-induced climate change (Lombardi & Sinatra, in preparation). The implications for climate change education of the findings will be discussed.

Expressions of climate perturbations in western Ugandan crater lake sediment records during the last 1000 years

NASA Astrophysics Data System (ADS)

Mills, K.; Ryves, D. B.; Anderson, N. J.; Bryant, C. L.; Tyler, J. J.

2014-08-01

Equatorial East Africa has a complex regional patchwork of climate regimes, sensitive to climate fluctuations over a variety of temporal and spatial scales during the late Holocene. Understanding how these changes are recorded in and interpreted from biological and geochemical proxies in lake sedimentary records remains a key challenge to answering fundamental questions regarding the nature, spatial extent and synchroneity of climatic changes seen in East African palaeo-records. Using a paired lake approach, where neighbouring lakes share the same geology, climate and landscape, it might be expected that the systems will respond similarly to external climate forcing. Sediment cores from two crater lakes in western Uganda spanning the last ~1000 years were examined to assess diatom community responses to late Holocene climate and environmental changes, and to test responses to multiple drivers using redundancy analysis (RDA). These archives provide annual to sub-decadal records of environmental change. Lakes Nyamogusingiri and Kyasanduka appear to operate as independent systems in their recording of a similar hydrological response signal via distinct diatom records. However, whilst their fossil diatom records demonstrate an individualistic, indirect response to external (e.g. climatic) drivers, the inferred lake levels show similar overall trends and reflect the broader patterns observed in Uganda and across East Africa. The lakes appear to be sensitive to large-scale climatic perturbations, with evidence of a dry Medieval Climate Anomaly (MCA; ca. AD 1000-1200). The diatom record from Lake Nyamogusingiri suggests a drying climate during the main phase of the Little Ice Age (LIA) (ca. AD 1600-1800), whereas the diatom response from the shallower Lake Kyasanduka is more complex (with groundwater likely playing a key role), and may be driven more by changes in silica and other nutrients, rather than by lake level. The sensitivity of these two Ugandan lakes to regional climate drivers breaks down in ca. AD 1800, when major changes in the ecosystems appear to be a response to increasing cultural impacts within the lake catchments, although both proxy records appear to respond to the drought recorded across East Africa in the mid-20th century. The data highlight the complexity of diatom community responses to external drivers (climate or cultural), even in neighbouring, shallow freshwater lakes. This research also illustrates the importance of, and the need to move towards, a multi-lake, multi-proxy landscape approach to understanding regional hydrological change which will allow for rigorous testing of climate reconstructions, climate forcing and ecosystem response models.

Climatic differentiation in polyploid apomictic Ranunculus auricomus complex in Europe.

PubMed

Paule, Juraj; Dunkel, Franz G; Schmidt, Marco; Gregor, Thomas

2018-05-21

Polyploidy and apomixis are important factors influencing plant distributions often resulting in range shifts, expansions and geographical parthenogenesis. We used the Ranunculus auricomus complex as a model to asses if the past and present distribution and climatic preferences were determined by these phenomena. Ecological differentiation among diploids and polyploids was tested by comparing the sets of climatic variables and distribution modelling using 191 novel ploidy estimations and 561 literature data. Significant differences in relative genome size on the diploid level were recorded between the "auricomus" and "cassubicus" groups and several new diploid occurrences were found in Slovenia and Hungary. The current distribution of diploids overlapped with the modelled paleodistribution (22 kyr BP), except Austria and the Carpathians, which are proposed to be colonized later on from refugia in the Balkans. Current and historical presence of diploids from the R. auricomus complex is suggested also for the foothills of the Caucasus. Based on comparisons of the climatic preferences polyploids from the R. auricomus complex occupy slightly drier and colder habitats than the diploids. The change of reproductive mode and selection due to competition with the diploid ancestors may have facilitated the establishment of polyploids within the R. auricomus complex in environments slightly cooler and drier, than those tolerated by diploid ancestors. Much broader distribution of polyploid apomicts may have been achieved due to faster colonization mediated by uniparental reproductive system.

Climate Impact of Solar Variability

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

1990-01-01

The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

Climate change and the Rocky Mountains: Chapter 20

USGS Publications Warehouse

Byrne, James M.; Fagre, Daniel B.; MacDonald, Ryan; Muhlfeld, Clint C.

2014-01-01

For at least half of the year, the Rocky Mountains are shrouded in snow that feeds a multitude of glaciers. Snow and ice eventually melt into rivers that have eroded deep valleys that contain rich aquatic and terrestrial ecosystems. Because the Rocky Mountains are the major divide on the continent, rainfall and melt water from glaciers and snowfields feed major river systems that run to the Pacific, Atlantic, and Arctic oceans. The Rockies truly are the water tower for much of North America, and part of the Alpine backbone of North and South America. For purposes of this chapter, we limit our discussion to the Rocky Mountains of the Canadian provinces of Alberta and British Columbia, and the U.S. states of Montana, Idaho, Wyoming, and Colorado. Similar to other mountain systems, the altitude of the Rocky Mountains condenses the weather, climate and ecosystems of thousands of kilometres of latitude into very short vertical distances. In one good day, a strong hiker can journey by foot from the mid-latitude climates of the great plains of North America to an arctic climate near the top of Rocky Mountain peaks. The steep climatic gradients of mountain terrain create some of the most diverse ecosystems in the world, but it is those rapid changes in microclimate and ecology that make mountains sensitive to climate change. The energy budget in mountains varies dramatically not only with elevation but with slope and aspect. A modest change in the slope of the terrain over short distances may radically change the solar radiation available in that location. Shaded or north facing slopes have very different microclimates than the same elevations in a sunlit location, or for a hill slope facing south. The complexities associated with the mountain terrain of the Rockies compound complexities of weather and climate to create diverse, amazing ecosystems. This chapter addresses the impacts of climate change on Rocky Mountain ecosystems in light of their complexities and sensitivities. The chapter emphasizes how climate change affects aquatic resources of the Rockies because they are impacted so directly by the changing snow and ice regimes. The chapter also suggests some approaches for coping with these impacts. Climate change is real and ever present, and the role of each of us in changing the climate is also real and present. The Rocky Mountains are a vast and complex region that is valuable both for resources and ecosystems, but the Rockies cannot provide the valuable resources we need, unless we protect and conserve mountain ecosystems. Hopefully this discussion of the major changes ongoing in the Rocky Mountains due to climate change will add to the collective societal will to minimize this change in the future.

Using the CLEAN educational resource collection for building three-dimensional lessons to teach the climate system

NASA Astrophysics Data System (ADS)

Gold, A. U.; Sullivan, S. M.; Manning, C. L. B.; Ledley, T. S.; Youngman, E.; Taylor, J.; Niepold, F., III; Kirk, K.; Lockwood, J.; Bruckner, M. Z.; Fox, S.

2017-12-01

The impacts of climate change are a critical societal challenge of the 21st century. Educating students about the globally connected climate system is key in supporting the development of mitigation and adaptation strategies. Systems thinking is required for students to understand the complex, dynamic climate systems and the role that humans play within them. The interdisciplinary nature of climate science challenges educators, who often don't have formal training in climate science, to identify resources that are scientifically accurate before weaving them together into units that teach about the climate system. The Climate Literacy and Energy Awareness Network (CLEAN) supports this work by providing over 700 peer-reviewed, classroom-ready resources on climate and energy topics. The resource collection itself provide only limited instructional guidance, so educators need to weave the resources together to build multi-dimensional lessons that develop systems thinking skills. The Next Generation Science Standards (NGSS) science standards encourage educators to teach science in a 3-dimensional approach that trains students in systems thinking. The CLEAN project strives to help educators design NGSS-style, three-dimensional lessons about the climate system. Two approaches are currently being modeled on the CLEAN web portal. The first is described in the CLEAN NGSS "Get Started Guide" which follows a step-by-step process starting with the Disciplinary Core Idea and then interweaves the Cross-Cutting Concepts (CCC) and the Science and Engineering Practices (SEP) based on the teaching strategy chosen for the lesson or unit topic. The second model uses a climate topic as a starting place and the SEP as the guide through a four-step lesson sequence called "Earth Systems Investigations". Both models use CLEAN reviewed lessons as the core activity but provide the necessary framework for classroom implementation. Sample lessons that were developed following these two approaches are provided on the CLEAN web portal (cleanet.org).

Urbanism, climate change and health: systems approaches to governance.

PubMed

Capon, Anthony G; Synnott, Emma S; Holliday, Sue

2009-01-01

Effective action on climate change health impacts and vulnerability will require systems approaches and integrated policy and planning responses from a range of government agencies. Similar responses are needed to address other complex problems, such as the obesity epidemic. Local government, with its focus on the governance of place, will have a key role in responding to these convergent agendas. Industry can also be part of the solution - indeed it must be, because it has a lead role in relevant sectors. Understanding the co-benefits for health of climate mitigation actions will strengthen the case for early action. There is a need for improved decision support tools to inform urban governance. These tools should be based on a systems approach and should incorporate a spatial perspective.

Unexpected Results are Usually Wrong, but Often Interesting

NASA Astrophysics Data System (ADS)

Huber, M.

2014-12-01

In climate modeling, an unexpected result is usually wrong, arising from some sort of mistake. Despite the fact that we all bemoan uncertainty in climate, the field is underlain by a robust, successful body of theory and any properly conducted modeling experiment is posed and conducted within that context. Consequently, if results from a complex climate model disagree with theory or from expectations from simpler models, much skepticism is in order. But, this exposes the fundamental tension of using complex, sophisticated models. If simple models and theory were perfect there would be no reason for complex models--the entire point of sophisticated models is to see if unexpected phenomena arise as emergent properties of the system. In this talk, I will step through some paleoclimate examples, drawn from my own work, of unexpected results that emerge from complex climate models arising from mistakes of two kinds. The first kind of mistake, is what I call a 'smart mistake'; it is an intentional incorporation of assumptions, boundary conditions, or physics that is in violation of theoretical or observational constraints. The second mistake, a 'dumb mistake', is just that, an unintentional violation. Analysis of such mistaken simulations provides some potentially novel and certainly interesting insights into what is possible and right in paleoclimate modeling by forcing the reexamination of well-held assumptions and theories.

Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate

NASA Astrophysics Data System (ADS)

Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.

2013-08-01

This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.

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.

The impact of climate change on smallholder and subsistence agriculture.

PubMed

Morton, John F

2007-12-11

Some of the most important impacts of global climate change will be felt among the populations, predominantly in developing countries, referred to as "subsistence" or "smallholder" farmers. Their vulnerability to climate change comes both from being predominantly located in the tropics, and from various socioeconomic, demographic, and policy trends limiting their capacity to adapt to change. However, these impacts will be difficult to model or predict because of (i) the lack of standardised definitions of these sorts of farming system, and therefore of standard data above the national level, (ii) intrinsic characteristics of these systems, particularly their complexity, their location-specificity, and their integration of agricultural and nonagricultural livelihood strategies, and (iii) their vulnerability to a range of climate-related and other stressors. Some recent work relevant to these farming systems is reviewed, a conceptual framework for understanding the diverse forms of impacts in an integrated manner is proposed, and future research needs are identified.

An Approach to Understanding Complex Socio-Economic Impacts and Responses to Climate Disruption in the Chesapeake Bay Region

NASA Astrophysics Data System (ADS)

Schaefer, R. K.; Nix, M.; Ihde, A. G.; Paxton, L. J.; Weiss, M.; Simpkins, S.; Fountain, G. H.; APl GAIA Team

2011-12-01

In this paper we describe the application of a proven methodology for modeling the complex social and economic interactions of a system under stress to the regional issues that are tied to global climate disruption. Under the auspices of the GAIA project (http://gaia.jhuapl.edu), we have investigated simulating the complex interplay between climate, politics, society, industry, and the environment in the Chesapeake Bay Watershed and associated geographic areas of Maryland, Virginia, and Pennsylvania. This Chesapeake Bay simulation draws on interrelated geophysical and climate models to support decision-making analysis about the Bay. In addition to physical models, however, human activity is also incorporated via input and output calculations. For example, policy implications are modeled in relation to business activities surrounding fishing, farming, industry and manufacturing, land development, and tourism. This approach fosters collaboration among subject matter experts to advance a more complete understanding of the regional impacts of climate change. Simulated interactive competition, in which teams of experts are assigned conflicting objectives in a controlled environment, allow for subject exploration which avoids trivial solutions that neglect the possible responses of affected parties. Results include improved planning, the anticipation of areas of conflict or high risk, and the increased likelihood of developing mutually acceptable solutions.

Response of the Vegetation-Climate System to High Temperature (Invited)

NASA Astrophysics Data System (ADS)

Berry, J. A.

2009-12-01

High temperature extremes may lead to inhibition of photosynthesis and stomatal closure at the leaf scale. When these responses occur over regional scales, they can initiate a positive feedback loop in the coupled vegetation-climate system. The fraction of net radiation that is used by the land surface to evaporate water decreases leading to deeper, drier boundary layers, fewer clouds, increased solar radiation reaching the surface, and possibility reduced precipitation. These interactions within the vegetation-climate system may amplify natural (or greenhouse gas forced) variations in temperature and further stress the vegetation. Properly modeling of this system depends, among other things, on getting the plant responses to high temperature correct. I will review the current state of this problem and present some studies of rain forest trees to high temperature and drought conducted in the Biosphere 2 enclosure that illustrate how experiments in controlled systems can contribute to our understanding of complex systems to extreme events.

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.

Sensitivity of the Gravity Recovery and Climate Experiment (GRACE) to the complexity of aquifer systems for monitoring of groundwater

NASA Astrophysics Data System (ADS)

Katpatal, Yashwant B.; Rishma, C.; Singh, Chandan K.

2018-05-01

The Gravity Recovery and Climate Experiment (GRACE) satellite mission is aimed at assessment of groundwater storage under different terrestrial conditions. The main objective of the presented study is to highlight the significance of aquifer complexity to improve the performance of GRACE in monitoring groundwater. Vidarbha region of Maharashtra, central India, was selected as the study area for analysis, since the region comprises a simple aquifer system in the western region and a complex aquifer system in the eastern region. Groundwater-level-trend analyses of the different aquifer systems and spatial and temporal variation of the terrestrial water storage anomaly were studied to understand the groundwater scenario. GRACE and its field application involve selecting four pixels from the GRACE output with different aquifer systems, where each GRACE pixel encompasses 50-90 monitoring wells. Groundwater storage anomalies (GWSA) are derived for each pixel for the period 2002 to 2015 using the Release 05 (RL05) monthly GRACE gravity models and the Global Land Data Assimilation System (GLDAS) land-surface models (GWSAGRACE) as well as the actual field data (GWSAActual). Correlation analysis between GWSAGRACE and GWSAActual was performed using linear regression. The Pearson and Spearman methods show that the performance of GRACE is good in the region with simple aquifers; however, performance is poorer in the region with multiple aquifer systems. The study highlights the importance of incorporating the sensitivity of GRACE in estimation of groundwater storage in complex aquifer systems in future studies.

Planning for climate change: The need for mechanistic systems-based approaches to study climate change impacts on diarrheal diseases.

PubMed

Mellor, Jonathan E; Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara

2016-04-01

Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

NASA Astrophysics Data System (ADS)

Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

2016-12-01

Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

Towards Improved Linkage of Disaster Risk Reduction and Climate Change Adaptation in Health: A Review.

PubMed

Banwell, Nicola; Rutherford, Shannon; Mackey, Brendan; Chu, Cordia

2018-04-18

Climate change and climate-sensitive disasters significantly impact health. Linking Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) is essential for addressing these ever present, complex and increasing risks. Recent calls have been made to build these links in health. However, there is a need to clearly articulate why linking DRR and CCA is important in health. Furthermore, little is known about how DRR and CCA should be linked in health. By extensively examining relevant literature, this review presents the current state of knowledge of linking DRR and CCA in health. This includes the potential for maximising conceptual synergies such as building resilience, and reducing vulnerability and risk. Additionally, technical and operational synergies are identified to link DRR and CCA in health, including: policy, Early Warning Systems, vulnerability and risk assessment, health systems strengthening, infrastructure resilience, disaster preparedness and response, and health impact pathways. Public health actors have a central role in building these links due to their expertise, work functions, and experience in addressing complex health risks. The review concludes with recommendations for future research, including how to better link DRR and CCA in health; and the opportunities, challenges and enablers to build and sustain these links.

Climate Narratives: Combing multiple sources of information to develop risk management strategies for a municipal water utility

NASA Astrophysics Data System (ADS)

Yates, D. N.; Basdekas, L.; Rajagopalan, B.; Stewart, N.

2013-12-01

Municipal water utilities often develop Integrated Water Resource Plans (IWRP), with the goal of providing a reliable, sustainable water supply to customers in a cost-effective manner. Colorado Springs Utilities, a 5-service provider (potable and waste water, solid waste, natural gas and electricity) in Colorado USA, recently undertook an IWRP. where they incorporated water supply, water demand, water quality, infrastructure reliability, environmental protection, and other measures within the context of complex water rights, such as their critically important 'exchange potential'. The IWRP noted that an uncertain climate was one of the greatest sources of uncertainty to achieving a sustainable water supply to a growing community of users. We describe how historic drought, paleo-climate, and climate change projections were blended together into climate narratives that informed a suite of water resource systems models used by the utility to explore the vulnerabilities of their water systems.

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management

NASA Astrophysics Data System (ADS)

Lee, T.; Tung, C.; Chung, N.

2007-12-01

In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.

Urban drainage system planning and design--challenges with climate change and urbanization: a review.

PubMed

Yazdanfar, Zeinab; Sharma, Ashok

2015-01-01

Urban drainage systems are in general failing in their functions mainly due to non-stationary climate and rapid urbanization. As these systems are becoming less efficient, issues such as sewer overflows and increase in urban flooding leading to surge in pollutant loads to receiving water bodies are becoming pervasive rapidly. A comprehensive investigation is required to understand these factors impacting the functioning of urban drainage, which vary spatially and temporally and are more complex when weaving together. It is necessary to establish a cost-effective, integrated planning and design framework for every local area by incorporating fit for purpose alternatives. Carefully selected adaptive measures are required for the provision of sustainable drainage systems to meet combined challenges of climate change and urbanization. This paper reviews challenges associated with urban drainage systems and explores limitations and potentials of different adaptation alternatives. It is hoped that the paper would provide drainage engineers, water planners, and decision makers with the state of the art information and technologies regarding adaptation options to increase drainage systems efficiency under changing climate and urbanization.

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

Moving toward climate-informed agricultural decision support - can we use PRISM data for more than just monthly averages?

USDA-ARS?s Scientific Manuscript database

Decision support systems/models for agriculture are varied in target application and complexity, ranging from simple worksheets to near real-time forecast systems requiring significant computational and manpower resources. Until recently, most such decision support systems have been constructed with...

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

USGS Publications Warehouse

Symstad, Amy J.; Fisichelli, Nicholas A.; Miller, Brian W.; Rowland, Erika; Schuurman, Gregor W.

2017-01-01

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

Forests and climate change: forcings, feedbacks, and the climate benefits of forests.

PubMed

Bonan, Gordon B

2008-06-13

The world's forests influence climate through physical, chemical, and biological processes that affect planetary energetics, the hydrologic cycle, and atmospheric composition. These complex and nonlinear forest-atmosphere interactions can dampen or amplify anthropogenic climate change. Tropical, temperate, and boreal reforestation and afforestation attenuate global warming through carbon sequestration. Biogeophysical feedbacks can enhance or diminish this negative climate forcing. Tropical forests mitigate warming through evaporative cooling, but the low albedo of boreal forests is a positive climate forcing. The evaporative effect of temperate forests is unclear. The net climate forcing from these and other processes is not known. Forests are under tremendous pressure from global change. Interdisciplinary science that integrates knowledge of the many interacting climate services of forests with the impacts of global change is necessary to identify and understand as yet unexplored feedbacks in the Earth system and the potential of forests to mitigate climate change.

CO2, the greenhouse effect and global warming: from the pioneering work of Arrhenius and Callendar to today's Earth System Models.

PubMed

Anderson, Thomas R; Hawkins, Ed; Jones, Philip D

2016-09-01

Climate warming during the course of the twenty-first century is projected to be between 1.0 and 3.7°C depending on future greenhouse gas emissions, based on the ensemble-mean results of state-of-the-art Earth System Models (ESMs). Just how reliable are these projections, given the complexity of the climate system? The early history of climate research provides insight into the understanding and science needed to answer this question. We examine the mathematical quantifications of planetary energy budget developed by Svante Arrhenius (1859-1927) and Guy Stewart Callendar (1898-1964) and construct an empirical approximation of the latter, which we show to be successful at retrospectively predicting global warming over the course of the twentieth century. This approximation is then used to calculate warming in response to increasing atmospheric greenhouse gases during the twenty-first century, projecting a temperature increase at the lower bound of results generated by an ensemble of ESMs (as presented in the latest assessment by the Intergovernmental Panel on Climate Change). This result can be interpreted as follows. The climate system is conceptually complex but has at its heart the physical laws of radiative transfer. This basic, or "core" physics is relatively straightforward to compute mathematically, as exemplified by Callendar's calculations, leading to quantitatively robust projections of baseline warming. The ESMs include not only the physical core but also climate feedbacks that introduce uncertainty into the projections in terms of magnitude, but not sign: positive (amplification of warming). As such, the projections of end-of-century global warming by ESMs are fundamentally trustworthy: quantitatively robust baseline warming based on the well-understood physics of radiative transfer, with extra warming due to climate feedbacks. These projections thus provide a compelling case that global climate will continue to undergo significant warming in response to ongoing emissions of CO 2 and other greenhouse gases to the atmosphere. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Low order climate models as a tool for cross-disciplinary collaboration

NASA Astrophysics Data System (ADS)

Newton, R.; Pfirman, S. L.; Tremblay, B.; Schlosser, P.

2014-12-01

Human impacts on climate are pervasive and significant and project future states cannot be projected without taking human influence into account. We recently helped convene a meeting of climatologists, policy analysts, lawyers and social scientists to discuss the dramatic loss in Arctic summer sea ice. A dialogue emerged around distinct time scales in the integrated human/natural climate system. Climate scientists tended to discuss engineering solutions as though they could be implemented immediately, whereas lags of 2 or more decades were estimated by social scientists for societal shifts and similar lags were cited for deployment by the engineers. Social scientists tended to project new climate states virtually overnight, while climatologists described time scales of decades to centuries for the system to respond to changes in forcing functions. For the conversation to develop, the group had to come to grips with an increasingly complex set of transient effect time scales and lags between decisions, changes in forcing, and system outputs. We use several low-order dynamical system models to explore mismatched timescales, ranges of lags, and uncertainty in cost estimates on climate outcomes, focusing on Arctic-specific issues. In addition to lessons regarding what is/isn't feasible from a policy and engineering perspective, these models provide a useful tool to concretize cross-disciplinary thinking. They are fast and easy to iterate through a large region of the problem space, while including surprising complexity in their evolution. Thus they are appropriate for investigating the implications of policy in an efficient, but not unrealistic physical setting. (Earth System Models, by contrast, can be too resource- and time-intensive for iteratively testing "what if" scenarios in cross-disciplinary collaborations.) Our runs indicate, for example, that the combined social, engineering and climate physics lags make it extremely unlikely that an ice-free summer ecology in the Arctic can be avoided. Further, if prospective remediation strategies are successful, a return to perennial ice conditions between one and two centuries from now is entirely likely, with interesting and large impacts on Northern economies.

Nonlinear Synergistic Emergence and Predictability in Complex Systems: Theory and Hydro-Climatic Applications

NASA Astrophysics Data System (ADS)

Perdigão, Rui A. P.; Hall, Julia; Pires, Carlos A. L.; Blöschl, Günter

2017-04-01

Classical and stochastic dynamical system theories assume structural coherence and dynamic recurrence with invariants of motion that are not necessarily so. These are grounded on the unproven assumption of universality in the dynamic laws derived from statistical kinematic evaluation of non-representative empirical records. As a consequence, the associated formulations revolve around a restrictive set of configurations and intermittencies e.g. in an ergodic setting, beyond which any predictability is essentially elusive. Moreover, dynamical systems are fundamentally framed around dynamic codependence among intervening processes, i.e. entail essentially redundant interactions such as couplings and feedbacks. That precludes synergistic cooperation among processes that, whilst independent from each other, jointly produce emerging dynamic behaviour not present in any of the intervening parties. In order to overcome these fundamental limitations, we introduce a broad class of non-recursive dynamical systems that formulate dynamic emergence of unprecedented states in a fundamental synergistic manner, with fundamental principles in mind. The overall theory enables innovations to be predicted from the internal system dynamics before any a priori information is provided about the associated dynamical properties. The theory is then illustrated to anticipate, from non-emergent records, the spatiotemporal emergence of multiscale hyper chaotic regimes, critical transitions and structural coevolutionary changes in synthetic and real-world complex systems. Example applications are provided within the hydro-climatic context, formulating and dynamically forecasting evolving hydro-climatic distributions, including the emergence of extreme precipitation and flooding in a structurally changing hydro-climate system. Validation is then conducted with a posteriori verification of the simulated dynamics against observational records. Agreement between simulations and observations is confirmed with robust nonlinear information diagnostics.

Unraveling multiple changes in complex climate time series using Bayesian inference

NASA Astrophysics Data System (ADS)

Berner, Nadine; Trauth, Martin H.; Holschneider, Matthias

2016-04-01

Change points in time series are perceived as heterogeneities in the statistical or dynamical characteristics of observations. Unraveling such transitions yields essential information for the understanding of the observed system. The precise detection and basic characterization of underlying changes is therefore of particular importance in environmental sciences. We present a kernel-based Bayesian inference approach to investigate direct as well as indirect climate observations for multiple generic transition events. In order to develop a diagnostic approach designed to capture a variety of natural processes, the basic statistical features of central tendency and dispersion are used to locally approximate a complex time series by a generic transition model. A Bayesian inversion approach is developed to robustly infer on the location and the generic patterns of such a transition. To systematically investigate time series for multiple changes occurring at different temporal scales, the Bayesian inversion is extended to a kernel-based inference approach. By introducing basic kernel measures, the kernel inference results are composed into a proxy probability to a posterior distribution of multiple transitions. Thus, based on a generic transition model a probability expression is derived that is capable to indicate multiple changes within a complex time series. We discuss the method's performance by investigating direct and indirect climate observations. The approach is applied to environmental time series (about 100 a), from the weather station in Tuscaloosa, Alabama, and confirms documented instrumentation changes. Moreover, the approach is used to investigate a set of complex terrigenous dust records from the ODP sites 659, 721/722 and 967 interpreted as climate indicators of the African region of the Plio-Pleistocene period (about 5 Ma). The detailed inference unravels multiple transitions underlying the indirect climate observations coinciding with established global climate events.

Handling Uncertainty in Palaeo-Climate Models and Data

NASA Astrophysics Data System (ADS)

Voss, J.; Haywood, A. M.; Dolan, A. M.; Domingo, D.

2017-12-01

The study of palaeoclimates can provide data on the behaviour of the Earth system with boundary conditions different from the ones we observe in the present. One of the main challenges in this approach is that data on past climates comes with large uncertainties, since quantities of interest cannot be observed directly, but must be derived from proxies instead. We consider proxy-derived data from the Pliocene (around 3 millions years ago; the last interval in Earth history when CO2 was at modern or near future levels) and contrast this data to the output of complex climate models. In order to perform a meaningful data-model comparison, uncertainties must be taken into account. In this context, we discuss two examples of complex data-model comparison problems. Both examples have in common that they involve fitting a statistical model to describe how the output of the climate simulations depends on various model parameters, including atmospheric CO2 concentration and orbital parameters (obliquity, excentricity, and precession). This introduces additional uncertainties, but allows to explore a much larger range of model parameters than would be feasible by only relying on simulation runs. The first example shows how Gaussian process emulators can be used to perform data-model comparison when simulation runs only differ in the choice of orbital parameters, but temperature data is given in the (somewhat inconvenient) form of "warm peak averages". The second example shows how a simpler approach, based on linear regression, can be used to analyse a more complex problem where we use a larger and more varied ensemble of climate simulations with the aim to estimate Earth System Sensitivity.

"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.

Climate models with delay differential equations

NASA Astrophysics Data System (ADS)

Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

2017-11-01

A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

Climate models with delay differential equations.

PubMed

Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M

2017-11-01

A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

Building Climate Resilience in the Blue Nile/Abay Highlands: A Role for Earth System Sciences

PubMed Central

Zaitchik, Benjamin F.; Simane, Belay; Habib, Shahid; Anderson, Martha C.; Ozdogan, Mutlu; Foltz, Jeremy D.

2012-01-01

The Blue Nile (Abay) Highlands of Ethiopia are characterized by significant interannual climate variability, complex topography and associated local climate contrasts, erosive rains and erodible soils, and intense land pressure due to an increasing population and an economy that is almost entirely dependent on smallholder, low-input agriculture. As a result, these highland zones are highly vulnerable to negative impacts of climate variability. As patterns of variability and precipitation intensity alter under anthropogenic climate change, there is concern that this vulnerability will increase, threatening economic development and food security in the region. In order to overcome these challenges and to enhance sustainable development in the context of climate change, it is necessary to establish climate resilient development strategies that are informed by best-available Earth System Science (ESS) information. This requirement is complicated by the fact that climate projections for the Abay Highlands contain significant and perhaps irreducible uncertainties. A critical challenge for ESS, then, is to generate and to communicate meaningful information for climate resilient development in the context of a highly uncertain climate forecast. Here we report on a framework for applying ESS to climate resilient development in the Abay Highlands, with a focus on the challenge of reducing land degradation. PMID:22470302

Climate regulation services by urban lakes in Bucharest city

NASA Astrophysics Data System (ADS)

Ioja, Cristian; Cheval, Sorin; Vanau, Gabriel; Sandric, Ionut; Onose, Diana; Carstea, Elfrida

2017-04-01

Urban ecosystems services assessment is an important challenge for practitioners, due to the high complexity of relations between urban systems components, high vulnerability to climate change, and consequences in social-economical systems. Urban lakes represent a significant component in more European cities (average 5% of total surface). Adequate urban management supports diverse benefits of urban lakes: clean water availability, mediation of waste, toxics and other nuisance, air quality and climate regulation, support for physical, intelectual or spiritual interactions. Due to underestimation of climate change and misfit urban planning decision, these benefits may be lost or chaged into diservices. The aim of the paper is to assess the changes in terms of the urban lakes contribution role to regulate urban climate, using the Bucharest as case study. Using sensors and Modis, Sentinel and Landsat images, the paper experiments the evolution of climate regulation services of urban lakes under the pressure of urbanisation and climate change between 2008 and 2015. Urban lakes management has to include specific measures in order to help the cities to become more sustainable, resilient, liveable and healthly.

Climate change and human health: a One Health approach.

PubMed

Patz, Jonathan A; Hahn, Micah B

2013-01-01

Climate change adds complexity and uncertainty to human health issues such as emerging infectious diseases, food security, and national sustainability planning that intensify the importance of interdisciplinary and collaborative research. Collaboration between veterinary, medical, and public health professionals to understand the ecological interactions and reactions to flux in a system can facilitate clearer understanding of climate change impacts on environmental, animal, and human health. Here we present a brief introduction to climate science and projections for the next century and a review of current knowledge on the impacts of climate-driven environmental change on human health. We then turn to the links between ecological and evolutionary responses to climate change and health. The literature on climate impacts on biological systems is rich in both content and historical data, but the connections between these changes and human health is less understood. We discuss five mechanisms by which climate changes impacts on biological systems will be felt by the human population: Modifications in Vector, Reservoir, and Pathogen Lifecycles; Diseases of Domestic and Wild Animals and Plants; Disruption of Synchrony Between Interacting Species; Trophic Cascades; and Alteration or Destruction of Habitat. Each species responds to environmental changes differently, and in order to predict the movement of disease through ecosystems, we have to rely on expertise from the fields of veterinary, medical, and public health, and these health professionals must take into account the dynamic nature of ecosystems in a changing climate.

Simulation of Optimal Decision-Making Under the Impacts of Climate Change.

PubMed

Møller, Lea Ravnkilde; Drews, Martin; Larsen, Morten Andreas Dahl

2017-07-01

Climate change causes transformations to the conditions of existing agricultural practices appointing farmers to continuously evaluate their agricultural strategies, e.g., towards optimising revenue. In this light, this paper presents a framework for applying Bayesian updating to simulate decision-making, reaction patterns and updating of beliefs among farmers in a developing country, when faced with the complexity of adapting agricultural systems to climate change. We apply the approach to a case study from Ghana, where farmers seek to decide on the most profitable of three agricultural systems (dryland crops, irrigated crops and livestock) by a continuous updating of beliefs relative to realised trajectories of climate (change), represented by projections of temperature and precipitation. The climate data is based on combinations of output from three global/regional climate model combinations and two future scenarios (RCP4.5 and RCP8.5) representing moderate and unsubstantial greenhouse gas reduction policies, respectively. The results indicate that the climate scenario (input) holds a significant influence on the development of beliefs, net revenues and thereby optimal farming practices. Further, despite uncertainties in the underlying net revenue functions, the study shows that when the beliefs of the farmer (decision-maker) opposes the development of the realised climate, the Bayesian methodology allows for simulating an adjustment of such beliefs, when improved information becomes available. The framework can, therefore, help facilitating the optimal choice between agricultural systems considering the influence of climate change.

Development of a system emulating the global carbon cycle in Earth system models

NASA Astrophysics Data System (ADS)

Tachiiri, K.; Hargreaves, J. C.; Annan, J. D.; Oka, A.; Abe-Ouchi, A.; Kawamiya, M.

2010-08-01

Recent studies have indicated that the uncertainty in the global carbon cycle may have a significant impact on the climate. Since state of the art models are too computationally expensive for it to be possible to explore their parametric uncertainty in anything approaching a comprehensive fashion, we have developed a simplified system for investigating this problem. By combining the strong points of general circulation models (GCMs), which contain detailed and complex processes, and Earth system models of intermediate complexity (EMICs), which are quick and capable of large ensembles, we have developed a loosely coupled model (LCM) which can represent the outputs of a GCM-based Earth system model, using much smaller computational resources. We address the problem of relatively poor representation of precipitation within our EMIC, which prevents us from directly coupling it to a vegetation model, by coupling it to a precomputed transient simulation using a full GCM. The LCM consists of three components: an EMIC (MIROC-lite) which consists of a 2-D energy balance atmosphere coupled to a low resolution 3-D GCM ocean (COCO) including an ocean carbon cycle (an NPZD-type marine ecosystem model); a state of the art vegetation model (Sim-CYCLE); and a database of daily temperature, precipitation, and other necessary climatic fields to drive Sim-CYCLE from a precomputed transient simulation from a state of the art AOGCM. The transient warming of the climate system is calculated from MIROC-lite, with the global temperature anomaly used to select the most appropriate annual climatic field from the pre-computed AOGCM simulation which, in this case, is a 1% pa increasing CO2 concentration scenario. By adjusting the effective climate sensitivity (equivalent to the equilibrium climate sensitivity for an energy balance model) of MIROC-lite, the transient warming of the LCM could be adjusted to closely follow the low sensitivity (with an equilibrium climate sensitivity of 4.0 K) version of MIROC3.2. By tuning of the physical and biogeochemical parameters it was possible to reasonably reproduce the bulk physical and biogeochemical properties of previously published CO2 stabilisation scenarios for that model. As an example of an application of the LCM, the behavior of the high sensitivity version of MIROC3.2 (with a 6.3 K equilibrium climate sensitivity) is also demonstrated. Given the highly adjustable nature of the model, we believe that the LCM should be a very useful tool for studying uncertainty in global climate change, and we have named the model, JUMP-LCM, after the name of our research group (Japan Uncertainty Modelling Project).

An application of sample entropy to precipitation in Paraíba State, Brazil

NASA Astrophysics Data System (ADS)

Xavier, Sílvio Fernando Alves; da Silva Jale, Jader; Stosic, Tatijana; dos Santos, Carlos Antonio Costa; Singh, Vijay P.

2018-05-01

A climate system is characterized to be a complex non-linear system. In order to describe the complex characteristics of precipitation series in Paraíba State, Brazil, we aim the use of sample entropy, a kind of entropy-based algorithm, to evaluate the complexity of precipitation series. Sixty-nine meteorological stations are distributed over four macroregions: Zona da Mata, Agreste, Borborema, and Sertão. The results of the analysis show that intricacies of monthly average precipitation have differences in the macroregions. Sample entropy is able to reflect the dynamic change of precipitation series providing a new way to investigate complexity of hydrological series. The complexity exhibits areal variation of local water resource systems which can influence the basis for utilizing and developing resources in dry areas.

An Enhanced Engineering Perspective of Global Climate Systems and Statistical Formulation of Terrestrial CO2 Exchanges

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

Dai, Yuanshun; Baek, Seung H.; Garcia-Diza, Alberto

2012-01-01

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of CO2 exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO2 fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO2 fluxes.more » To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as Stochastic Filtering Analysis of Variance (SFANOVA). The CO2 flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction and globalization capabilities of the proposed engineering approach and the SF-ANOVA technology. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.« less

The Software Architecture of Global Climate Models

NASA Astrophysics Data System (ADS)

Alexander, K. A.; Easterbrook, S. M.

2011-12-01

It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

Soil chemical weathering under morphologic and climatic controls in the Northern Rockies, Montana

NASA Astrophysics Data System (ADS)

Benjaram, S. S.; Dixon, J. L.

2015-12-01

Climate influences soil weathering via moisture availability and temperatures, but globally physical erosion rate appears to be a more important control on weathering rate than climate. Understanding these links requires investigation into landscapes where the climate's influence on weathering is discernable despite the signal of physical erosion rate—in kinetically limited regimes. However, in these systems, rapid erosion rates and complex morphologies add complexity and heterogeneity to soil weathering. To investigate the dual controls of landscape morphology and climate on chemical weathering, we quantify soil distribution, thickness, and weathering extent by focusing on catchments within two adjacent mountain ranges in the Northern Rockies. The Bitterroot Mtns present previously-glaciated valleys with steep ridges and high present-day MAP, which contrast with the drier and more gentle, nonglaciated hillslopes of the Sapphire Mtns to the east. We use field and remotely sensed data to quantify soil distribution and thickness, and elemental geochemistry to measure the variability of chemical weathering across these systems.Mean slopes in the Bitterroots are ~1.3x higher than those in our Sapphire catchment, leading to large differences in soil distribution. Initial mapping of soils using remotely sensed data and rock exposure indices (REI) indicate that ~50% of the Bitterroot system is bare of soil, compared to <5% in the Sapphire system. REIs are distinct between these systems, with ~10˚ difference in slope thresholds for soil cover. Additionally, field data indicate that sparse soils of the Bitterroots are significantly thinner than those in Sapphire system (B=17±2cm, n=161; S=32±3, n=31). Initial XRF data suggest soil weathering intensity is more than two times greater in the Sapphires. These results suggest that the morphologic landscape legacy left by now-extinct glaciers imposes a kinetic limitation on soil weathering, even despite high modern moisture availability.

Integrated modeling of land-use change: the role of coupling, interactions and feedbacks between the human and Earth systems

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Ejaz, Q.; Winchester, N.; Paltsev, S.; Reilly, J. M.

2016-12-01

Land-use change integrates a large number of components of the human and Earth systems, including climate, energy, water, and land. These complex coupling elements, interactions and feedbacks take place on a variety of space and time scales, thus increasing the complexity of land-use change modeling frameworks. In this study, we aim to identify which coupling elements, interactions and feedbacks are important for modeling land-use change, both at the global and regional level. First, we review the existing land-use change modeling framework used to develop land-use change projections for the Representative Concentration Pathways (RCP) scenarios. In such framework, land-use change is simulated by Integrated Assessment Models (IAMs) and mainly influenced by economic, energy, demographic and policy drivers. IAMs focus on representing the demand for agriculture and forestry goods (crops for food and bioenergy, forest products for construction and bioenergy), the interactions with other sectors of the economy and trade between various regions of the world. Then, we investigate how important various coupling elements and feedbacks with the Earth system are for projections of land-use change at the global and regional level. We focus on the following: i) the climate impacts on land productivity and greenhouse gas emissions, which requires climate change information and coupling to a terrestrial ecosystem model/crop model; ii) the climate and economic impacts on irrigation availability, which requires coupling the LUC modeling framework to a water resources management model and disaggregating rainfed and irrigated croplands; iii) the feedback of land-use change on the global and regional climate system through land-use change emissions and changes in the surface albedo and hydrology, which requires coupling to an Earth system model. Finally, we conclude our study by highlighting the current lack of clarity in how various components of the human and Earth systems are coupled in IAMs , and the need for a lexicon that is agreed upon by the IAM community.

The Nested Regional Climate Model: An Approach Toward Prediction Across Scales

NASA Astrophysics Data System (ADS)

Hurrell, J. W.; Holland, G. J.; Large, W. G.

2008-12-01

The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.

2016 International Land Model Benchmarking (ILAMB) Workshop Report

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

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

New climatic classification of Nepal

NASA Astrophysics Data System (ADS)

Karki, Ramchandra; Talchabhadel, Rocky; Aalto, Juha; Baidya, Saraju Kumar

2016-08-01

Although it is evident that Nepal has an extremely wide range of climates within a short latitudinal distance, there is a lack of comprehensive research in this field. The climatic zoning in a topographically complex country like Nepal has important implications for the selection of scientific station network design and climate model verification, as well as for studies examining the effects of climate change in terms of shifting climatic boundaries and vegetation in highly sensitive environments. This study presents a new high-resolution climate map of Nepal on the basis of long-term (1981-2010) monthly precipitation data for 240 stations and mean air temperature data for 74 stations, using original and modified Köppen-Geiger climate classification systems. Climatic variables used in Köppen-Geiger system were calculated (i) at each station and (ii) interpolated to 1-km spatial resolution using kriging which accounted for latitude, longitude, and elevation. The original Köppen-Geiger scheme could not identify all five types of climate (including tropical) observed in Nepal. Hence, the original scheme was slightly modified by changing the boundary of coldest month mean air temperature value from 18 °C to 14.5 °C in order to delineate the realistic climatic condition of Nepal. With this modification, all five types of climate (including tropical) were identified. The most common dominant type of climate for Nepal is temperate with dry winter and hot summer (Cwa).

Observationally-based Metrics of Ocean Carbon and Biogeochemical Variables are Essential for Evaluating Earth System Model Projections

NASA Astrophysics Data System (ADS)

Russell, J. L.; Sarmiento, J. L.

2017-12-01

The Southern Ocean is central to the climate's response to increasing levels of atmospheric greenhouse gases as it ventilates a large fraction of the global ocean volume. Global coupled climate models and earth system models, however, vary widely in their simulations of the Southern Ocean and its role in, and response to, the ongoing anthropogenic forcing. Due to its complex water-mass structure and dynamics, Southern Ocean carbon and heat uptake depend on a combination of winds, eddies, mixing, buoyancy fluxes and topography. Understanding how the ocean carries heat and carbon into its interior and how the observed wind changes are affecting this uptake is essential to accurately projecting transient climate sensitivity. Observationally-based metrics are critical for discerning processes and mechanisms, and for validating and comparing climate models. As the community shifts toward Earth system models with explicit carbon simulations, more direct observations of important biogeochemical parameters, like those obtained from the biogeochemically-sensored floats that are part of the Southern Ocean Carbon and Climate Observations and Modeling project, are essential. One goal of future observing systems should be to create observationally-based benchmarks that will lead to reducing uncertainties in climate projections, and especially uncertainties related to oceanic heat and carbon uptake.

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

Data-Driven Synthesis for Investigating Food Systems Resilience to Climate Change

NASA Astrophysics Data System (ADS)

Magliocca, N. R.; Hart, D.; Hondula, K. L.; Munoz, I.; Shelley, M.; Smorul, M.

2014-12-01

The production, supply, and distribution of our food involves a complex set of interactions between farmers, rural communities, governments, and global commodity markets that link important issues such as environmental quality, agricultural science and technology, health and nutrition, rural livelihoods, and social institutions and equality - all of which will be affected by climate change. The production of actionable science is thus urgently needed to inform and prepare the public for the consequences of climate change for local and global food systems. Access to data that spans multiple sectors/domains and spatial and temporal scales is key to beginning to tackle such complex issues. As part of the White House's Climate Data Initiative, the USDA and the National Socio-Environmental Synthesis Center (SESYNC) are launching a new collaboration to catalyze data-driven research to enhance food systems resilience to climate change. To support this collaboration, SESYNC is developing a new "Data to Motivate Synthesis" program designed to engage early career scholars in a highly interactive and dynamic process of real-time data discovery, analysis, and visualization to catalyze new research questions and analyses that would not have otherwise been possible and/or apparent. This program will be supported by an integrated, spatially-enabled cyberinfrastructure that enables the management, intersection, and analysis of large heterogeneous datasets relevant to food systems resilience to climate change. Our approach is to create a series of geospatial abstraction data structures and visualization services that can be used to accelerate analysis and visualization across various socio-economic and environmental datasets (e.g., reconcile census data with remote sensing raster datasets). We describe the application of this approach with a pilot workshop of socio-environmental scholars that will lay the groundwork for the larger SESYNC-USDA collaboration. We discuss the particular challenges of supporting an integrated, repeatable workflow for socio-environmental data synthesis, and the advantages and limitations to using data as a launching point for interdisciplinary research projects.

Flood Protection Decision Making Within a Coupled Human and Natural System

NASA Astrophysics Data System (ADS)

O'Donnell, Greg; O'Connell, Enda

2013-04-01

Due to the perceived threat from climate change, prediction under changing climatic and hydrological conditions has become a dominant theme of hydrological research. Much of this research has been climate model-centric, in which GCM/RCM climate projections have been used to drive hydrological system models to explore potential impacts that should inform adaptation decision-making. However, adaptation fundamentally involves how humans may respond to increasing flood and drought hazards by changing their strategies, activities and behaviours which are coupled in complex ways to the natural systems within which they live and work. Humans are major agents of change in hydrological systems, and representing human activities and behaviours in coupled human and natural hydrological system models is needed to gain insight into the complex interactions that take place, and to inform adaptation decision-making. Governments and their agencies are under pressure to make proactive investments to protect people living in floodplains from the perceived increasing flood hazard. However, adopting this as a universal strategy everywhere is not affordable, particularly in times of economic stringency and given uncertainty about future climatic conditions. It has been suggested that the assumption of stationarity, which has traditionally been invoked in making hydrological risk assessments, is no longer tenable. However, before the assumption of hydrologic nonstationarity is accepted, the ability to cope with the uncertain impacts of global warming on water management via the operational assumption of hydrologic stationarity should be carefully examined. Much can be learned by focussing on natural climate variability and its inherent changes in assessing alternative adaptation strategies. A stationary stochastic multisite flood hazard model has been developed that can exhibit increasing variability/persistence in annual maximum floods, starting with the traditional assumption of independence. This has been coupled to an agent based model of how various stakeholders interact in determining where and when flood protection investments are made in a hypothetical region with multiple sites at risk from flood hazard. Monte Carlo simulation is used to explore how government agencies with finite resources might best invest in flood protection infrastructure in a highly variable climate with a high degree of future uncertainty. Insight is provided into whether proactive or reactive strategies are to be preferred in an increasingly variable climate.

Integrating Scientific Content with Context to Connect Educators with the Complexities and Consequences of Climate Change

NASA Astrophysics Data System (ADS)

Low, R.; Gosselin, D. C.; Oglesby, R. J.; Larson-Miller, C.; Thomas, J.; Mawalagedara, R.

2011-12-01

Over the past three years the Nebraska Earth Systems Education Network has designed professional development opportunities for K-12 and extension educators that integrates scientific content into the context of helping educators connect society with the complexities and consequences of climate change. Our professional development approach uses learner-, knowledge-, assessment-, and community-centered strategies to achieve our long-term goal: collaboration of scientists, educators and learners to foster civic literacy about climate change. Two NASA-funded projects, Global Climate Change Literacy for Educators (GCCE, 2009-2012), and the Educators Climatologists Learning Community (ECLC, 2011-2013), have provided the mechanism to provide teachers with scientifically sound and pedagogically relevant educational materials to improve climate and Earth systems literacy among educators. The primary product of the GCCE program is a 16-week, online, distance-delivered, asynchronous course entitled, Laboratory Earth: Human Dimensions of Climate Change. This course consists of four, four-week modules that integrate climate literacy, Earth Systems concepts, and pedagogy focused on active learning processes, building community, action research, and students' sense of place to promote action at the local level to address the challenges of climate change. Overall, the Community of Inquiry Survey (COI) indicated the course was effective in teaching content, developing a community of learners, and engaging students in experiences designed to develop content knowledge. A pre- and post- course Wilcoxan Signed Ranks Test indicated there was a statistically significant increase in participant's beliefs about their personal science teaching efficacy. Qualitative data from concept maps and content mastery assignments support a positive impact on teachers' content knowledge and classroom practice. Service Learning units seemed tohelp teachers connect course learning to their classroom teaching. In addition, qualitative data indicate that teachers' students found service learning to be highly motivational components to learning. The ECLC project, to be initiated in the fall 2011, will build on our GCCE experiences to create a sustainable virtual learning community of educators and scientists. Climate-change issues will serve as a context in which collaborative scientist-educator-teams will develop discrete, locally oriented research projects to facilitate development of confident, knowledgeable citizen-scientists within their classrooms.

Modeling Climate and Societal Resilience in the Mediterranean During the Last Millennium

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2017-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

Migrating Legacy Systems in the Global Merger & Acquisition Environment

ERIC Educational Resources Information Center

Katerattanakul, Pairin; Kam, Hwee-Joo; Lee, James J.; Hong, Soongoo

2009-01-01

The MetaFrame system migration project at WorldPharma, while driven by merger and acquisition, had faced complexities caused by both technical challenges and organizational issues in the climate of uncertainties. However, WorldPharma still insisted on instigating this post-merger system migration project. This project served to (1) consolidate the…

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

A megaregion-scale approach for assessing the impacts of climate change and strategic management decisions in the Northeast United States

NASA Astrophysics Data System (ADS)

Rosenzweig, B.; Vorosmarty, C. J.; Stewart, R. J.; Miara, A.; Lu, X.; Kicklighter, D. W.; Ehsani, N.; Wollheim, W. M.; Melillo, J. M.; Fekete, B. M.; Dilekli, N.; Duchin, F.; Gross, B.; Bhatt, V.

2014-12-01

'Megaregions' have been identified as an important new scale of geography for policy decision-making in the United States. These regions extend beyond local boundaries (ie. cities, states) to incorporate areas with linked economies, infrastructure and land-use patterns and shared climate and environmental systems, such as watersheds. The corridor of densely connected metropolitan areas and surrounding hinterlands along the U.S. east coast from Maine to Virginia is the archetype of this type of unit: The Northeast Megaregion. The Northeast faces a unique set of policy challenges including: projections of a wetter, more extreme climate, aging and underfunded infrastructure and economically distressed rural areas. Megaregion-scale policy efforts such as the Regional Greenhouse Gas Initiative (RGGI) and support for a regional food system have been recognized as strategic tools for climate change mitigation and adaptation, but decision-makers have limited information on the potential consequences of these strategies on the complex natural-human system of the Northeast, under various scenarios of global climate change. We have developed a Northeast Regional Earth System Model (NE-RESM) as a framework to provide this type of information. We integrate terrestrial ecosystem, hydrologic, energy system and economic models to investigate scenarios of paired regional socioeconomic pathways and global climate projections. Our initial results suggest that megaregion-scale strategic decisions in the Northeast may have important consequences for both local water management and global climate change mitigation.

Climate Forecasts and Water Resource Management: Applications for a Developing Country

NASA Astrophysics Data System (ADS)

Brown, C.; Rogers, P.

2002-05-01

While the quantity of water on the planet earth is relatively constant, the demand for water is continuously increasing. Population growth leads to linear increases in water demand, and economic growth leads to further demand growth. Strzepek et al. calculate that with a United Nations mean population estimate of 8.5 billion people by 2025 and globally balanced economic growth, water use could increase by 70% over that time (Strzepek et al., 1995). For developing nations especially, supplying water for this growing demand requires the construction of new water supply infrastructure. The prospect of designing and constructing long life-span infrastructure is clouded by the uncertainty of future climate. The availability of future water resources is highly dependent on future climate. With realization of the nonstationarity of climate, responsible design emphasizes resiliency and robustness of water resource systems (IPCC, 1995; Gleick et al., 1999). Resilient systems feature multiple sources and complex transport and distribution systems, and so come at a high economic and environmental price. A less capital-intense alternative to creating resilient and robust water resource systems is the use of seasonal climate forecasts. Such forecasts provide adequate lead time and accuracy to allow water managers and water-based sectors such as agriculture or hydropower to optimize decisions for the expected water supply. This study will assess the use of seasonal climate forecasts from regional climate models as a method to improve water resource management in systems with limited water supply infrastructure

Linking aboveground net primary productivity to soil carbon and dissolved organic carbon in complex terrain

Treesearch

F.S. Peterson; K. Lajtha

2013-01-01

Factors influencing soil organic matter (SOM) stabilization and dissolved organic carbon (DOC) content in complex terrain, where vegetation, climate, and topography vary over the scale of a few meters, are not well understood. We examined the spatial correlations of lidar and geographic information system-derived landscape topography, empirically measured soil...

Climate Change Impacts on Hydrology and Water Management of the San Juan Basin

NASA Astrophysics Data System (ADS)

Rich, P. M.; Weintraub, L. H.; Chen, L.; Herr, J.

2005-12-01

Recent climatic events, including regional drought and increased storm severity, have accentuated concerns that climatic extremes may be increasing in frequency and intensity due to global climate change. As part of the ZeroNet Water-Energy Initiative, the San Juan Decision Support System includes a basin-scale modeling tool to evaluate effects of climate change on water budgets under different climate and management scenarios. The existing Watershed Analysis Risk Management Framework (WARMF) was enhanced with iterative modeling capabilities to enable construction of climate scenarios based on historical and projected data. We applied WARMF to 42,000 km2 (16,000 mi2) of the San Juan Basin (CO, NM) to assess impacts of extended drought and increased temperature on surface water balance. Simulations showed that drought and increased temperature impact water availability for all sectors (agriculture, energy, municipal, industry), and lead to increased frequency of critical shortages. Implementation of potential management alternatives such as "shortage sharing" or degraded water usage during critical years helps improve available water supply. In the face of growing concern over climate change, limited water resources, and competing demands, integrative modeling tools can enable better understanding of complex interconnected systems, and enable better decisions.

Ecological complexity buffers the impacts of future climate on marine consumers

NASA Astrophysics Data System (ADS)

Goldenberg, Silvan U.; Nagelkerken, Ivan; Marangon, Emma; Bonnet, Angélique; Ferreira, Camilo M.; Connell, Sean D.

2018-03-01

Ecological complexity represents a network of interacting components that either propagate or counter the effects of environmental change on individuals and communities1-3. Yet, our understanding of the ecological imprint of ocean acidification (elevated CO2) and climate change (elevated temperature) is largely based on reports of negative effects on single species in simplified laboratory systems4,5. By combining a large mesocosm experiment with a global meta-analysis, we reveal the capacity of consumers (fish and crustaceans) to resist the impacts of elevated CO2. While individual behaviours were impaired by elevated CO2, consumers could restore their performances in more complex environments that allowed for compensatory processes. Consequently, consumers maintained key traits such as foraging, habitat selection and predator avoidance despite elevated CO2 and sustained their populations. Our observed increase in risk-taking under elevated temperature, however, predicts greater vulnerability of consumers to predation. Yet, CO2 as a resource boosted the biomass of consumers through species interactions and may stabilize communities by countering the negative effects of elevated temperature. We conclude that compensatory dynamics inherent in the complexity of nature can buffer the impacts of future climate on species and their communities.

The role of climatic and geological events in generating diversity in Ethiopian grass frogs (genus Ptychadena).

PubMed

Smith, Megan L; Noonan, Brice P; Colston, Timothy J

2017-08-01

Ethiopia is a world biodiversity hotspot and harbours levels of biotic endemism unmatched in the Horn of Africa, largely due to topographic-and thus habitat-complexity, which results from a very active geological and climatic history. Among Ethiopian vertebrate fauna, amphibians harbour the highest levels of endemism, making amphibians a compelling system for the exploration of the impacts of Ethiopia's complex abiotic history on biotic diversification. Grass frogs of the genus Ptychadena are notably diverse in Ethiopia, where they have undergone an evolutionary radiation. We used molecular data and expanded taxon sampling to test for cryptic diversity and to explore diversification patterns in both the highland radiation and two widespread lowland Ptychadena . Species delimitation results support the presence of nine highland species and four lowland species in our dataset, and divergence dating suggests that both geologic events and climatic fluctuations played a complex and confounded role in the diversification of Ptychadena in Ethiopia. We rectify the taxonomy of the endemic P. neumanni species complex, elevating one formally synonymized name and describing three novel taxa. Finally, we describe two novel lowland Ptychadena species that occur in Ethiopia and may be more broadly distributed.

Planning and Design of Water Resources Systems Under Climate Change and Variability

NASA Astrophysics Data System (ADS)

Strzepek, K. M.

2014-12-01

Regional and local water supplies and demands are impacted by global and national systems: climate, economics, population and energy as well as policies: development, energy, and environmental. These drivers can result in complex interactions that require deeper understanding in order to provide actionable information for water planners and stakeholders to develop strategic plans in the face of a changing and growing world. To add more complexity to this issue is the fact that all these drivers are uncertain and the type of uncertainty is not the same. This talk will address approaches to Water Resource Planning at sub-national water regions, national levels and trans-boundary river basins under a non-stationary hydro-climatic future. Additionally the talk will address the design of specific water resource projects such as reservoirs and hydroplants that are being designed now but will operate far in the future when the hydro-climatology will be very different. Examples will be drawn from recent work in Africa, Eastern Europe and Central Asia, and North America and some insights and outstanding questions will be presented.

Climate Change Education: Student Media Production to Educate and Engage

NASA Astrophysics Data System (ADS)

Rooney-Varga, J. N.; Brisk, A. A.; Ledley, T. S.; Shuldman, M.

2011-12-01

Climate change education offers many challenges, including the complexity of the natural and human systems involved, a need for a multi-disciplinary perspective, and the psychological barriers to learning that result from a problem that frequently elicits a sense of being overwhelmed and powerless. The implications of climate change impacts and/or solutions can be especially overwhelming for today's students, who are likely to be confronted with many projected changes within their lifetimes. We are developing approaches to incorporate video production by students at both the high school and university levels in order to overcome many of the challenges unique to climate change education. Through media production, students are asked to convey complex topics using clear, simple language and metaphor, so their content knowledge must be deep enough to educate others. Video production is a team effort (director, camera person, editor, etc.) and inherently creates an opportunity for learning in a social context, which has been shown to lead to better learning outcomes in climate change education. Video production also promotes the basic tenets of engagement theory, in which a small group of students is in constant contact with the content and, ideally, creates a product that can be disseminated broadly. Lastly, putting students behind the camera can give them a voice and a sense of empowerment, fostering active participation in the learning process. While video is a medium that is readily disseminated to a broad audience, our focus is on the process (i.e., learning outcomes of students directly involved in media production), not the product. However, we have found that providing students with a means to add their voices to the broader public's discussion of climate change has a positive impact on student engagement with climate change science and on public awareness this problem beyond the classroom. While student-produced media pieces are not intended to provide in-depth scientific information to the broader public, we have found that they can be successful in conveying some of the key, basic concepts needed to understand anthropogenic climate change. Some of these concepts include the causal relationships between fossil fuel-based energy systems, atmospheric carbon dioxide concentrations, and climate change; the distinction between natural and anthropogenic processes in the carbon cycle; impacts of climate change on ecosystem services; and transitioning to renewable energy systems that do not emit carbon dioxide is necessary to avert 'dangerous' climate change.

Cloud Microphysical Properties in Mesoscale Convective Systems: An Intercomparison of Three Tropical Locations

NASA Astrophysics Data System (ADS)

Fontaine, Emmanuel; Leroy, Delphine; Schwarzenboeck, Alfons; Coutris, Pierre; Delanoë, Julien; Protat, Alain; Dezitter, Fabien; Grandin, Alice; Strapp, John W.; Lilie, Lyle E.

2017-04-01

Mesoscale Convective Systems are complex cloud systems which are primarily the result of specific synoptic conditions associated with mesoscale instabilities leading to the development of cumulonimbus type clouds (Houze, 2004). These systems can last several hours and can affect human societies in various ways. In general, weather and climate models use simplistic schemes to describe ice hydrometeors' properties. However, MCS are complex cloud systems where the dynamic, radiative and precipitation processes depend on spatiotemporal location in the MCS (Houze, 2004). As a consequence, hydrometeor growth processes in MCS vary in space and time, thereby impacting shape and concentration of ice crystals and finally CWC. As a consequence, differences in the representation of ice properties in models (Li et al., 2007, 2005) lead to significant disagreements in the quantification of ice cloud effects on climate evolution (Intergovernmental Panel on Climate Change Fourth Assessment Report). An accurate estimation of the spatiotemporal CWC distribution is therefore a key parameter for evaluating and improving numerical weather prediction (Stephens et al., 2002). The main purpose of this study is to show ice microphysical properties of MCS observed in three different locations in the tropical atmosphere: West-African continent, Indian Ocean, and Northern Australia. An intercomparison study is performed in order to quantify how similar or different are the ice hydrometeors' properties in these three regions related to radar reflectivity factors and temperatures observed in respective MCS.

Simulations of the future precipitation climate of the Central Andes using a coupled regional climate model

NASA Astrophysics Data System (ADS)

Nicholls, S.; Mohr, K. I.

2014-12-01

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. Global climate models, although capable of resolving synoptic-scale South American climate features, are inadequate for fully-resolving the strong gradients between climate regimes and the complex orography which define the Tropical Andes given their low spatial and temporal resolution. Recent computational advances now make practical regional climate modeling with prognostic mesoscale atmosphere-ocean coupled models, such as the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, to climate research. Previous work has shown COAWST to reasonably simulate the both the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data. More recently, COAWST simulations have also been shown to sensibly reproduce the entire annual cycle of rainfall (Oct 2003 - Oct 2004) with historical climate model input. Using future global climate model input for COAWST, the present work involves year-long cycle spanning October to October for the years 2031, 2059, and 2087 assuming the most likely regional climate pathway (RCP): RCP 6.0. COAWST output is used to investigate how global climate change impacts the spatial distribution, precipitation rates, and diurnal cycle of precipitation patterns in the Central Andes vary in these yearly "snapshots". Initial results show little change to precipitation coverage or its diurnal cycle, however precipitation amounts did tend drier over the Brazilian Plateau and wetter over the Western Amazon and Central Andes. These results suggest potential adjustments to large-scale climate features (such as the Bolivian High).

Towards Improved Linkage of Disaster Risk Reduction and Climate Change Adaptation in Health: A Review

PubMed Central

Banwell, Nicola; Rutherford, Shannon; Mackey, Brendan; Chu, Cordia

2018-01-01

Climate change and climate-sensitive disasters significantly impact health. Linking Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) is essential for addressing these ever present, complex and increasing risks. Recent calls have been made to build these links in health. However, there is a need to clearly articulate why linking DRR and CCA is important in health. Furthermore, little is known about how DRR and CCA should be linked in health. By extensively examining relevant literature, this review presents the current state of knowledge of linking DRR and CCA in health. This includes the potential for maximising conceptual synergies such as building resilience, and reducing vulnerability and risk. Additionally, technical and operational synergies are identified to link DRR and CCA in health, including: policy, Early Warning Systems, vulnerability and risk assessment, health systems strengthening, infrastructure resilience, disaster preparedness and response, and health impact pathways. Public health actors have a central role in building these links due to their expertise, work functions, and experience in addressing complex health risks. The review concludes with recommendations for future research, including how to better link DRR and CCA in health; and the opportunities, challenges and enablers to build and sustain these links. PMID:29670057

A Regional Climate Model Evaluation System based on Satellite and other Observations

NASA Astrophysics Data System (ADS)

Lean, P.; Kim, J.; Waliser, D. E.; Hall, A. D.; Mattmann, C. A.; Granger, S. L.; Case, K.; Goodale, C.; Hart, A.; Zimdars, P.; Guan, B.; Molotch, N. P.; Kaki, S.

2010-12-01

Regional climate models are a fundamental tool needed for downscaling global climate simulations and projections, such as those contributing to the Coupled Model Intercomparison Projects (CMIPs) that form the basis of the IPCC Assessment Reports. The regional modeling process provides the means to accommodate higher resolution and a greater complexity of Earth System processes. Evaluation of both the global and regional climate models against observations is essential to identify model weaknesses and to direct future model development efforts focused on reducing the uncertainty associated with climate projections. However, the lack of reliable observational data and the lack of formal tools are among the serious limitations to addressing these objectives. Recent satellite observations are particularly useful as they provide a wealth of information on many different aspects of the climate system, but due to their large volume and the difficulties associated with accessing and using the data, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL / UCLA is developing a model evaluation system to help make satellite observations, in conjunction with in-situ, assimilated, and reanalysis datasets, more readily accessible to the modeling community. The system includes a central database to store multiple datasets in a common format and codes for calculating predefined statistical metrics to assess model performance. This allows the time taken to compare model simulations with satellite observations to be reduced from weeks to days. Early results from the use this new model evaluation system for evaluating regional climate simulations over California/western US regions will be presented.

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

PubMed

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

2018-06-01

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

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.

Flash crashes, bursts, and black swans: parallels between financial markets and healthcare systems.

PubMed

West, Bruce J; Clancy, Thomas R

2010-11-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 16th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, Dr Clancy, the editor of this column, and co-author, Dr West, discuss how the collapse of global financial markets in 2008 may provide valuable insight into mechanisms of complex system behavior in healthcare. Dr West, a physicist and expert in the field of complex systems and network science, is author of a chapter in the book, On the Edge: Nursing in the Age of Complexity (Lindberg C, Nash S, Linberg C. Bordertown, NJ: Plexus Press; 2008) and his most recent book, Disrupted Networks: From Physics to Climate Change (West BJ, Scafetta N. Singapore: Disrupted Networks, World Scientific Publishing; 2010).

Fuel cell on-site integrated energy system parametric analysis of a residential complex

NASA Technical Reports Server (NTRS)

Simons, S. N.

1977-01-01

A parametric energy-use analysis was performed for a large apartment complex served by a fuel cell on-site integrated energy system (OS/IES). The variables parameterized include operating characteristics for four phosphoric acid fuel cells, eight OS/IES energy recovery systems, and four climatic locations. The annual fuel consumption for selected parametric combinations are presented and a breakeven economic analysis is presented for one parametric combination. The results show fuel cell electrical efficiency and system component choice have the greatest effect on annual fuel consumption; fuel cell thermal efficiency and geographic location have less of an effect.

Advanced Materials, Technologies, and Complex Systems Analyses: Emerging Opportunities to Enhance Urban Water Security.

PubMed

Zodrow, Katherine R; Li, Qilin; Buono, Regina M; Chen, Wei; Daigger, Glen; Dueñas-Osorio, Leonardo; Elimelech, Menachem; Huang, Xia; Jiang, Guibin; Kim, Jae-Hong; Logan, Bruce E; Sedlak, David L; Westerhoff, Paul; Alvarez, Pedro J J

2017-09-19

Innovation in urban water systems is required to address the increasing demand for clean water due to population growth and aggravated water stress caused by water pollution, aging infrastructure, and climate change. Advances in materials science, modular water treatment technologies, and complex systems analyses, coupled with the drive to minimize the energy and environmental footprints of cities, provide new opportunities to ensure a resilient and safe water supply. We present a vision for enhancing efficiency and resiliency of urban water systems and discuss approaches and research needs for overcoming associated implementation challenges.

Effects of climate change on the delivery of soil-mediated ecosystem services within the primary sector in temperate ecosystems: a review and New Zealand case study.

PubMed

Orwin, Kate H; Stevenson, Bryan A; Smaill, Simeon J; Kirschbaum, Miko U F; Dickie, Ian A; Clothier, Brent E; Garrett, Loretta G; van der Weerden, Tony J; Beare, Michael H; Curtin, Denis; de Klein, Cecile A M; Dodd, Michael B; Gentile, Roberta; Hedley, Carolyn; Mullan, Brett; Shepherd, Mark; Wakelin, Steven A; Bell, Nigel; Bowatte, Saman; Davis, Murray R; Dominati, Estelle; O'Callaghan, Maureen; Parfitt, Roger L; Thomas, Steve M

2015-08-01

Future human well-being under climate change depends on the ongoing delivery of food, fibre and wood from the land-based primary sector. The ability to deliver these provisioning services depends on soil-based ecosystem services (e.g. carbon, nutrient and water cycling and storage), yet we lack an in-depth understanding of the likely response of soil-based ecosystem services to climate change. We review the current knowledge on this topic for temperate ecosystems, focusing on mechanisms that are likely to underpin differences in climate change responses between four primary sector systems: cropping, intensive grazing, extensive grazing and plantation forestry. We then illustrate how our findings can be applied to assess service delivery under climate change in a specific region, using New Zealand as an example system. Differences in the climate change responses of carbon and nutrient-related services between systems will largely be driven by whether they are reliant on externally added or internally cycled nutrients, the extent to which plant communities could influence responses, and variation in vulnerability to erosion. The ability of soils to regulate water under climate change will mostly be driven by changes in rainfall, but can be influenced by different primary sector systems' vulnerability to soil water repellency and differences in evapotranspiration rates. These changes in regulating services resulted in different potentials for increased biomass production across systems, with intensively managed systems being the most likely to benefit from climate change. Quantitative prediction of net effects of climate change on soil ecosystem services remains a challenge, in part due to knowledge gaps, but also due to the complex interactions between different aspects of climate change. Despite this challenge, it is critical to gain the information required to make such predictions as robust as possible given the fundamental role of soils in supporting human well-being. © 2015 John Wiley & Sons Ltd.

Climate Literacy: Progress in Climate and Global Change Undergraduate Courses in Meteorology and Earth System Science Programs at Jackson State University

NASA Astrophysics Data System (ADS)

Reddy, S. R.; Tuluri, F.; Fadavi, M.

2017-12-01

JSU Meteorology Program will be offering AMS Climate Studies undergraduate course under MET 210: Climatology in spring 2013. AMS Climate Studies is offered as a 3 credit hour laboratory course with 2 lectures and 1 lab sessions per week. Although this course places strong intellectual demands upon each student, the instructors' objective is to help each student to pass the course with an adequate understanding of the fundamentals and advanced and advanced courses. AMS Climate Studies is an introductory college-level course developed by the American Meteorological Society for implementation at undergraduate institutions nationwide. The course places students in a dynamic and highly motivational educational environment where they investigate Earth's climate system using real-world environmental data. The AMS Climate Studies course package consists of a textbook, investigations manual, course website, and course management system-compatible files. Instructors can use these resources in combinations that make for an exciting learning experience for their students. This is a content course in Earth Science. It introduces a new concept that views Earth as a synergistic physical system applied concepts of climatology, for him/her to understand basic atmospheric/climate processes, physical and dynamical climatology, regional climatology, past and future climates and statistical analysis using climate data and to be prepared to profit from studying more of interrelated phenomenon governed by complex processes involving the atmosphere, the hydrosphere, the biosphere, and the solid Earth. The course emphasizes that the events that shape the physical, chemical, and biological processes of the Earth do not occur in isolation. Rather, there is a delicate relationship between the events that occur in the ocean, atmosphere, and the solid Earth. The course provides a multidimensional approach in solving scientific issues related to Earth-related sciences,

Convergence in France facing Big Data era and Exascale challenges for Climate Sciences

NASA Astrophysics Data System (ADS)

Denvil, Sébastien; Dufresne, Jean-Louis; Salas, David; Meurdesoif, Yann; Valcke, Sophie; Caubel, Arnaud; Foujols, Marie-Alice; Servonnat, Jérôme; Sénési, Stéphane; Derouillat, Julien; Voury, Pascal

2014-05-01

The presentation will introduce a french national project : CONVERGENCE that has been funded for four years. This project will tackle big data and computational challenges faced by climate modeling community in HPC context. Model simulations are central to the study of complex mechanisms and feedbacks in the climate system and to provide estimates of future and past climate changes. Recent trends in climate modelling are to add more physical components in the modelled system, increasing the resolution of each individual component and the more systematic use of large suites of simulations to address many scientific questions. Climate simulations may therefore differ in their initial state, parameter values, representation of physical processes, spatial resolution, model complexity, and degree of realism or degree of idealisation. In addition, there is a strong need for evaluating, improving and monitoring the performance of climate models using a large ensemble of diagnostics and better integration of model outputs and observational data. High performance computing is currently reaching the exascale and has the potential to produce this exponential increase of size and numbers of simulations. However, post-processing, analysis, and exploration of the generated data have stalled and there is a strong need for new tools to cope with the growing size and complexity of the underlying simulations and datasets. Exascale simulations require new scalable software tools to generate, manage and mine those simulations ,and data to extract the relevant information and to take the correct decision. The primary purpose of this project is to develop a platform capable of running large ensembles of simulations with a suite of models, to handle the complex and voluminous datasets generated, to facilitate the evaluation and validation of the models and the use of higher resolution models. We propose to gather interdisciplinary skills to design, using a component-based approach, a specific programming environment for scalable scientific simulations and analytics, integrating new and efficient ways of deploying and analysing the applications on High Performance Computing (HPC) system. CONVERGENCE, gathering HPC and informatics expertise that cuts across the individual partners and the broader HPC community, will allow the national climate community to leverage information technology (IT) innovations to address its specific needs. Our methodology consists in developing an ensemble of generic elements needed to run the French climate models with different grids and different resolution, ensuring efficient and reliable execution of these models, managing large volume and number of data and allowing analysis of the results and precise evaluation of the models. These elements include data structure definition and input-output (IO), code coupling and interpolation, as well as runtime and pre/post-processing environments. A common data and metadata structure will allow transferring consistent information between the various elements. All these generic elements will be open source and publicly available. The IPSL-CM and CNRM-CM climate models will make use of these elements that will constitute a national platform for climate modelling. This platform will be used, in its entirety, to optimise and tune the next version of the IPSL-CM model and to develop a global coupled climate model with a regional grid refinement. It will also be used, at least partially, to run ensembles of the CNRM-CM model at relatively high resolution and to run a very-high resolution prototype of this model. The climate models we developed are already involved in many international projects. For instance we participate to the CMIP (Coupled Model Intercomparison Project) project that is very demanding but has a high visibility: its results are widely used and are in particular synthesised in the IPCC (Intergovernmental Panel on Climate Change) assessment reports. The CONVERGENCE project will constitute an invaluable step for the French climate community to prepare and better contribute to the next phase of the CMIP project.

Sustainability: Why the Language and Ethics of Sustainability Matter in the Geoscience Classroom

ERIC Educational Resources Information Center

Metzger, Ellen P.; Curren, Randall R.

2017-01-01

Because challenges to sustainability arise at the intersection of human and biophysical systems they are inescapably embedded in social contexts and involve multiple stakeholders with diverse and often conflicting needs and value systems. Addressing complex and solution-resistant problems such as climate change, biodiversity loss, and…

The Role of the School Principal in Comparative Perspectives.

ERIC Educational Resources Information Center

Geering, Adrian D.

Decentralized school systems make the principal's role more complex in the U.S. than in Australia's highly centralized system. Principals are pivotal to school success in both countries. A principal sets a school's climate, affecting decision-making, communications, educational innovations, and teacher morale, while performing formal tasks…

Mathematics applied to the climate system: outstanding challenges and recent progress

PubMed Central

Williams, Paul D.; Cullen, Michael J. P.; Davey, Michael K.; Huthnance, John M.

2013-01-01

The societal need for reliable climate predictions and a proper assessment of their uncertainties is pressing. Uncertainties arise not only from initial conditions and forcing scenarios, but also from model formulation. Here, we identify and document three broad classes of problems, each representing what we regard to be an outstanding challenge in the area of mathematics applied to the climate system. First, there is the problem of the development and evaluation of simple physically based models of the global climate. Second, there is the problem of the development and evaluation of the components of complex models such as general circulation models. Third, there is the problem of the development and evaluation of appropriate statistical frameworks. We discuss these problems in turn, emphasizing the recent progress made by the papers presented in this Theme Issue. Many pressing challenges in climate science require closer collaboration between climate scientists, mathematicians and statisticians. We hope the papers contained in this Theme Issue will act as inspiration for such collaborations and for setting future research directions. PMID:23588054

Near real time/low latency data collection for climate warming manipulations and an elevated CO2 SPRUCE experiment

NASA Astrophysics Data System (ADS)

Krassovski, M.; Hanson, P. J.; Riggs, J. S.; Nettles, W. R., IV

2017-12-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This presentation shares our experience of establishing near real time/low latency data collection and monitoring system using satellite communication.

The Mathematical Formatting of Climate Change: Critical Mathematics Education and Post-Normal Science

ERIC Educational Resources Information Center

Barwell, Richard

2013-01-01

Climate change is one of the most pressing issues of the 21st Century. Mathematics is involved at every level of understanding climate change, including the description, prediction and communication of climate change. As a highly complex issue, climate change is an example of "post-normal" science -- it is urgent, complex and involves a…

Quantification of scaling exponents and dynamical complexity of microwave refractivity in a tropical climate

NASA Astrophysics Data System (ADS)

Fuwape, Ibiyinka A.; Ogunjo, Samuel T.

2016-12-01

Radio refractivity index is used to quantify the effect of atmospheric parameters in communication systems. Scaling and dynamical complexities of radio refractivity across different climatic zones of Nigeria have been studied. Scaling property of the radio refractivity across Nigeria was estimated from the Hurst Exponent obtained using two different scaling methods namely: The Rescaled Range (R/S) and the detrended fluctuation analysis(DFA). The delay vector variance (DVV), Largest Lyapunov Exponent (λ1) and Correlation Dimension (D2) methods were used to investigate nonlinearity and the results confirm the presence of deterministic nonlinear profile in the radio refractivity time series. The recurrence quantification analysis (RQA) was used to quantify the degree of chaoticity in the radio refractivity across the different climatic zones. RQA was found to be a good measure for identifying unique fingerprint and signature of chaotic time series data. Microwave radio refractivity was found to be persistent and chaotic in all the study locations. The dynamics of radio refractivity increases in complexity and chaoticity from the Coastal region towards the Sahelian climate. The design, development and deployment of robust and reliable microwave communication link in the region will be greatly affected by the chaotic nature of radio refractivity in the region.

Cloud Macroscopic Organization: Order Emerging from Randomness

NASA Technical Reports Server (NTRS)

Yuan, Tianle

2011-01-01

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models

PubMed Central

Knight, Christopher G.; Knight, Sylvia H. E.; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J.; Kettleborough, Jamie A.; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A.; Allen, Myles R.

2007-01-01

In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally. PMID:17640921

Applying a Comprehensive Contextual Climate Change Vulnerability Framework to New Zealand's Tourism Industry.

PubMed

Hopkins, Debbie

2015-03-01

Conceptualisations of 'vulnerability' vary amongst scholarly communities, contributing to a wide variety of applications. Research investigating vulnerability to climate change has often excluded non-climatic changes which may contribute to degrees of vulnerability perceived or experienced. This paper introduces a comprehensive contextual vulnerability framework which incorporates physical, social, economic and political factors which could amplify or reduce vulnerability. The framework is applied to New Zealand's tourism industry to explore its value in interpreting a complex, human-natural environment system with multiple competing vulnerabilities. The comprehensive contextual framework can inform government policy and industry decision making, integrating understandings of climate change within the broader context of internal and external social, physical, economic, and institutional stressors.

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

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.

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

Advanced functional network analysis in the geosciences: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

2013-04-01

Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

International Land Model Benchmarking (ILAMB) Workshop Report, Technical Report DOE/SC-0186

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

Hoffman, Forrest M.; Koven, Charles D.; Kappel-Aleks, Gretchen

2016-11-01

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

Complex response of a midcontinent north America drainage system to late Wisconsinan sedimentation

USGS Publications Warehouse

Bettis, E. Arthur; Autin, W.J.

1997-01-01

The geomorphic evolution of Mud Creek basin in eastern Iowa, U.S.A. serves to illustrate how geomorphic influences such as sediment supply, valley gradient, climate, and vegetation are recorded in the alluvial stratigraphic record. Sediment supply to the fluvial system increased significantly during the late Wisconsinan through a combination of periglacial erosion and loess accumulation. Subsequent evolution of the Holocene alluvial stratigraphic record reflects long-term routing of the late Wisconsinan sediment through the drainage basin in a series of cut-and-fill cycles whose timing was influenced by hydrologic response to change in climate and vegetation. When viewed in a regional context, the alluvial stratigraphic record appears to reflect a long-term complex response of the fluvial system to increased sediment supply during the late Wisconsinan. Hydrologic and sediment-supply changes accompanying the spread of Euroamerican agriculture to the basin in the 180Os dramatically upset trends in sedimentation and channel behavior established during the Holocene. Copyright ?? 1997, SEPM (Society for Sedimentary Geology).

From Dr. Steven Ashby, Director of PNNL

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

Ashby, Steven

Powered by the creativity and imagination of more than 4,000 exceptional scientists, engineers and support professionals, at PNNL we advance the frontiers of science and address some of the most challenging problems in energy, the environment and national security. As DOE’s premier chemistry, environmental sciences and data analytics laboratory, we provide national leadership in four areas: deepening our understanding of climate science; inventing the future power grid; preventing nuclear proliferation; and speeding environmental remediation. Other areas where we make important contributions include energy storage, microbial biology and cyber security. PNNL also is home to EMSL (the Environmental Molecular Sciences Laboratory),more » one of DOE’s scientific user facilities. We apply these science strengths to address both national and international problems in complex adaptive systems that are too difficult for one institution to tackle alone. Take earth systems, for instance. The earth is a complex adaptive system because it involves everything from climate and microbial communities in the soil to emissions from cars and coal-powered industrial plants. All of these factors and others ultimately influence not only our environment and overall quality of life, but cause the earth to adapt in ways that must be further addressed. PNNL researchers are playing a vital role in finding solutions across every area of this complex adaptive system.« less

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

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

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

The Scientific Committee on Antarctic Research (SCAR) in the IPY 2007-2009

NASA Astrophysics Data System (ADS)

Kennicutt, M. C.; Wilson, T. J.; Summerhayes, C.

2005-05-01

The Scientific Committee on Antarctic Research (SCAR) initiates, develops, and coordinates international scientific research in the Antarctic region. SCAR is assuming a leadership position in the IPY primarily through its five major Scientific Research Programs; ACE, SALE, EBA, AGCS, and ICESTAR; which will be briefly described.Antarctic Climate Evolution (ACE) promotes the exchange of data and ideas between research groups focusing on the evolution of Antarctica's climate system and ice sheet. The program will: (1) quantitatively assess the climate and glacial history of Antarctica; (2) identify the processes which govern Antarctic change and feed back around the globe; (3) improve our ability to model past changes in Antarctica; and (4)document past change to predict future change in Antarctica. Subglacial Antarctic Lake Environments (SALE) promotes, facilitates, and champions cooperation and collaboration in the exploration and study of subglacial environments in Antarctica. SALE intends to understand the complex interplay of biological, geological, chemical, glaciological, and physical processes within subglacial lake environments through coordinated international research teams. Evolution and Biodiversity in the Antarctic (EBA) will use a suite of modern techniques and interdisciplinary approaches, to explore the evolutionary history of selected modern Antarctic biota, examine how modern biological diversity in the Antarctic influences the way present-day ecosystems function, and thereby predict how the biota may respond to future environmental change. Antarctica and the Global Climate System (AGCS) will investigate the nature of the atmospheric and oceanic linkages between the climate of the Antarctic and the rest of the Earth system, and the mechanisms involved therein. A combination of modern instrumented records of atmospheric and oceanic conditions, and the climate signals held within ice cores will be used to understand past and future climate variability and change in the Antarctic as a result of natural and anthropogenic forcings over the last 100,000 years. Interhemispheric Conjugacy Effects in Solar-Terrestrial and Aeronomy Research (ICESTAR) will study the interactions between and collective behavior of the many component parts of the Earth system, including the interaction between the natural environment and human society. Objectives include specification and prediction of the state of the system and assimilation and integration of data from disparate sources to understand the complex geospace environment.

A Simple Exploration of Complexity at the Climate-Weather-Social-Conflict Nexus

NASA Astrophysics Data System (ADS)

Shaw, M.

2017-12-01

The conceptualization, exploration, and prediction of interplay between climate, weather, important resources, and social and economic - so political - human behavior is cast, and analyzed, in terms familiar from statistical physics and nonlinear dynamics. A simple threshold toy model is presented which emulates human tendencies to either actively engage in responses deriving, in part, from environmental circumstances or to maintain some semblance of status quo, formulated based on efforts drawn from the sociophysics literature - more specifically vis a vis a model akin to spin glass depictions of human behavior - with threshold/switching of individual and collective dynamics influenced by relatively more detailed weather and land surface model (hydrological) analyses via a land data assimilation system (a custom rendition of the NASA GSFC Land Information System). Parameters relevant to human systems' - e.g., individual and collective switching - sensitivity to hydroclimatology are explored towards investigation of overall system behavior; i.e., fixed points/equilibria, oscillations, and bifurcations of systems composed of human interactions and responses to climate and weather through, e.g., agriculture. We discuss implications in terms of conceivable impacts of climate change and associated natural disasters on socioeconomics, politics, and power transfer, drawing from relatively recent literature concerning human conflict.

Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

NASA Astrophysics Data System (ADS)

Nunes, Ana

2015-04-01

Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.

A simple object-oriented and open-source model for scientific and policy analyses of the global climate system – Hector v1.0

DOE PAGES

Hartin, Corinne A.; Patel, Pralit L.; Schwarber, Adria; ...

2015-04-01

Simple climate models play an integral role in the policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v1.0, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global-scale earth system processes. Hector has a three-part main carbon cycle: a one-pool atmosphere, land, and ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector actively solves the inorganicmore » carbon system in the surface ocean, directly calculating air–sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO 2], radiative forcing, and surface temperatures. The model simulates all four Representative Concentration Pathways (RCPs) with equivalent rates of change of key variables over time compared to current observations, MAGICC (a well-known simple climate model), and models from the 5th Coupled Model Intercomparison Project. Hector's flexibility, open-source nature, and modular design will facilitate a broad range of research in various areas.« less

Incorporating climate-system and carbon-cycle uncertainties in integrated assessments of climate change. (Invited)

NASA Astrophysics Data System (ADS)

Rogelj, J.; McCollum, D. L.; Reisinger, A.; Knutti, R.; Riahi, K.; Meinshausen, M.

2013-12-01

The field of integrated assessment draws from a large body of knowledge across a range of disciplines to gain robust insights about possible interactions, trade-offs, and synergies. Integrated assessment of climate change, for example, uses knowledge from the fields of energy system science, economics, geophysics, demography, climate change impacts, and many others. Each of these fields comes with its associated caveats and uncertainties, which should be taken into account when assessing any results. The geophysical system and its associated uncertainties are often represented by models of reduced complexity in integrated assessment modelling frameworks. Such models include simple representations of the carbon-cycle and climate system, and are often based on the global energy balance equation. A prominent example of such model is the 'Model for the Assessment of Greenhouse Gas Induced Climate Change', MAGICC. Here we show how a model like MAGICC can be used for the representation of geophysical uncertainties. Its strengths, weaknesses, and limitations are discussed and illustrated by means of an analysis which attempts to integrate socio-economic and geophysical uncertainties. These uncertainties in the geophysical response of the Earth system to greenhouse gases remains key for estimating the cost of greenhouse gas emission mitigation scenarios. We look at uncertainties in four dimensions: geophysical, technological, social and political. Our results indicate that while geophysical uncertainties are an important factor influencing projections of mitigation costs, political choices that delay mitigation by one or two decades a much more pronounced effect.

Process connectivity reveals ecohydrologic sensitivity to drought and rainfall pulses

NASA Astrophysics Data System (ADS)

Goodwell, A. E.; Kumar, P.

2017-12-01

Ecohydrologic fluxes within atmosphere, canopy and soil systems exhibit complex and joint variability. This complexity arises from direct and indirect forcing and feedback interactions that can cause fluctuations to propagate between water, energy, and nutrient fluxes at various time scales. When an ecosystem is perturbed in the form of a single storm event, an accumulating drought, or changes in climate and land cover, this aspect of joint variability may dictate responsiveness and resilience of the entire system. A characterization of the time-dependent and multivariate connectivity between processes, fluxes, and states is necessary to identify and understand these aspects of ecohydrologic systems. We construct Temporal Information Partitioning Networks (TIPNets), based on information theory measures, to identify time-dependencies between variables measured at flux towers along elevation and climate gradients in relation to their responses to moisture-related perturbations. Along a flux tower transect in the Reynolds Creek Critical Zone Observatory (CZO) in Idaho, we detect a significant network response to a large 2015 dry season rainfall event that enhances microbial respiration and latent heat fluxes. At a transect in the Southern Sierra CZO in California, we explore network properties in relation to drought responses from 2011 to 2015. We find that both high and low elevation sites exhibit decreased connectivity between atmospheric and soil variables and latent heat fluxes, but the higher elevation site is less sensitive to this altered connectivity in terms of average monthly heat fluxes. Through a novel approach to gage the responsiveness of ecosystem fluxes to shifts in connectivity, this study aids our understanding of ecohydrologic sensitivity to short-term rainfall events and longer term droughts. This study is relevant to ecosystem resilience under a changing climate, and can lead to a greater understanding of shifting behaviors in many types of complex systems.

Climate change impacts on food system

NASA Astrophysics Data System (ADS)

Zhang, X.; Cai, X.; Zhu, T.

2014-12-01

Food system includes biophysical factors (climate, land and water), human environments (production technologies and food consumption, distribution and marketing), as well as the dynamic interactions within them. Climate change affects agriculture and food systems in various ways. Agricultural production can be influenced directly by climatic factors such as mean temperature rising, change in rainfall patterns, and more frequent extreme events. Eventually, climate change could cause shift of arable land, alteration of water availability, abnormal fluctuation of food prices, and increase of people at risk of malnutrition. This work aims to evaluate how climate change would affect agricultural production biophysically and how these effects would propagate to social factors at the global level. In order to model the complex interactions between the natural and social components, a Global Optimization model of Agricultural Land and Water resources (GOALW) is applied to the analysis. GOALW includes various demands of human society (food, feed, other), explicit production module, and irrigation water availability constraint. The objective of GOALW is to maximize global social welfare (consumers' surplus and producers' surplus).Crop-wise irrigation water use in different regions around the world are determined by the model; marginal value of water (MVW) can be obtained from the model, which implies how much additional welfare benefit could be gained with one unit increase in local water availability. Using GOALW, we will analyze two questions in this presentation: 1) how climate change will alter irrigation requirements and how the social system would buffer that by price/demand adjustment; 2) how will the MVW be affected by climate change and what are the controlling factors. These results facilitate meaningful insights for investment and adaptation strategies in sustaining world's food security under climate change.

Adapting regional watershed management to climate change in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, Ralf; Muerth, Markus; Schmid, Josef; Jobst, Andreas; Caya, Daniel; Gauvin St-Denis, Blaise; Chaumont, Diane; Velazquez, Juan-Alberto; Turcotte, Richard; Ricard, Simon

2013-04-01

The international research project QBic3 (Quebec-Bavarian Collaboration on Climate Change) aims at investigating the potential impacts of climate change on the hydrology of regional scale catchments in Southern Quebec (Canada) and Bavaria (Germany). For this purpose, a hydro-meteorological modeling chain has been established, applying climatic forcing from both dynamical and statistical climate model data to an ensemble of hydrological models of varying complexity. The selection of input data, process descriptions and scenarios allows for the inter-comparison of the uncertainty ranges on selected runoff indicators; a methodology to display the relative importance of each source of uncertainty is developed and results for past runoff (1971-2000) and potential future changes (2041-2070) are obtained. Finally, the impact of hydrological changes on the operational management of dams, reservoirs and transfer systems is investigated and shown for the Bavarian case studies, namely the potential change in i) hydro-power production for the Upper Isar watershed and ii) low flow augmentation and water transfer rates at the Donau-Main transfer system in Central Franconia. Two overall findings will be presented and discussed in detail: a) the climate change response of selected hydrological indicators, especially those related to low flows, is strongly affected by the choice of the hydrological model. It can be shown that an assessment of the changes in the hydrological cycle is best represented by a complex physically based hydrological model, computationally less demanding models (usually simple, lumped and conceptual) can give a significant level of trust for selected indicators. b) the major differences in the projected climate forcing stemming from the ensemble of dynamic climate models (GCM/RCM) versus the statistical-stochastical WETTREG2010 approach. While the dynamic ensemble reveals a moderate modification of the hydrological processes in the investigated catchments, the WETTREG2010 driven runs show a severe detraction for all water operations, mainly related to a strong decline in projected precipitation in all seasons (except winter).

Effects of climate change on the persistence and dispersal of foodborne bacterial pathogens in the outdoor environment: A review.

PubMed

Hellberg, Rosalee S; Chu, Eric

2016-08-01

According to the Intergovernmental Panel on Climate Change (IPCC), warming of the climate system is unequivocal. Over the coming century, warming trends such as increased duration and frequency of heat waves and hot extremes are expected in some areas, as well as increased intensity of some storm systems. Climate-induced trends will impact the persistence and dispersal of foodborne pathogens in myriad ways, especially for environmentally ubiquitous and/or zoonotic microorganisms. Animal hosts of foodborne pathogens are also expected to be impacted by climate change through the introduction of increased physiological stress and, in some cases, altered geographic ranges and seasonality. This review article examines the effects of climatic factors, such as temperature, rainfall, drought and wind, on the environmental dispersal and persistence of bacterial foodborne pathogens, namely, Bacillus cereus, Brucella, Campylobacter, Clostridium, Escherichia coli, Listeria monocytogenes, Salmonella, Staphylococcus aureus, Vibrio and Yersinia enterocolitica. These relationships are then used to predict how future climatic changes will impact the activity of these microorganisms in the outdoor environment and associated food safety issues. The development of predictive models that quantify these complex relationships will also be discussed, as well as the potential impacts of climate change on transmission of foodborne disease from animal hosts.

Varying geospatial analyses to assess climate risk and adaptive capacity in a hotter, drier Southwestern United States

NASA Astrophysics Data System (ADS)

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

2017-12-01

Assessing vulnerability of agricultural systems to climate variability and change is vital in securing food systems and sustaining rural livelihoods. Farmers, ranchers, and forest landowners rely on science-based, decision-relevant, and localized information to maintain production, ecological viability, and economic returns. This contribution synthesizes a collection of research on the future of agricultural production in the American Southwest (SW). Research was based on a variety of geospatial methodologies and datasets to assess the vulnerability of rangelands and livestock, field crops, specialty crops, and forests in the SW to climate-risk and change. This collection emerged from the development of regional vulnerability assessments for agricultural climate-risk by the U.S. Department of Agriculture (USDA) Climate Hub Network, established to deliver science-based information and technologies to enable climate-informed decision-making. Authors defined vulnerability differently based on their agricultural system of interest, although each primarily focuses on biophysical systems. We found that an inconsistent framework for vulnerability and climate risk was necessary to adequately capture the diversity, variability, and heterogeneity of SW landscapes, peoples, and agriculture. Through the diversity of research questions and methodologies, this collection of articles provides valuable information on various aspects of SW vulnerability. All articles relied on geographic information systems technology, with highly variable levels of complexity. Agricultural articles used National Agricultural Statistics Service data, either as tabular county level summaries or through the CropScape cropland raster datasets. Most relied on modeled historic and future climate information, but with differing assumptions regarding spatial resolution and temporal framework. We assert that it is essential to evaluate climate risk using a variety of complementary methodologies and perspectives. In addition, we found that spatial analysis supports informed adaptation, within and outside the SW United States. The persistence and adaptive capacity of agriculture in the water-limited Southwest serves as an instructive example and may offer solutions to reduce future climate risk.

Preface

NASA Astrophysics Data System (ADS)

Gidea, Marian; Sieber, Jan; Silber, Mary; Wieczorek, Sebastian

2015-05-01

This special issue on "Tipping Points: Fundamentals and Applications" is an offspring of the workshop with the same title held at the International Centre for Mathematical Sciences (ICMS), Edinburgh, between September 09-13, 2013. The theme of the meeting was the study of threshold behavior in complex environmental systems, such as Earth's climate, or ecological, sociological or economic systems.

RZWQM2 Simulations of Alternative Cropping Systems With and Without Summer Crops in the Central Great Plains

USDA-ARS?s Scientific Manuscript database

Integration and synthesis of data accruing from complex alternative crop rotation experiments across locations and climates is a challenge to agriculturists. System simulation models are potential tools to address this challenge. In this study, we simulated three long-term (1991 to 2008) dryland c...

The science of decisionmaking: applications for sustainable forest and grassland management in the National Forest System

Treesearch

Matthew P. Thompson; Bruce G. Marcot; Frank R. Thompson; Steven McNulty; Larry A. Fisher; Michael C. Runge; David Cleaves; Monica Tomosy

2013-01-01

Sustainable management of national forests and grasslands within the National Forest System (NFS) often requires managers to make tough decisions under considerable uncertainty, complexity, and potential conflict. Resource decisionmakers must weigh a variety of risks, stressors, and challenges to sustainable management, including climate change, wildland fire, invasive...

Storm and tide influenced depositional architecture of the Pliocene-Pleistocene Chad Formation, Chad Basin (Bornu Sub-basin) NE Nigeria: A mixed fluvial, deltaic, shoreface and lacustrine complex

NASA Astrophysics Data System (ADS)

Shettima, Bukar; Kyari, Aji Maina; Aji, Mallam Musa; Adams, Fatimoh Dupe

2018-07-01

Lithofacies analyses of the upper part of the Chad Formation (Bama Ridge Complex) in the Bornu Sub-basin of the Chad Basin indicated four facies associations; fluvial, deltaic, shoreface and lacustrine sequences. The fluvial sequences are composed of fining upward cycles with successive occurrence of planar crossbedded sandstone facies displaying unimodal paleocurrent system and rare mudstone facies typical of braided river system. The deltaic succession consists of both fining and coarsening upwards cycles with the former depicting fluvial setting of an upper delta plain while the later suggestive of mouth-bar sequences. The setting displays a polymodal current system of fluvial, waves, storms and tides that were primarily induced by complex interactions of seiches and lunar tides. Similar current systems devoid of fluvial patterns were reflected in the coarsening upward packages of the shoreface sequences. Lacustrine succession composed of thick bioturbated mudstone facies generally defines the base of these coarsening upward profiles, giving a fluvio-lacustrine geomorphic relief where complex interaction developed the deltaic and shoreface facies along its shorelines. Clay mineral fractions of the formation are dominantly kaolinitic, indicating a predominantly humid tropical-subtropical climatic condition during their deposition. This climatic regime falls within the African humid period of the early-mid Holocene that led to the third lacustrine transgression of the Lake Mega-Chad, whereas the subordinate smectite mineralization points to aridification that characterizes most of the post humid period to recent.

Synchronization and Causality Across Time-scales: Complex Dynamics and Extremes in El Niño/Southern Oscillation

NASA Astrophysics Data System (ADS)

Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.

2017-12-01

A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.

A problem-oriented approach to understanding adaptation: lessons learnt from Alpine Shire, Victoria Australia.

NASA Astrophysics Data System (ADS)

Roman, Carolina

2010-05-01

Climate change is gaining attention as a significant strategic issue for localities that rely on their business sectors for economic viability. For businesses in the tourism sector, considerable research effort has sought to characterise the vulnerability to the likely impacts of future climate change through scenarios or ‘end-point' approaches (Kelly & Adger, 2000). Whilst useful, there are few demonstrable case studies that complement such work with a ‘start-point' approach that seeks to explore contextual vulnerability (O'Brien et al., 2007). This broader approach is inclusive of climate change as a process operating within a biophysical system and allows recognition of the complex interactions that occur in the coupled human-environmental system. A problem-oriented and interdisciplinary approach was employed at Alpine Shire, in northeast Victoria Australia, to explore the concept of contextual vulnerability and adaptability to stressors that include, but are not limited to climatic change. Using a policy sciences approach, the objective was to identify factors that influence existing vulnerabilities and that might consequently act as barriers to effective adaptation for the Shire's business community involved in the tourism sector. Analyses of results suggest that many threats, including the effects climate change, compete for the resources, strategy and direction of local tourism management bodies. Further analysis of conditioning factors revealed that many complex and interacting factors define the vulnerability and adaptive capacity of the Shire's tourism sector to the challenges of global change, which collectively have more immediate implications for policy and planning than long-term future climate change scenarios. An approximation of the common interest, i.e. enhancing capacity in business acumen amongst tourism operators, would facilitate adaptability and sustainability through the enhancement of social capital in this business community. Kelly, P. M., & Adger, W. N. (2000). Theory and practice in assessing vulnerability to climatic change and facilitating adaptation. Climatic Change, 47, 325-352. O'Brien, K., Eriksen, S., Nygaard, L. P., & Schjolden, A. (2007). Why different interpretations of vulnerability matter in climate change discourses. Climate Policy, 7, 73-88.

Global change modeling for Northern Eurasia: a review and strategies to move forward

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Sokolov, A. P.; Zhuang, Q.; Sokolik, I. N.; Lawford, R. G.; Kappas, M.; Paltsev, S.; Groisman, P. Y.

2017-12-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

A review of and perspectives on global change modeling for Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Kicklighter, David W.; Sokolov, Andrei P.; Zhuang, Qianlai; Sokolik, Irina N.; Lawford, Richard; Kappas, Martin; Paltsev, Sergey V.; Groisman, Pavel Ya

2017-08-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change?

EPA Science Inventory

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site...

Climatic Evolution and Habitability of Terrestrial Planets: Perspectives from Coupled Atmosphere-Mantle Systems

NASA Astrophysics Data System (ADS)

Basu Sarkar, D.; Moore, W. B.

2016-12-01

A multitude of factors including the distance from the host star and the stage of planetary evolution affect planetary climate and habitability. The complex interactions between the atmosphere and dynamics of the deep interior of the planets along with stellar fluxes present a formidable challenge. This work employs simplified approaches to address these complex issues in a systematic way. To be specific, we are investigating the coupled evolution of atmosphere and mantle dynamics. The overarching goal here is to simulate the evolutionary history of the terrestrial planets, for example Venus, Earth and Mars. This research also aims at deciphering the history of Venus-like runaway greenhouse and thus explore the possibility of cataclysmic shifts in climate of Earth-like planets. We focus on volatile cycling within the solid planets to understand the role of carbon/water in climatic and tectonic outcomes of such planets. In doing so, we are considering the feedbacks in the coupled mantle-atmosphere system. The primary feedback between the atmosphere and mantle is the surface temperature established by the greenhouse effect, which regulates the temperature gradient that drives the mantle convection and controls the rate at which volatiles are exchanged through weathering. We start our models with different initial assumptions to determine the final climate outcomes within a reasonable parameter space. Currently, there are very few planetary examples, to sample the climate outcomes, however this will soon change as exoplanets are discovered and examined. Therefore, we will be able to work with a significant number of potential candidates to answer questions like this one: For every Earth is there one Venus? ten? a thousand?

Non-linear regime shifts in Holocene Asian monsoon variability: potential impacts on cultural change and migratory patterns

NASA Astrophysics Data System (ADS)

Donges, J. F.; Donner, R. V.; Marwan, N.; Breitenbach, S. F. M.; Rehfeld, K.; Kurths, J.

2015-05-01

The Asian monsoon system is an important tipping element in Earth's climate with a large impact on human societies in the past and present. In light of the potentially severe impacts of present and future anthropogenic climate change on Asian hydrology, it is vital to understand the forcing mechanisms of past climatic regime shifts in the Asian monsoon domain. Here we use novel recurrence network analysis techniques for detecting episodes with pronounced non-linear changes in Holocene Asian monsoon dynamics recorded in speleothems from caves distributed throughout the major branches of the Asian monsoon system. A newly developed multi-proxy methodology explicitly considers dating uncertainties with the COPRA (COnstructing Proxy Records from Age models) approach and allows for detection of continental-scale regime shifts in the complexity of monsoon dynamics. Several epochs are characterised by non-linear regime shifts in Asian monsoon variability, including the periods around 8.5-7.9, 5.7-5.0, 4.1-3.7, and 3.0-2.4 ka BP. The timing of these regime shifts is consistent with known episodes of Holocene rapid climate change (RCC) and high-latitude Bond events. Additionally, we observe a previously rarely reported non-linear regime shift around 7.3 ka BP, a timing that matches the typical 1.0-1.5 ky return intervals of Bond events. A detailed review of previously suggested links between Holocene climatic changes in the Asian monsoon domain and the archaeological record indicates that, in addition to previously considered longer-term changes in mean monsoon intensity and other climatic parameters, regime shifts in monsoon complexity might have played an important role as drivers of migration, pronounced cultural changes, and the collapse of ancient human societies.

Perspectives on Hydro-Climatic Change in Rivers Sourced From the Khangai Mountains, Mongolia

NASA Astrophysics Data System (ADS)

Venable, N. B.; Fassnacht, S. R.; Tumenjargal, S.; Batbuyan, B.; Odgarav, J.; Sukhbataar, J.; Fernandez-Gimenez, M.; Adyabadam, G.

2012-12-01

Patterns of pastoralism have shaped the Mongolian countryside throughout history. These patterns are largely dictated by seasonal and extreme climate and water conditions. While change has always been a part of the traditional herder lifestyle, the magnitude and variety of impacts imposed by natural and human-induced changes in the last few decades has increased, negatively affecting the coupled natural-human systems of Mongolia. Regional hydrologic impacts from increased mining, irrigation, urbanization, and climate change are challenging to measure and model due to sparse and relatively short meteorological and hydrological records. Characterization of the variability inherent in Mongolian hydrological systems in the international literature remains limited. To quantify recent changes to these systems, several river basins near the Khangai Mountains were analyzed. These basins adjoin and include community-based managed and non-managed grazing lands under study as part of an ongoing National Science Foundation Coupled Natural and Human Systems (NSF-CNH) project. Statistically significant increasing temperatures and decreasing streamflows in the study areas support herder's perceptions of hydro-climatic changes and variability. The results of basin characterization combined with water balance modeling and trend analyses illustrate the future potential for further change in these hydro-climatic systems. Alternate land-uses and herder lifestyle modifications may amplify impacts from climatic change. Recent fieldwork also revealed complex surface-groundwater interactions in some areas that may affect model outcomes. Future explorations of longer-term variability through the use of proxies and the development of hydrologic scenarios will place the current basin analyses in context to more fully assess possible impacts to the hydrologic-human systems of Mongolia.

Data Integration Plans for the NOAA National Climate Model Portal (NCMP) (Invited)

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Williams, D. N.; Deluca, C.; Hankin, S. C.; Compo, G. P.

2010-12-01

NOAA’s National Climatic Data Center (NCDC) and its collaborators have initiated a five-year development and implementation of an operational access capability for the next generation weather and climate model datasets. The NOAA National Climate Model Portal (NCMP) is being designed using format neutral open web based standards and tools where users at all levels of expertise can gain access and understanding to many of NOAA’s climate and weather model products. NCMP will closely coordinate with and reside under the emerging NOAA Climate Services Portal (NCSP). To carry out its mission, NOAA must be able to successfully integrate model output and other data and information from all of its discipline specific areas to understand and address the complexity of many environmental problems. The NCMP will be an initial access point for the emerging NOAA Climate Services Portal (NCSP), which is the basis for unified access to NOAA climate products and services. NCMP is currently collaborating with the emerging Environmental Projection Center (EPC) expected to be developed at the Earth System Research Laboratory in Boulder CO. Specifically, NCMP is being designed to: - Enable policy makers and resource managers to make informed national and global policy decisions using integrated climate and weather model outputs, observations, information, products, and other services for the scientist and the non-scientist; - Identify model to observational interoperability requirements for climate and weather system analysis and diagnostics; - Promote the coordination of an international reanalysis observational clearinghouse (i.e.., Reanalysis.org) spanning the worlds numerical processing Center’s for an “Ongoing Analysis of the Climate System”. NCMP will initially provide access capabilities to 3 of NOAA’s high volume Reanalysis data sets of the weather and climate systems: 1) NCEP’s Climate Forecast System Reanalysis (CFS-R); 2) NOAA’s Climate Diagnostics Center/ Earth System Research Laboratory (ESRL) Twentieth Century Reanalysis Project data set (20CR, G. Compo, et al.), a historical reanalysis that will provide climate information dating back to 1850 to the present; and 3) the CPC’s Upper Air Reanlaysis. NCMP will advance the highly successful NOAA National Operational Model Archive and Distribution System (NOMADS, Rutledge, BAMS 2006), and standards already in use including Unidata’s THREDDS (TDS), PMEL’s Live Access Server (LAS) and the GrADS Data Server (GDS) from COLA; the Department of Energy (DOE) Earth System Grid (ESG) and the associated IPCC Climate model archive located at the Program for Climate Model Diagnostics and Inter-comparison (PCMDI) through the ESG; and NOAA’s Unified Access Framework (UAF) effort; and core standards developed by Open Geospatial Consortium (OGC). The format neutral OPeNDAP protocol as used in the NOMADS system will also be a key aspect of the design of NCMP.

Surface radiation budget in the Clouds and the Earth's Radiant Energy System (CERES) effort and in the Global Energy and Water Cycle Experiment (GEWEX)

NASA Technical Reports Server (NTRS)

Charlock, Thomas P.; Smith, G. L.; Rose, Fred G.

1990-01-01

The surface radiation budget (SRB) and the atmospheric radiative flux divergence (ARD) are vital components of the weather and climate system. The importance of radiation in a complex international scientific endeavor, the GEWEX of the World Climate Research Programme is explained. The radiative transfer techniques and satellite instrumentation that will be used to retrieve the SRB and ARD later in this decade with the CERES are discussed; CERES is a component of the Earth Observing System satellite program. Examples of consistent SRB and ARD retrievals made with Nimbus-7 and International Satellite Cloud Climatology Project data from July 1983 are presented.

Physio-climatic controls on vulnerability of watersheds to climate and land use change across the U. S.

NASA Astrophysics Data System (ADS)

Deshmukh, Ankit; Singh, Riddhi

2016-11-01

Understanding how a watershed's physio-climatic characteristics affect its vulnerability to environmental (climatic and land use) change is crucial for managing these complex systems. In this study, we combine the strengths of recently developed exploratory modeling frameworks and comparative hydrology to quantify the relationship between watershed's vulnerability and its physio-climatic characteristics. We propose a definition of vulnerability that can be used by a diverse range of water system managers and is useful in the presence of large uncertainties in drivers of environmental change. This definition is related to adverse climate change and land use thresholds that are quantified using a recently developed exploratory modeling approach. In this way, we estimate the vulnerability of 69 watersheds in the United States to climate and land use change. We explore definitions of vulnerability that describe average or extreme flow conditions, as well as others that are relevant from the point of view of instream organisms. In order to understand the dominant controls on vulnerability, we correlate these indices with watershed's characteristics describing its topography, geology, drainage, climate, and land use. We find that mean annual flow is more vulnerable to reductions in precipitation in watersheds with lower average soil permeability, lower baseflow index, lower forest cover, higher topographical wetness index, and vice-versa. Our results also indicate a potential mediation of climate change impacts by regional groundwater systems. By developing such relationships across a large range of watersheds, such information can potentially be used to assess the vulnerability of ungauged watersheds to uncertain environmental change.

Influence of dimethyl sulfide on the carbon cycle and biological production

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

Wang, Shanlin; Maltrud, Mathew; Elliott, Scott

Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to examine the sign and strength of phytoplankton-DMS-climate feedbacks for the first time. Simulation results show small differences in the DMS production and emissions between pre-industrial and present climate scenarios, except for some areas in the Southern Ocean. There are clear changes in surface ocean DMS concentrations moving into the future, and they are attributable to changes inmore » phytoplankton production and competition driven by complex spatially varying mechanisms. Comparisons between parallel simulations with and without DMS fluxes into the atmosphere show significant differences in marine ecosystems and physical fields. Without DMS, the missing subsequent aerosol indirect effects on clouds and radiative forcing lead to fewer clouds, more solar radiation, and a much warmer climate. Phaeocystis, a uniquely efficient organosulfur producer with a growth advantage under cooler climate states, can benefit from producing the compound through cooling effects of DMS in the climate system. Our results show a tight coupling between the sulfur and carbon cycles. The ocean carbon uptake declines without DMS emissions to the atmosphere. The analysis indicates a weak positive phytoplankton-DMS-climate feedback at the global scale, with large spatial variations driven by individual autotrophic functional groups and complex mechanisms. The sign and strength of the feedback vary with climate states and phytoplankton groups. This highlights the importance of a dynamic marine ecosystem module and the sulfur cycle mechanism in climate projections.« less

Influence of dimethyl sulfide on the carbon cycle and biological production

DOE PAGES

Wang, Shanlin; Maltrud, Mathew; Elliott, Scott; ...

2018-02-27

Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to examine the sign and strength of phytoplankton-DMS-climate feedbacks for the first time. Simulation results show small differences in the DMS production and emissions between pre-industrial and present climate scenarios, except for some areas in the Southern Ocean. There are clear changes in surface ocean DMS concentrations moving into the future, and they are attributable to changes inmore » phytoplankton production and competition driven by complex spatially varying mechanisms. Comparisons between parallel simulations with and without DMS fluxes into the atmosphere show significant differences in marine ecosystems and physical fields. Without DMS, the missing subsequent aerosol indirect effects on clouds and radiative forcing lead to fewer clouds, more solar radiation, and a much warmer climate. Phaeocystis, a uniquely efficient organosulfur producer with a growth advantage under cooler climate states, can benefit from producing the compound through cooling effects of DMS in the climate system. Our results show a tight coupling between the sulfur and carbon cycles. The ocean carbon uptake declines without DMS emissions to the atmosphere. The analysis indicates a weak positive phytoplankton-DMS-climate feedback at the global scale, with large spatial variations driven by individual autotrophic functional groups and complex mechanisms. The sign and strength of the feedback vary with climate states and phytoplankton groups. This highlights the importance of a dynamic marine ecosystem module and the sulfur cycle mechanism in climate projections.« less

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow

PubMed Central

Ganjurjav, Hasbagan; Gao, Qingzhu; Schwartz, Mark W.; Zhu, Wenquan; Liang, Yan; Li, Yue; Wan, Yunfan; Cao, Xujuan; Williamson, Matthew A.; Jiangcun, Wangzha; Guo, Hongbao; Lin, Erda

2016-01-01

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system. PMID:26983697

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow

NASA Astrophysics Data System (ADS)

Ganjurjav, Hasbagan; Gao, Qingzhu; Schwartz, Mark W.; Zhu, Wenquan; Liang, Yan; Li, Yue; Wan, Yunfan; Cao, Xujuan; Williamson, Matthew A.; Jiangcun, Wangzha; Guo, Hongbao; Lin, Erda

2016-03-01

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system.

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow.

PubMed

Ganjurjav, Hasbagan; Gao, Qingzhu; Schwartz, Mark W; Zhu, Wenquan; Liang, Yan; Li, Yue; Wan, Yunfan; Cao, Xujuan; Williamson, Matthew A; Jiangcun, Wangzha; Guo, Hongbao; Lin, Erda

2016-03-17

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system.

Intersectoral action for health equity as it relates to climate change in Canada: contributions from critical systems heuristics.

PubMed

Buse, Chris

2013-12-01

Intersectoral action (ISA) has been at the forefront of public health policy discussions since the 1970s. ISA incorporates a broader perspective of public health issues and coordinates efforts to address the social, political, economic and environmental contexts from which health determinants operate and are created. Despite being forwarded as a useful way to address and treat complex or 'wicked' problems, such policy issues are still often addressed within, rather than across, disciplinary silos and ISA has been documented to fail more often than it succeeds. This paper contributes to an understanding of ISA by outlining and applying critical systems heuristics (CSH) theory and methods. CSH theory and methods are described and discussed before applying them to the example of addressing climate change and health equity through public health practice. CSH thinking provides useful tools to engage stakeholders, question relations of power that may exist between collaborating partners, and move beyond power inequalities that guide ISA initiatives. CSH is a compelling framing that can improve an understanding of the collaborative relationships that are a prerequisite for engaging in ISA to address complex or 'wicked' policy problems such as climate change. © 2013 John Wiley & Sons Ltd.

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

NASA Astrophysics Data System (ADS)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

Co-producing resilient solutions to climate change: Bridging the gap between science and decision-making around nexus issues

NASA Astrophysics Data System (ADS)

Howarth, C.

2016-12-01

The nexus represents a multi-dimensional means of scientific enquiry encapsulating the complex and non-linear interactions between water, energy, food, environment with the climate, and wider implications for society. These resources are fundamental for human life but are negatively affected by climate change. Methods of analysis, which are currently used, were not built to represent complex systems and are insufficiently equipped to understand positive and negative externalities generated by interactions among different stakeholders involved in the nexus. In addition misalignment between the science that scientists produce and the evidence decision-makers need leads to a range of complexities within the science-policy interface. Adopting a bottom-up, participative approach, the results of five themed workshops organized in the UK (focusing on: shocks and hazards, infrastructure, local economy, governance and governments, finance and insurance) featuring 80 stakeholders from academia, government and industry allow us to map perceptions of opportunities and challenges of better informing decision making on climate change when there is a strong disconnect between the evidence scientists provide and the actions decision makers take. The research identified key areas where gaps could be bridged between science and action and explores how a knowledge co-production approach can help identify opportunities for building a more effective and legitimate policy agenda to face climate risks. Concerns, barriers and opportunities to better inform decision making centred on four themes: communication and collaboration, decision making processes, social and cultural dimensions, and the nature of responses to nexus shocks. In so doing, this analysis provides an assessment of good practice on climate decision-making and highlights opportunities for improvement to bridge gaps in the science-policy interface

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.

Climate Analytics as a Service. Chapter 11

NASA Technical Reports Server (NTRS)

Schnase, John L.

2016-01-01

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

Using simple chaotic models to interpret climate under climate change: Implications for probabilistic climate prediction

NASA Astrophysics Data System (ADS)

Daron, Joseph

2010-05-01

Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci, 43, 419-432, 1986. Lorenz, E. N. Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141, 1963. Lorenz, E. N. Irregularity: a fundamental property of the atmosphere. Tellus, 36A, 98-110, 1984. Murphy, J. M., D. M. H. Sexton, G. J. Jenkins, B. B. B. Booth, C. C. Brown, R. T. Clark, M. Collins, G. R. Harris, E. J. Kendon, R. A. Betts, S. J. Brown, P. Boorman, T. P. Howard, K. A. Humphrey, M. P. McCarthy, R. E. McDonald, A. Stephens, C. Wallace, R. Warren, R. Wilby, and R. A. Wood. Uk climate projections science report: Climate change projections. 2009. Sahay, A. and K. R. Sreenivasan. The search for a low-dimensional characterization of a local climate system. Phil. Trans. R. Soc. A., 354, 1715-1750, 1996. Stainforth, D. A., M. R. Allen, E. R. Tredger, and L. A. Smith. Confidence, uncertainty and decision-support relevance in climate predictions. Phil. Trans. R. Soc. A, 365, 2145-2161, 2007.

Assessing the impact of model and climate uncertainty in malaria simulations for the Kenyan Highlands.

NASA Astrophysics Data System (ADS)

Tompkins, A. M.; Thomson, M. C.

2017-12-01

Simulations of the impact of climate variations on a vector-bornedisease such as malaria are subject to a number of sources ofuncertainty. These include the model structure and parameter settingsin addition to errors in the climate data and the neglect of theirspatial heterogeneity, especially over complex terrain. We use aconstrained genetic algorithm to confront these two sources ofuncertainty for malaria transmission in the highlands of Kenya. Thetechnique calibrates the parameter settings of a process-based,mathematical model of malaria transmission to vary within theirassessed level of uncertainty and also allows the calibration of thedriving climate data. The simulations show that in highland settingsclose to the threshold for sustained transmission, the uncertainty inclimate is more important to address than the malaria modeluncertainty. Applications of the coupled climate-malaria modelling system are briefly presented.

Identifying legal, ecological and governance obstacles and opportunities for adapting to climate change

USGS Publications Warehouse

Cosens, Barbara; Gunderson, Lance; Allen, Craig R.; Benson, Melinda H.

2014-01-01

Current governance of regional scale water management systems in the United States has not placed them on a path toward sustainability, as conflict and gridlock characterize the social arena and ecosystem services continue to erode. Changing climate may continue this trajectory, but it also provides a catalyst for renewal of ecosystems and a window of opportunity for change in institutions. Resilience provides a bridging concept that predicts that change in ecological and social systems is often dramatic, abrupt, and surprising. Adapting to the uncertainty of climate driven change must be done in a manner perceived as legitimate by the participants in a democratic society. Adaptation must begin with the current hierarchical and fragmented social-ecological system as a baseline from which new approaches must be applied. Achieving a level of integration between ecological concepts and governance requires a dialogue across multiple disciplines, including ecologists with expertise in ecological resilience, hydrologists and climate experts, with social scientists and legal scholars. Criteria and models that link ecological dynamics with policies in complex, multi-jurisdictional water basins with adaptive management and governance frameworks may move these social-ecological systems toward greater sustainability.

Simple Climate Model Evaluation Using Impulse Response Tests

NASA Astrophysics Data System (ADS)

Schwarber, A.; Hartin, C.; Smith, S. J.

2017-12-01

Simple climate models (SCMs) are central tools used to incorporate climate responses into human-Earth system modeling. SCMs are computationally inexpensive, making them an ideal tool for a variety of analyses, including consideration of uncertainty. Despite their wide use, many SCMs lack rigorous testing of their fundamental responses to perturbations. Here, following recommendations of a recent National Academy of Sciences report, we compare several SCMs (Hector-deoclim, MAGICC 5.3, MAGICC 6.0, and the IPCC AR5 impulse response function) to diagnose model behavior and understand the fundamental system responses within each model. We conduct stylized perturbations (emissions and forcing/concentration) of three different chemical species: CO2, CH4, and BC. We find that all 4 models respond similarly in terms of overall shape, however, there are important differences in the timing and magnitude of the responses. For example, the response to a BC pulse differs over the first 20 years after the pulse among the models, a finding that is due to differences in model structure. Such perturbation experiments are difficult to conduct in complex models due to internal model noise, making a direct comparison with simple models challenging. We can, however, compare the simplified model response from a 4xCO2 step experiment to the same stylized experiment carried out by CMIP5 models, thereby testing the ability of SCMs to emulate complex model results. This work allows an assessment of how well current understanding of Earth system responses are incorporated into multi-model frameworks by way of simple climate models.

The Sun, Its Extended Corona, the Interplanetary Space, the Earth's Magnetosphere, Ionosphere, Middle and Low Atmosphere, are All Parts of a Complex System - the Heliosphere

NASA Technical Reports Server (NTRS)

Gopalswamy, Natchimuthuk

2011-01-01

Various manifestations of solar activity cause disturbances known as space weather effects in the interplanetary space, near-Earth environment, and all the Earth's "spheres. Longterm variations in the frequency, intensity and relative importance of the manifestations of solar activity are due to the slow changes in the output of the solar dynamo, and they define space climate. Space climate governs long-term variations in geomagnetic activity and is the primary natural driver of terrestrial climate. To understand how the variable solar activity affects the Earth's environment, geomagnetic activity and climate on both short and long time scales, we need to understand the origins of solar activity itself and its different manifestations, as well as the sequence of coupling processes linking various parts of the system. This session provides a forum to discuss the chain of processes and relations from the Sun to the Earth's surface: the origin and long-term and short-term evolution of solar activity, initiation and temporal variations in solar flares, CMEs, coronal holes, the solar wind and its interaction with the terrestrial magnetosphere, the ionosphere and its connection to the neutral dominated regions below and the plasma dominated regions above, the stratosphere, its variations due to the changing solar activity and its interactions with the underlying troposphere, and the mechanisms of solar influences on the lower atmosphere on different time-scales. Particularly welcome are papers highlighting the coupling processes between the different domains in this complex system.

Windblown Dust and Air Quality Under a Changing Climate in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Sharratt, B. S.; Tatarko, J.; Abatzoglou, J. T.; Fox, F.; Huggins, D. R.

2016-12-01

Wind erosion is a concern for sustainable agriculture and societal health in the US Pacific Northwest. Indeed, wind erosion continues to cause exceedances of the National Ambient Air Quality Standard for PM10 in the region. Can we expect air quality to deteriorate or improve as climate changes? Will wind erosion escalate in the future under a warmer and drier climate as forecast for Australia, southern prairies of Canada, northern China, and United States Corn Belt and Colorado Plateau? To answer these questions, we used 18 global climate models, cropping systems simulation model (CropSyst), and the Wind Erosion Prediction System (WEPS) to simulate the complex interactions among climate, crop production, and wind erosion. These simulations were carried out in eastern Washington where wind erosion of agricultural lands contribute to poor air quality in the region. Our results suggest that an increase in temperature and CO2 concentration, coupled with nominal increases in precipitation, will enhance biomass production and reduce soil and PM10 losses by the mid-21st century. This study reveals that climate change may reduce the risk of wind erosion and improve air quality in the Inland Pacific Northwest.

Climate Change, Foodborne Pathogens and Illness in Higher-Income Countries.

PubMed

Lake, I R; Barker, G C

2018-03-01

We present a review of the likely consequences of climate change for foodborne pathogens and associated human illness in higher-income countries. The relationships between climate and food are complex and hence the impacts of climate change uncertain. This makes it difficult to know which foodborne pathogens will be most affected, what the specific effects will be, and on what timescales changes might occur. Hence, a focus upon current capacity and adaptation potential against foodborne pathogens is essential. We highlight a number of developments that may enhance preparedness for climate change. These include the following: Adoption of novel surveillance methods, such as syndromic methods, to speed up detection and increase the fidelity of intervention in foodborne outbreaks Genotype-based approaches to surveillance of food pathogens to enhance spatiotemporal resolution in tracing and tracking of illness Ever increasing integration of plant, animal and human surveillance systems, One Health, to maximise potential for identifying threats Increased commitment to cross-border (global) information initiatives (including big data) Improved clarity regarding the governance of complex societal issues such as the conflict between food safety and food waste Strong user-centric (social) communications strategies to engage diverse stakeholder groups The impact of climate change upon foodborne pathogens and associated illness is uncertain. This emphasises the need to enhance current capacity and adaptation potential against foodborne illness. A range of developments are explored in this paper to enhance preparedness.

Topography alters tree growth–climate relationships in a semi-arid forested catchment

DOE PAGES

Adams, Hallie R.; Barnard, Holly R.; Loomis, Alexander K.

2014-11-26

Topography and climate play an integral role in the spatial variability and annual dynamics of aboveground carbon sequestration. Despite knowledge of vegetation–climate–topography relationships on the landscape and hillslope scales, little is known about the influence of complex terrain coupled with hydrologic and topoclimatic variation on tree growth and physiology at the catchment scale. Climate change predictions for the semi-arid, western United States include increased temperatures, more frequent and extreme drought events, and decreases in snowpack, all of which put forests at risk of drought induced mortality and enhanced susceptibility to disturbance events. In this study, we determine how species-specific treemore » growth patterns and water use efficiency respond to interannual climate variability and how this response varies with topographic position. We found that Pinus contorta and Pinus ponderosa both show significant decreases in growth with water-limiting climate conditions, but complex terrain mediates this response by controlling moisture conditions in variable topoclimates. Foliar carbon isotope analyses show increased water use efficiency during drought for Pinus contorta, but indicate no significant difference in water use efficiency of Pinus ponderosa between a drought year and a non-drought year. The responses of the two pine species to climate indicate that semi-arid forests are especially susceptible to changes and risks posed by climate change and that topographic variability will likely play a significant role in determining the future vegetation patterns of semi-arid systems.« less

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

Sr/Ca and δ18O records of a coral from Sanya: reconstructions of temperature and precipitation in the northern South China Sea in the late Holocene

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2016-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

Probabilistic Estimates of Climate Impacts of the Paris Agreement and Contributions from Different Countries.

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Paltsev, S.; Chen, Y. H. H.; Monier, E.; Libardoni, A. G.; Forest, C. E.

2017-12-01

In December of 2015 during COP21 meeting in Paris almost 200 countries signed an agreement pledging to reduce their anthropogenic greenhouse gas (GHG) emissions. Recently USA announced plans to withdraw from the agreement. In this study, we estimate an impact of this decision on future climate using the MIT Integrated Global System Model, which consists of the human activity model, Economic Projection and Policy Analysis (EPPA) model, and a climate model of intermediate complexity, the MIT Earth System Model (MESM). For comparison, we also estimated impacts of possible withdrawals of China, Europe or India. In addition to the "no climate policy" scenario, we consider five emissions scenarios: Paris, Paris_no_USA, Paris_no_EUR and so on. Climate simulations were carried out from 1861 to 2005 driven by prescribed changes in GHGs and natural forcings and them continued to 2100 driven by GHG emissions produced by EPPA model. Because Paris agreement only cover the period up to 2030, last five scenarios were created assuming that emissions or carbon intensity will continue to decrease after 2030 at the same rate as in the 2020-2030 period. To account for uncertainty in climate system response to external forcing, we carry out 400 member ensembles on climate simulations for each scenario. Probability distributions for climate parameters are obtained by comparing simulated climate for 1861 to 2010 with observations. Our analysis shows that, full implementation of Paris agreement (under above-descried assumptions) will increase probability of surface air temperature in the last decade of this century increasing by less than 3oC relative to pre-industrial form about 20% for "no climate policy" to about 86%. Withdrawal of USA, China, Europe or India will decrease this probability to about 63, 67, 75 and 82%, respectively.

Examining Challenges Related to the Production of Actionable Climate Knowledge for Adaptation Decision-Making: A Focus on Climate Knowledge System Producers

NASA Astrophysics Data System (ADS)

Ernst, K.; Preston, B. L.; Tenggren, S.; Klein, R.; Gerger-Swartling, Å.

2017-12-01

Many challenges to adaptation decision-making and action have been identified across peer-reviewed and gray literature. These challenges have primarily focused on the use of climate knowledge for adaptation decision-making, the process of adaptation decision-making, and the needs of the decision-maker. Studies on climate change knowledge systems often discuss the imperative role of climate knowledge producers in adaptation decision-making processes and stress the need for producers to engage in knowledge co-production activities and to more effectively meet decision-maker needs. While the influence of climate knowledge producers on the co-production of science for adaptation decision-making is well-recognized, hardly any research has taken a direct approach to analyzing the challenges that climate knowledge producers face when undertaking science co-production. Those challenges can influence the process of knowledge production and may hinder the creation, utilization, and dissemination of actionable knowledge for adaptation decision-making. This study involves semi-structured interviews, focus groups, and participant observations to analyze, identify, and contextualize the challenges that climate knowledge producers in Sweden face as they endeavor to create effective climate knowledge systems for multiple contexts, scales, and levels across the European Union. Preliminary findings identify complex challenges related to education, training, and support; motivation, willingness, and culture; varying levels of prioritization; professional roles and responsibilities; the type and amount of resources available; and professional incentive structures. These challenges exist at varying scales and levels across individuals, organizations, networks, institutions, and disciplines. This study suggests that the creation of actionable knowledge for adaptation decision-making is not supported across scales and levels in the climate knowledge production landscape. Additionally, enabling the production of actionable knowledge for adaptation decision-making requires multi-level effort beyond the individual level.

Development of Representative Rainfall Periods for Green Infrastructure Design: Connecting the Dots Between Climate, Urban Hydrology and Resilience

NASA Astrophysics Data System (ADS)

Albright, C. M.; Traver, R.; Wadzuk, B.

2017-12-01

Analysis of local-to-regional climate data is critical in understanding how changing patterns in rainfall and other atmospheric conditions can affect urban hydrology. Urbanization has caused hydrologic and ecologic modifications to our land surfaces, and altered the dynamics of urban water cycle in complex ways. Green infrastructure (GI) systems, in their simplest form, reduce runoff and flooding, prevent combined sewer overflows and improve quality of receiving waters. However, when viewed through a more holistic lens, GI systems sit at the nexus of hydrology, climate and energy, yet are rarely designed to account for the impacts of these intersections. We must assess urban hydrologic systems beyond their response to a single event or design storm, incorporating multiple temporal scales and all hydrologic processes. This is of utmost importance to design and characterization of urban GI systems because the resilience of these systems will be dictated by their ability to adapt to future behavior of extreme weather patterns and climate. In this study, we characterize long-term hydrologic conditions in Philadelphia to identify periods of record that are most representative of regional climate characteristics, including a representative rainfall year and longer representative periods. Utility of these datasets will be demonstrated by showing that GI systems are able to sustain effective performance for most expected annual precipitation events. Connections between atmospheric (precipitation and temperature) patterns, GI systems and potential removal mechanisms in the urban hydrologic cycle will be presented for Philadelphia and cities with similar climate characteristics. Establishing such connections is critically needed to not only validate what is already known about urban GI, but more importantly, to advance theory and practice by linking the hydrologic benefits of urban GI to broader concepts such as risk, mitigation of extreme events and sustainable communities.

Impact of climate change on water balance components in Mediterranean rainfed olive orchards under tillage or cover crop soil management

NASA Astrophysics Data System (ADS)

Rodríguez-Carretero, María Teresa; Lorite, Ignacio J.; Ruiz-Ramos, Margarita; Dosio, Alessandro; Gómez, José A.

2013-04-01

The rainfed olive orchards in Southern Spain constitute the main socioeconomic system of the Mediterranean Spanish agriculture. These systems have an elevated level of complexity and require the accurate characterization of crop, climate and soil components for a correct management. It is common the inclusion of cover crops (usually winter cereals or natural cover) intercalated between the olive rows in order to reduce water erosion. Saving limited available water requires specific management, mowing or killing these cover crops in early spring. Thus, under the semi-arid conditions in Southern Spain the management of the cover crops in rainfed olive orchards is essential to avoid a severe impact to the olive orchards yield through depletion of soil water. In order to characterize this agricultural system, a complete water balance model has been developed, calibrated and validated for the semi-arid conditions of Southern Spain, called WABOL (Abazi et al., 2013). In this complex and fragile system, the climate change constitutes a huge threat for its sustainability, currently limited by the availability of water resources, and its forecasted reduction for Mediterranean environments in Southern Spain. The objective of this study was to simulate the impact of climate change on the different components of the water balance in these representative double cropping systems: transpiration of the olive orchard and cover crop, runoff, deep percolation and soil water content. Four climatic scenarios from the FP6 European Project ENSEMBLES were first bias corrected for temperatures and precipitation (Dosio and Paruolo, 2011; Dosio et al., 2012) and, subsequently, used as inputs for the WABOL model for five olive orchard fields located in Southern Spain under different conditions of crop, climate, soils and management, in order to consider as much as possible of the variability detected in the Spanish olive orchards. The first results indicate the significant effect of the cover crop on the transpiration of the olive orchard, indicating that a correct water and soil management is crucial for these systems especially under climate change conditions. Thus, a significant reduction of transpiration was detected when the cover crops were implanted. When the climatic conditions were more limited (reductions of around 21% for the annual precipitation and increases around 13% for reference evapotranspiration), the impact on olive orchards were critical, affecting seriously the profitability of the olive orchards. In this context, cover crops can be considered as part of adaptation strategies. Further studies will be required for the determination of optimal species and varieties to be used as cover crops to reduce the impact of climate change on olive orchards under semi-arid conditions. References Abazi U, Lorite IJ, Cárceles B, Martínez-Raya A, Durán VH, Francia JR, Gómez JA (2013) WABOL: A conceptual water balance model for analyzing rainfall water use in olive orchards under different soil and cover crop Management strategies. Computers and Electronics in Agriculture 91:35-48 Dosio A, Paruolo P (2011) Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, V 116, D16106, doi:10.1029/2011JD015934 Dosio A, Paruolo P, Rojas R (2012) Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research, V 117, D17, doi: 10.1029/2012JD017968

ClimateSpark: An In-memory Distributed Computing Framework for Big Climate Data Analytics

NASA Astrophysics Data System (ADS)

Hu, F.; Yang, C. P.; Duffy, D.; Schnase, J. L.; Li, Z.

2016-12-01

Massive array-based climate data is being generated from global surveillance systems and model simulations. They are widely used to analyze the environment problems, such as climate changes, natural hazards, and public health. However, knowing the underlying information from these big climate datasets is challenging due to both data- and computing- intensive issues in data processing and analyzing. To tackle the challenges, this paper proposes ClimateSpark, an in-memory distributed computing framework to support big climate data processing. In ClimateSpark, the spatiotemporal index is developed to enable Apache Spark to treat the array-based climate data (e.g. netCDF4, HDF4) as native formats, which are stored in Hadoop Distributed File System (HDFS) without any preprocessing. Based on the index, the spatiotemporal query services are provided to retrieve dataset according to a defined geospatial and temporal bounding box. The data subsets will be read out, and a data partition strategy will be applied to equally split the queried data to each computing node, and store them in memory as climateRDDs for processing. By leveraging Spark SQL and User Defined Function (UDFs), the climate data analysis operations can be conducted by the intuitive SQL language. ClimateSpark is evaluated by two use cases using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. One use case is to conduct the spatiotemporal query and visualize the subset results in animation; the other one is to compare different climate model outputs using Taylor-diagram service. Experimental results show that ClimateSpark can significantly accelerate data query and processing, and enable the complex analysis services served in the SQL-style fashion.

'Changing climate, changing health, changing stories' profile: using an EcoHealth approach to explore impacts of climate change on inuit health.

PubMed

Harper, S L; Edge, V L; Cunsolo Willox, A

2012-03-01

Global climate change and its impact on public health exemplify the challenge of managing complexity and uncertainty in health research. The Canadian North is currently experiencing dramatic shifts in climate, resulting in environmental changes which impact Inuit livelihoods, cultural practices, and health. For researchers investigating potential climate change impacts on Inuit health, it has become clear that comprehensive and meaningful research outcomes depend on taking a systemic and transdisciplinary approach that engages local citizens in project design, data collection, and analysis. While it is increasingly recognised that using approaches that embrace complexity is a necessity in public health, mobilizing such approaches from theory into practice can be challenging. In 2009, the Rigolet Inuit Community Government in Rigolet, Nunatsiavut, Canada partnered with a transdisciplinary team of researchers, health practitioners, and community storytelling facilitators to create the Changing Climate, Changing Health, Changing Stories project, aimed at developing a multi-media participatory, community-run methodological strategy to gather locally appropriate and meaningful data to explore climate-health relationships. The goal of this profile paper is to describe how an EcoHealth approach guided by principles of transdisciplinarity, community participation, and social equity was used to plan and implement this climate-health research project. An overview of the project, including project development, research methods, project outcomes to date, and challenges encountered, is presented. Though introduced in this one case study, the processes, methods, and lessons learned are broadly applicable to researchers and communities interested in implementing EcoHealth approaches in community-based research.

The Regional Network for Asian Schistosomiasis and Other Helminth Zoonoses (RNAS(+)) target diseases in face of climate change.

PubMed

Yang, Guo-Jing; Utzinger, Jürg; Lv, Shan; Qian, Ying-Jun; Li, Shi-Zhu; Wang, Qiang; Bergquist, Robert; Vounatsou, Penelope; Li, Wei; Yang, Kun; Zhou, Xiao-Nong

2010-01-01

Climate change-according to conventional wisdom-will result in an expansion of tropical parasitic diseases in terms of latitude and altitude, with vector-borne diseases particularly prone to change. However, although a significant rise in temperature occurred over the past century, there is little empirical evidence whether climate change has indeed favoured infectious diseases. This might be explained by the complex relationship between climate change and the frequency and the transmission dynamics of infectious diseases, which is characterised by nonlinear associations and countless other complex factors governing the distribution of infectious diseases. Here, we explore whether and how climate change might impact on diseases targeted by the Regional Network for Asian Schistosomiasis and Other Helminth Zoonoses (RNAS(+)). We start our review with a short summary of the current evidence-base how climate change affects the distribution of infectious diseases. Next, we introduce biology-based models for predicting the distribution of infectious diseases in a future, warmer world. Two case studies are presented: the classical RNAS(+) disease schistosomiasis and an emerging disease, angiostrongyliasis, focussing on their occurrences in the People's Republic of China. Strengths and limitations of current models for predicting the impact of climate change on infectious diseases are discussed, and we propose model extensions to include social and ecological factors. Finally, we recommend that mitigation and adaptation strategies to diminish potential negative effects of climate change need to be developed in concert with key stakeholders so that surveillance and early-warning systems can be strengthened and the most vulnerable population groups protected. Copyright 2010 Elsevier Ltd. All rights reserved.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

The GLOBE Carbon Cycle Project: Using a systems approach to understand carbon and the Earth's climate system

NASA Astrophysics Data System (ADS)

Silverberg, S. K.; Ollinger, S. V.; Martin, M. E.; Gengarelly, L. M.; Schloss, A. L.; Bourgeault, J. L.; Randolph, G.; Albrechtova, J.

2009-12-01

National Science Content Standards identify systems as an important unifying concept across the K-12 curriculum. While this standard exists, there is a recognized gap in the ability of students to use a systems thinking approach in their learning. In a similar vein, both popular media as well as some educational curricula move quickly through climate topics to carbon footprint analyses without ever addressing the nature of carbon or the carbon cycle. If students do not gain a concrete understanding of carbon’s role in climate and energy they will not be able to successfully tackle global problems and develop innovative solutions. By participating in the GLOBE Carbon Cycle project, students learn to use a systems thinking approach, while at the same time, gaining a foundation in the carbon cycle and it's relation to climate and energy. Here we present the GLOBE Carbon Cycle project and materials, which incorporate a diverse set of activities geared toward upper middle and high school students with a variety of learning styles. A global carbon cycle adventure story and game let students see the carbon cycle as a complete system, while introducing them to systems thinking concepts including reservoirs, fluxes and equilibrium. Classroom photosynthesis experiments and field measurements of schoolyard vegetation brings the global view to the local level. And the use of computer models at varying levels of complexity (effects on photosynthesis, biomass and carbon storage in global biomes, global carbon cycle) not only reinforces systems concepts and carbon content, but also introduces students to an important scientific tool necessary for understanding climate change.

One Teacher, 20 Preschoolers, and a Goldfish Environmental Awareness, Emergent Curriculum, and Documentation

ERIC Educational Resources Information Center

Lewin-Benham, Ann

2006-01-01

Teaching Preschoolers about the environment is hard. Many complex concepts are involved: the interactions among everything on the planet--air, land, water, and all living things; the systems that determine weather and climate, food supply, energy resources, and the quality of life for every plant and animal; systems operating on a planetary scale…

Challenges in predicting climate and environmental effects on vector-borne disease episystems in a changing world.

PubMed

Tabachnick, W J

2010-03-15

Vector-borne pathogens cause enormous suffering to humans and animals. Many are expanding their range into new areas. Dengue, West Nile and Chikungunya have recently caused substantial human epidemics. Arthropod-borne animal diseases like Bluetongue, Rift Valley fever and African horse sickness pose substantial threats to livestock economies around the world. Climate change can impact the vector-borne disease epidemiology. Changes in climate will influence arthropod vectors, their life cycles and life histories, resulting in changes in both vector and pathogen distribution and changes in the ability of arthropods to transmit pathogens. Climate can affect the way pathogens interact with both the arthropod vector and the human or animal host. Predicting and mitigating the effects of future changes in the environment like climate change on the complex arthropod-pathogen-host epidemiological cycle requires understanding of a variety of complex mechanisms from the molecular to the population level. Although there has been substantial progress on many fronts the challenges to effectively understand and mitigate the impact of potential changes in the environment on vector-borne pathogens are formidable and at an early stage of development. The challenges will be explored using several arthropod-borne pathogen systems as illustration, and potential avenues to meet the challenges will be presented.

Transient climate-carbon simulations of planetary geoengineering.

PubMed

Matthews, H Damon; Caldeira, Ken

2007-06-12

Geoengineering (the intentional modification of Earth's climate) has been proposed as a means of reducing CO2-induced climate warming while greenhouse gas emissions continue. Most proposals involve managing incoming solar radiation such that future greenhouse gas forcing is counteracted by reduced solar forcing. In this study, we assess the transient climate response to geoengineering under a business-as-usual CO2 emissions scenario by using an intermediate-complexity global climate model that includes an interactive carbon cycle. We find that the climate system responds quickly to artificially reduced insolation; hence, there may be little cost to delaying the deployment of geoengineering strategies until such a time as "dangerous" climate change is imminent. Spatial temperature patterns in the geoengineered simulation are comparable with preindustrial temperatures, although this is not true for precipitation. Carbon sinks in the model increase in response to geoengineering. Because geoengineering acts to mask climate warming, there is a direct CO2-driven increase in carbon uptake without an offsetting temperature-driven suppression of carbon sinks. However, this strengthening of carbon sinks, combined with the potential for rapid climate adjustment to changes in solar forcing, leads to serious consequences should geoengineering fail or be stopped abruptly. Such a scenario could lead to very rapid climate change, with warming rates up to 20 times greater than present-day rates. This warming rebound would be larger and more sustained should climate sensitivity prove to be higher than expected. Thus, employing geoengineering schemes with continued carbon emissions could lead to severe risks for the global climate system.

The World Climate Exercise: Is (Simulated) Experience Our Best Teacher?

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

2014-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Ecophysiology meets conservation: understanding the role of disease in amphibian population declines

PubMed Central

Blaustein, Andrew R.; Gervasi, Stephanie S.; Johnson, Pieter T. J.; Hoverman, Jason T.; Belden, Lisa K.; Bradley, Paul W.; Xie, Gisselle Y.

2012-01-01

Infectious diseases are intimately associated with the dynamics of biodiversity. However, the role that infectious disease plays within ecological communities is complex. The complex effects of infectious disease at the scale of communities and ecosystems are driven by the interaction between host and pathogen. Whether or not a given host–pathogen interaction results in progression from infection to disease is largely dependent on the physiological characteristics of the host within the context of the external environment. Here, we highlight the importance of understanding the outcome of infection and disease in the context of host ecophysiology using amphibians as a model system. Amphibians are ideal for such a discussion because many of their populations are experiencing declines and extinctions, with disease as an important factor implicated in many declines and extinctions. Exposure to pathogens and the host's responses to infection can be influenced by many factors related to physiology such as host life history, immunology, endocrinology, resource acquisition, behaviour and changing climates. In our review, we discuss the relationship between disease and biodiversity. We highlight the dynamics of three amphibian host–pathogen systems that induce different effects on hosts and life stages and illustrate the complexity of amphibian–host–parasite systems. We then review links between environmental stress, endocrine–immune interactions, disease and climate change. PMID:22566676

Global Climate Change: Valuable Insights from Concordant and Discordant Ice Core Histories

NASA Astrophysics Data System (ADS)

Mosley-Thompson, E.; Thompson, L. G.; Porter, S. E.; Goodwin, B. P.; Wilson, A. B.

2014-12-01

Earth's ice cover is responding to the ongoing large-scale warming driven in part by anthropogenic forces. The highest tropical and subtropical ice fields are dramatically shrinking and/or thinning and unique climate histories archived therein are now threatened, compromised or lost. Many ice fields in higher latitudes are also experiencing and recording climate system changes although these are often manifested in less evident and spectacular ways. The Antarctic Peninsula (AP) has experienced a rapid, widespread and dramatic warming over the last 60 years. Carefully selected ice fields in the AP allow reconstruction of long histories of key climatic variables. As more proxy climate records are recovered it is clear they reflect a combination of expected and unexpected responses to seemingly similar climate forcings. Recently acquired temperature and precipitation histories from the Bruce Plateau are examined within the context provided by other cores recently collected in the AP. Understanding the differences and similarities among these records provides a better understanding of the forces driving climate variability in the AP over the last century. The Arctic is also rapidly warming. The δ18O records from the Bona-Churchill and Mount Logan ice cores from southeast Alaska and southwest Yukon Territory, respectively, do not record this strong warming. The Aleutian Low strongly influences moisture transport to this geographically complex region, yet its interannual variability is preserved differently in these cores located just 110 km apart. Mount Logan is very sensitive to multi-decadal to multi-centennial climate shifts in the tropical Pacific while low frequency variability on Bona-Churchill is more strongly connected to Western Arctic sea ice extent. There is a natural tendency to focus more strongly on commonalities among records, particularly on regional scales. However, it is also important to investigate seemingly poorly correlated records, particularly those from geographically complex settings that appear to be dominated by similar large-scale climatological processes. Better understanding of the spatially and temporally diverse responses in such regions will expand our understanding of the mechanisms forcing climate variability in meteorologically complex environments.

Climate change: effects on animal disease systems and implications for surveillance and control.

PubMed

de La Rocque, S; Rioux, J A; Slingenbergh, J

2008-08-01

Climate driven and other changes in landscape structure and texture, plus more general factors, may create favourable ecological niches for emerging diseases. Abiotic factors impact on vectors, reservoirs and pathogen bionomics and their ability to establish in new ecosystems. Changes in climatic patterns and in seasonal conditions may affect disease behaviour in terms of spread pattern, diffusion range, amplification and persistence in novel habitats. Pathogen invasion may result in the emergence of novel disease complexes, presenting major challenges for the sustainability of future animal agriculture at the global level. In this paper, some of the ecological mechanisms underlying the impact of climatic change on disease transmission and disease spread are further described. Potential effects of different climatic variables on pathogens and host population dynamics and distribution are complex to assess, and different approaches are used to describe the underlying epidemiological processes and the availability of ecological niches for pathogens and vectors. The invasion process can disrupt the long-term co-evolution of species. Pathogens adhering to an r-type strategy (e.g. RNA viruses) may be more inclined to encroach on a novel niche resulting from climate change. However, even when linkage between disease dynamics and climate change are relatively strong, there are other factors changing disease behaviour, and these should be accounted for as well. Overall vulnerability of a given ecosystem is a key variable in this regard. The impact of climate-driven changes varies in different parts of the world and in the different agro-climatic zones. Perhaps priority should go to those geographical areas where the integrity of the ecosystem is most severely affected and the adaptability, in terms of robustness and sustainability of response, relatively low.

Assessing the effects of climate change on aquatic invasive species.

PubMed

Rahel, Frank J; Olden, Julian D

2008-06-01

Different components of global environmental change are typically studied and managed independently, although there is a growing recognition that multiple drivers often interact in complex and nonadditive ways. We present a conceptual framework and empirical review of the interactive effects of climate change and invasive species in freshwater ecosystems. Climate change is expected to result in warmer water temperatures, shorter duration of ice cover, altered streamflow patterns, increased salinization, and increased demand for water storage and conveyance structures. These changes will alter the pathways by which non-native species enter aquatic systems by expanding fish-culture facilities and water gardens to new areas and by facilitating the spread of species during floods. Climate change will influence the likelihood of new species becoming established by eliminating cold temperatures or winter hypoxia that currently prevent survival and by increasing the construction of reservoirs that serve as hotspots for invasive species. Climate change will modify the ecological impacts of invasive species by enhancing their competitive and predatory effects on native species and by increasing the virulence of some diseases. As a result of climate change, new prevention and control strategies such as barrier construction or removal efforts may be needed to control invasive species that currently have only moderate effects or that are limited by seasonally unfavorable conditions. Although most researchers focus on how climate change will increase the number and severity of invasions, some invasive coldwater species may be unable to persist under the new climate conditions. Our findings highlight the complex interactions between climate change and invasive species that will influence how aquatic ecosystems and their biota will respond to novel environmental conditions.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding Climate Uncertainty with an Ocean Focus

NASA Astrophysics Data System (ADS)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599.

Quantifying uncertainties of permafrost carbon-climate feedbacks

NASA Astrophysics Data System (ADS)

Burke, Eleanor J.; Ekici, Altug; Huang, Ye; Chadburn, Sarah E.; Huntingford, Chris; Ciais, Philippe; Friedlingstein, Pierre; Peng, Shushi; Krinner, Gerhard

2017-06-01

The land surface models JULES (Joint UK Land Environment Simulator, two versions) and ORCHIDEE-MICT (Organizing Carbon and Hydrology in Dynamic Ecosystems), each with a revised representation of permafrost carbon, were coupled to the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) intermediate-complexity climate and ocean carbon uptake model. IMOGEN calculates atmospheric carbon dioxide (CO2) and local monthly surface climate for a given emission scenario with the land-atmosphere CO2 flux exchange from either JULES or ORCHIDEE-MICT. These simulations include feedbacks associated with permafrost carbon changes in a warming world. Both IMOGEN-JULES and IMOGEN-ORCHIDEE-MICT were forced by historical and three alternative future-CO2-emission scenarios. Those simulations were performed for different climate sensitivities and regional climate change patterns based on 22 different Earth system models (ESMs) used for CMIP3 (phase 3 of the Coupled Model Intercomparison Project), allowing us to explore climate uncertainties in the context of permafrost carbon-climate feedbacks. Three future emission scenarios consistent with three representative concentration pathways were used: RCP2.6, RCP4.5 and RCP8.5. Paired simulations with and without frozen carbon processes were required to quantify the impact of the permafrost carbon feedback on climate change. The additional warming from the permafrost carbon feedback is between 0.2 and 12 % of the change in the global mean temperature (ΔT) by the year 2100 and 0.5 and 17 % of ΔT by 2300, with these ranges reflecting differences in land surface models, climate models and emissions pathway. As a percentage of ΔT, the permafrost carbon feedback has a greater impact on the low-emissions scenario (RCP2.6) than on the higher-emissions scenarios, suggesting that permafrost carbon should be taken into account when evaluating scenarios of heavy mitigation and stabilization. Structural differences between the land surface models (particularly the representation of the soil carbon decomposition) are found to be a larger source of uncertainties than differences in the climate response. Inertia in the permafrost carbon system means that the permafrost carbon response depends on the temporal trajectory of warming as well as the absolute amount of warming. We propose a new policy-relevant metric - the frozen carbon residence time (FCRt) in years - that can be derived from these complex land surface models and used to quantify the permafrost carbon response given any pathway of global temperature change.

Space-time dependence between energy sources and climate related energy production

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn; Borga, Marco; Creutin, Jean-Dominique; Ramos, Maria-Helena; Tøfte, Lena; Warland, Geir

2014-05-01

The European Renewable Energy Directive adopted in 2009 focuses on achieving a 20% share of renewable energy in the EU overall energy mix by 2020. A major part of renewable energy production is related to climate, called "climate related energy" (CRE) production. CRE production systems (wind, solar, and hydropower) are characterized by a large degree of intermittency and variability on both short and long time scales due to the natural variability of climate variables. The main strategies to handle the variability of CRE production include energy-storage, -transport, -diversity and -information (smart grids). The three first strategies aim to smooth out the intermittency and variability of CRE production in time and space whereas the last strategy aims to provide a more optimal interaction between energy production and demand, i.e. to smooth out the residual load (the difference between demand and production). In order to increase the CRE share in the electricity system, it is essential to understand the space-time co-variability between the weather variables and CRE production under both current and future climates. This study presents a review of the literature that searches to tackle these problems. It reveals that the majority of studies deals with either a single CRE source or with the combination of two CREs, mostly wind and solar. This may be due to the fact that the most advanced countries in terms of wind equipment have also very little hydropower potential (Denmark, Ireland or UK, for instance). Hydropower is characterized by both a large storage capacity and flexibility in electricity production, and has therefore a large potential for both balancing and storing energy from wind- and solar-power. Several studies look at how to better connect regions with large share of hydropower (e.g., Scandinavia and the Alps) to regions with high shares of wind- and solar-power (e.g., green battery North-Sea net). Considering time scales, various studies consider wind and solar power production and their co-fluctuation at small time scales. The multi-scale nature of the variability is less studied, i.e., the potential adverse or favorable co-fluctuation at intermediate time scales involving water scarcity or abundance, is less present in the literature.Our review points out that it could be especially interesting to promote research on how the pronounced large-scale fluctuations in inflow to hydropower (intra-annual run-off) and smaller scale fluctuations in wind- and solar-power interact in an energy system. There is a need to better represent the profound difference between wind-, solar- and hydro-energy sources. On the one hand, they are all directly linked to the 2-D horizontal dynamics of meteorology. On the other hand, the branching structure of hydrological systems transforms this variability and governs the complex combination of natural inflows and reservoir storage.Finally, we note that the CRE production is, in addition to weather, also influenced by the energy system and market, i.e., the energy transport and demand across scales as well as changes of market regulation. The CRE production system lies thus in this nexus between climate, energy systems and market regulations. The work presented is part of the FP7 project COMPLEX (Knowledge based climate mitigation systems for a low carbon economy; http://www.complex.ac.uk)

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.

pyhector: A Python interface for the simple climate model Hector

DOE PAGES

Willner, Sven N.; Hartin, Corinne; Gieseke, Robert

2017-04-01

Here, pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary productionmore » and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system. The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2.« less

Forecasting the Performance of Agroforestry Systems

NASA Astrophysics Data System (ADS)

Luedeling, E.; Shepherd, K.

2014-12-01

Agroforestry has received considerable attention from scientists and development practitioners in recent years. It is recognized as a cornerstone of many traditional agricultural systems, as well as a new option for sustainable land management in currently treeless agricultural landscapes. Agroforestry systems are diverse, but most manifestations supply substantial ecosystem services, including marketable tree products, soil fertility, water cycle regulation, wildlife habitat and carbon sequestration. While these benefits have been well documented for many existing systems, projecting the outcomes of introducing new agroforestry systems, or forecasting system performance under changing environmental or climatic conditions, remains a substantial challenge. Due to the various interactions between system components, the multiple benefits produced by trees and crops, and the host of environmental, socioeconomic and cultural factors that shape agroforestry systems, mechanistic models of such systems quickly become very complex. They then require a lot of data for site-specific calibration, which presents a challenge for their use in new environmental and climatic domains, especially in data-scarce environments. For supporting decisions on the scaling up of agroforestry technologies, new projection methods are needed that can capture system complexity to an adequate degree, while taking full account of the fact that data on many system variables will virtually always be highly uncertain. This paper explores what projection methods are needed for supplying decision-makers with useful information on the performance of agroforestry in new places or new climates. Existing methods are discussed in light of these methodological needs. Finally, a participatory approach to performance projection is proposed that captures system dynamics in a holistic manner and makes probabilistic projections about expected system performance. This approach avoids the temptation to take spuriously precise model results at face value, and it is able to make predictions even where data is scarce. It thus provides a rapid and honest assessment option that can quickly supply decision-makers with system performance estimates, offering an opportunity to improve the targeting of agroforestry interventions.

Complexity Science and the Dynamics of Climate and Communication: Reducing Nursing Home Turnover

ERIC Educational Resources Information Center

Anderson, Ruth A.; Corazzini, Kirsten N.; McDaniel, Reuben R., Jr.

2004-01-01

Purpose: Turnover in nursing homes is a widespread problem adversely affecting care quality. Using complexity theory, we tested the effect of administrative climate, communication patterns, and the interaction between the two on turnover, controlling for facility context. Design and Methods: Perceptions of administrative climate and communication…

Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5

NASA Astrophysics Data System (ADS)

Dufresne, J.-L.; Foujols, M.-A.; Denvil, S.; Caubel, A.; Marti, O.; Aumont, O.; Balkanski, Y.; Bekki, S.; Bellenger, H.; Benshila, R.; Bony, S.; Bopp, L.; Braconnot, P.; Brockmann, P.; Cadule, P.; Cheruy, F.; Codron, F.; Cozic, A.; Cugnet, D.; de Noblet, N.; Duvel, J.-P.; Ethé, C.; Fairhead, L.; Fichefet, T.; Flavoni, S.; Friedlingstein, P.; Grandpeix, J.-Y.; Guez, L.; Guilyardi, E.; Hauglustaine, D.; Hourdin, F.; Idelkadi, A.; Ghattas, J.; Joussaume, S.; Kageyama, M.; Krinner, G.; Labetoulle, S.; Lahellec, A.; Lefebvre, M.-P.; Lefevre, F.; Levy, C.; Li, Z. X.; Lloyd, J.; Lott, F.; Madec, G.; Mancip, M.; Marchand, M.; Masson, S.; Meurdesoif, Y.; Mignot, J.; Musat, I.; Parouty, S.; Polcher, J.; Rio, C.; Schulz, M.; Swingedouw, D.; Szopa, S.; Talandier, C.; Terray, P.; Viovy, N.; Vuichard, N.

2013-05-01

We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.

Regime shifts and panarchies in regional scale social-ecological water systems

EPA Science Inventory

In this article we summarize histories of nonlinear, complex interactions among societal, legal, and ecosystem dynamics in six North American water basins, as they respond to changing climate. These case studies were chosen to explore the conditions for emergence of adaptive gove...

Hydrological modeling of upper Indus Basin and assessment of deltaic ecology

USDA-ARS?s Scientific Manuscript database

Managing water resources is mostly required at watershed scale where the complex hydrology processes and interactions linking land surface, climatic factors and human activities can be studied. Geographical Information System based watershed model; Soil and Water Assessment Tool (SWAT) is applied f...

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

PubMed Central

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

2011-01-01

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production. PMID:22163927

State-Dependence of the Climate Sensitivity in Earth System Models of Intermediate Complexity

NASA Astrophysics Data System (ADS)

Pfister, Patrik L.; Stocker, Thomas F.

2017-10-01

Growing evidence from general circulation models (GCMs) indicates that the equilibrium climate sensitivity (ECS) depends on the magnitude of forcing, which is commonly referred to as state-dependence. We present a comprehensive assessment of ECS state-dependence in Earth system models of intermediate complexity (EMICs) by analyzing millennial simulations with sustained 2×CO2 and 4×CO2 forcings. We compare different extrapolation methods and show that ECS is smaller in the higher-forcing scenario in 12 out of 15 EMICs, in contrast to the opposite behavior reported from GCMs. In one such EMIC, the Bern3D-LPX model, this state-dependence is mainly due to the weakening sea ice-albedo feedback in the Southern Ocean, which depends on model configuration. Due to ocean-mixing adjustments, state-dependence is only detected hundreds of years after the abrupt forcing, highlighting the need for long model integrations. Adjustments to feedback parametrizations of EMICs may be necessary if GCM intercomparisons confirm an opposite state-dependence.

Digital divide, biometeorological data infrastructures and human vulnerability definition

NASA Astrophysics Data System (ADS)

Fdez-Arroyabe, Pablo; Lecha Estela, Luis; Schimt, Falko

2018-05-01

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user's geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.

Digital divide, biometeorological data infrastructures and human vulnerability definition.

PubMed

Fdez-Arroyabe, Pablo; Lecha Estela, Luis; Schimt, Falko

2018-05-01

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user's geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.

Digital divide, biometeorological data infrastructures and human vulnerability definition

NASA Astrophysics Data System (ADS)

Fdez-Arroyabe, Pablo; Lecha Estela, Luis; Schimt, Falko

2017-06-01

The design and implementation of any climate-related health service, nowadays, imply avoiding the digital divide as it means having access and being able to use complex technological devices, massive meteorological data, user's geographic location and biophysical information. This article presents the co-creation, in detail, of a biometeorological data infrastructure, which is a complex platform formed by multiple components: a mainframe, a biometeorological model called Pronbiomet, a relational database management system, data procedures, communication protocols, different software packages, users, datasets and a mobile application. The system produces four daily world maps of the partial density of the atmospheric oxygen and collects user feedback on their health condition. The infrastructure is shown to be a useful tool to delineate individual vulnerability to meteorological changes as one key factor in the definition of any biometeorological risk. This technological approach to study weather-related health impacts is the initial seed for the definition of biometeorological profiles of persons, and for the future development of customized climate services for users in the near future.

Preliminary design study of a baseline MIUS

NASA Technical Reports Server (NTRS)

Wolfer, B. M.; Shields, V. E.; Rippey, J. O.; Roberts, H. L.; Wadle, R. C.; Wallin, S. P.; Gill, W. L.; White, E. H.; Monzingo, R.

1977-01-01

Results of a conceptual design study to establish a baseline design for a modular integrated utility system (MIUS) are presented. The system concept developed a basis for evaluating possible projects to demonstrate an MIUS. For the baseline study, climate conditions for the Washington, D.C., area were used. The baseline design is for a high density apartment complex of 496 dwelling units with a planned full occupancy of approximately 1200 residents. Environmental considerations and regulations for the MIUS installation are discussed. Detailed cost data for the baseline MIUS are given together with those for design and operating variations under climate conditions typified by Las Vegas, Nevada, Houston, Texas, and Minneapolis, Minnesota. In addition, results of an investigation of size variation effects, for 300 and 1000 unit apartment complexes, are presented. Only conceptual aspects of the design are discussed. Results regarding energy savings and costs are intended only as trend information and for use in relative comparisons. Alternate heating, ventilation, and air conditioning concepts are considered in the appendix.

Project Ukko - Design of a climate service visualisation interface for seasonal wind forecasts

NASA Astrophysics Data System (ADS)

Hemment, Drew; Stefaner, Moritz; Makri, Stephann; Buontempo, Carlo; Christel, Isadora; Torralba-Fernandez, Veronica; Gonzalez-Reviriego, Nube; Doblas-Reyes, Francisco; de Matos, Paula; Dykes, Jason

2016-04-01

Project Ukko is a prototype climate service to visually communicate probabilistic seasonal wind forecasts for the energy sector. In Project Ukko, an interactive visualisation enhances the accessibility and readability to the latests advances in seasonal wind speed predictions developed as part of the RESILIENCE prototype of the EUPORIAS (EC FP7) project. Climate services provide made-to-measure climate information, tailored to the specific requirements of different users and industries. In the wind energy sector, understanding of wind conditions in the next few months has high economic value, for instance, for the energy traders. Current energy practices use retrospective climatology, but access to reliable seasonal predictions based in the recent advances in global climate models has potential to improve their resilience to climate variability and change. Despite their potential benefits, a barrier to the development of commercially viable services is the complexity of the probabilistic forecast information, and the challenge of communicating complex and uncertain information to decision makers in industry. Project Ukko consists of an interactive climate service interface for wind energy users to explore probabilistic wind speed predictions for the coming season. This interface enables fast visual detection and exploration of interesting features and regions likely to experience unusual changes in wind speed in the coming months.The aim is not only to support users to better understand the future variability in wind power resources, but also to bridge the gap between practitioners' traditional approach and the advanced prediction systems developed by the climate science community. Project Ukko is presented as a case study of cross-disciplinary collaboration between climate science and design, for the development of climate services that are useful, usable and effective for industry users. The presentation will reflect on the challenge of developing a climate service for industry users in the wind energy sector, the background to this challenge, our approach, and the evaluation of the visualisation interface.

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.

Causal Chains Arising from Climate Change in Mountain Regions: the Core Program of the Mountain Research Initiative

NASA Astrophysics Data System (ADS)

Greenwood, G. B.

2014-12-01

Mountains are a widespread terrestrial feature, covering from 12 to 24 percent of the world's terrestrial surface, depending of the definition. Topographic relief is central to the definition of mountains, to the benefits and costs accruing to society and to the cascade of changes expected from climate change. Mountains capture and store water, particularly important in arid regions and in all areas for energy production. In temperate and boreal regions, mountains have a great range in population densities, from empty to urban, while tropical mountains are often densely settled and farmed. Mountain regions contain a wide range of habitats, important for biodiversity, and for primary, secondary and tertiary sectors of the economy. Climate change interacts with this relief and consequent diversity. Elevation itself may accentuate warming (elevationi dependent warming) in some mountain regions. Even average warming starts complex chains of causality that reverberate through the diverse social ecological mountain systems affecting both the highlands and adjacent lowlands. A single feature of climate change such as higher snow lines affect the climate through albedo, the water cycle through changes in timing of release , water quality through the weathering of newly exposed material, geomorphology through enhanced erosion, plant communities through changes in climatic water balance, and animal and human communities through changes in habitat conditions and resource availabilities. Understanding these causal changes presents a particular interdisciplinary challenge to researchers, from assessing the existence and magnitude of elevation dependent warming and monitoring the full suite of changes within the social ecological system to climate change, to understanding how social ecological systems respond through individual and institutional behavior with repercussions on the long-term sustainability of these systems.

Climate mitigation is not the only benefit of a national energy system

NASA Astrophysics Data System (ADS)

Clack, C.

2016-12-01

Many speculate that the main driving force for a continental scale energy system is for climate mitigation. While this is a strong driver, there are multiple co-benefits that emerge from such a transition when purely driven by costs. These components could be managed within a planned system to provide a close-to-optimal solution that enhances the probability of realization. It is shown that these co-benefits of a continental scale electric system occur at costs lower than existing ones. That means there are multiple additional savings without extra costs or effort. The disadvantage is coordination between large geographic regions that could cause more complexity in planning. The main finding from different versions of the NEWS simulator is that carbon mitigation is enhanced by larger systems. In addition, there are increased jobs, reduced water consumption, Sulphur dioxide emissions, Nitrogen oxide emissions, a more distributed electric system and a lower cost of electricity.

Two Case Studies to Quantify Resilience across Food-Energy-Water Systems: the Columbia River Treaty and Adaptation in Yakima River Basin Irrigation Systems

NASA Astrophysics Data System (ADS)

Malek, K.; Adam, J. C.; Richey, A.; Rushi, B. R.; Stockle, C.; Yoder, J.; Barik, M.; Lee, S. Y.; Rajagopalan, K.; Brady, M.; Barber, M. E.; Boll, J.; Padowski, J.

2017-12-01

The U.S. Pacific Northwest (PNW) plays a significant role in meeting agricultural and hydroelectric demands nationwide. Climatic and anthropogenic stressors, however, potentially threaten the productivity, resilience, and environmental health of the region. Our objective is to understand how resilience of each Food-Energy-Water (FEW) sector, and the combined Nexus, respond to exogenous perturbations and the extent to which technological and institutional advances can buffer these perturbations. In the process of taking information from complex integrated models and assessing resilience across FEW sectors, we start with two case studies: 1) Columbia River Treaty (CRT) with Canada that determines how multiple reservoirs in the Columbia River basin (CRB) are operated, and 2) climate change adaptation actions in the Yakima River basin (YRB). We discuss these case studies in terms of the similarities and contrasts related to FEW sectors and management complexities. Both the CRB and YBP systems are highly sensitive to climate change (they are both snowmelt-dominant) and already experience water conflict. The CRT is currently undergoing renegotiation; a new CRT will need to consider a much more comprehensive approach, e.g., treating environmental flows explicitly. The YRB also already experiences significant water conflict and thus the comprehensive Yakima Basin Integrated Plan (YBIP) is being pursued. We apply a new modeling framework that mechanistically captures the interactions between the FEW sectors to quantify the impacts of CRT and YBIP planning (as well as adaptation decisions taken by individuals, e.g., irrigators) on resilience in each sector. Proposed modification to the CRT may relieve impacts to multiple sectors. However, in the YRB, irrigators' actions to adapt to climate change (through investing in more efficient irrigation technology) could reduce downstream water availability for other users. Developing a process to quantify resilience to perturbations, such as climate change, will enable innovative solutions that co-balance benefits, and ultimately increase resilience, across all FEW sectors.

Compilation of Abstracts for SC12 Conference Proceedings

NASA Technical Reports Server (NTRS)

Morello, Gina Francine (Compiler)

2012-01-01

1 A Breakthrough in Rotorcraft Prediction Accuracy Using Detached Eddy Simulation; 2 Adjoint-Based Design for Complex Aerospace Configurations; 3 Simulating Hypersonic Turbulent Combustion for Future Aircraft; 4 From a Roar to a Whisper: Making Modern Aircraft Quieter; 5 Modeling of Extended Formation Flight on High-Performance Computers; 6 Supersonic Retropropulsion for Mars Entry; 7 Validating Water Spray Simulation Models for the SLS Launch Environment; 8 Simulating Moving Valves for Space Launch System Liquid Engines; 9 Innovative Simulations for Modeling the SLS Solid Rocket Booster Ignition; 10 Solid Rocket Booster Ignition Overpressure Simulations for the Space Launch System; 11 CFD Simulations to Support the Next Generation of Launch Pads; 12 Modeling and Simulation Support for NASA's Next-Generation Space Launch System; 13 Simulating Planetary Entry Environments for Space Exploration Vehicles; 14 NASA Center for Climate Simulation Highlights; 15 Ultrascale Climate Data Visualization and Analysis; 16 NASA Climate Simulations and Observations for the IPCC and Beyond; 17 Next-Generation Climate Data Services: MERRA Analytics; 18 Recent Advances in High-Resolution Global Atmospheric Modeling; 19 Causes and Consequences of Turbulence in the Earths Protective Shield; 20 NASA Earth Exchange (NEX): A Collaborative Supercomputing Platform; 21 Powering Deep Space Missions: Thermoelectric Properties of Complex Materials; 22 Meeting NASA's High-End Computing Goals Through Innovation; 23 Continuous Enhancements to the Pleiades Supercomputer for Maximum Uptime; 24 Live Demonstrations of 100-Gbps File Transfers Across LANs and WANs; 25 Untangling the Computing Landscape for Climate Simulations; 26 Simulating Galaxies and the Universe; 27 The Mysterious Origin of Stellar Masses; 28 Hot-Plasma Geysers on the Sun; 29 Turbulent Life of Kepler Stars; 30 Modeling Weather on the Sun; 31 Weather on Mars: The Meteorology of Gale Crater; 32 Enhancing Performance of NASAs High-End Computing Applications; 33 Designing Curiosity's Perfect Landing on Mars; 34 The Search Continues: Kepler's Quest for Habitable Earth-Sized Planets.

iMarNet: an ocean biogeochemistry model inter-comparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-07-01

Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low resolution climate dynamics and high complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-12-01

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

The Role of Snow and Ice in the Climate System

ScienceCinema

Barry, Roger G.

2017-12-09

Global snow and ice cover (the 'cryosphere') plays a major role in global climate and hydrology through a range of complex interactions and feedbacks, the best known of which is the ice - albedo feedback. Snow and ice cover undergo marked seasonal and long term changes in extent and thickness. The perennial elements - the major ice sheets and permafrost - play a role in present-day regional and local climate and hydrology, but the large seasonal variations in snow cover and sea ice are of importance on continental to hemispheric scales. The characteristics of these variations, especially in the Northern Hemisphere, and evidence for recent trends in snow and ice extent are discussed.

An improved land biosphere module for use in the DCESS Earth system model (version 1.1) with application to the last glacial termination

NASA Astrophysics Data System (ADS)

Eichinger, Roland; Shaffer, Gary; Albarrán, Nelson; Rojas, Maisa; Lambert, Fabrice

2017-09-01

Interactions between the land biosphere and the atmosphere play an important role for the Earth's carbon cycle and thus should be considered in studies of global carbon cycling and climate. Simple approaches are a useful first step in this direction but may not be applicable for certain climatic conditions. To improve the ability of the reduced-complexity Danish Center for Earth System Science (DCESS) Earth system model DCESS to address cold climate conditions, we reformulated the model's land biosphere module by extending it to include three dynamically varying vegetation zones as well as a permafrost component. The vegetation zones are formulated by emulating the behaviour of a complex land biosphere model. We show that with the new module, the size and timing of carbon exchanges between atmosphere and land are represented more realistically in cooling and warming experiments. In particular, we use the new module to address carbon cycling and climate change across the last glacial transition. Within the constraints provided by various proxy data records, we tune the DCESS model to a Last Glacial Maximum state and then conduct transient sensitivity experiments across the transition under the application of explicit transition functions for high-latitude ocean exchange, atmospheric dust, and the land ice sheet extent. We compare simulated time evolutions of global mean temperature, pCO2, atmospheric and oceanic carbon isotopes as well as ocean dissolved oxygen concentrations with proxy data records. In this way we estimate the importance of different processes across the transition with emphasis on the role of land biosphere variations and show that carbon outgassing from permafrost and uptake of carbon by the land biosphere broadly compensate for each other during the temperature rise of the early last deglaciation.

A Semi-empirical Model of the Stratosphere in the Climate System

NASA Astrophysics Data System (ADS)

Sodergren, A. H.; Bodeker, G. E.; Kremser, S.; Meinshausen, M.; McDonald, A.

2014-12-01

Chemistry climate models (CCMs) currently used to project changes in Antarctic ozone are extremely computationally demanding. CCM projections are uncertain due to lack of knowledge of future emissions of greenhouse gases (GHGs) and ozone depleting substances (ODSs), as well as parameterizations within the CCMs that have weakly constrained tuning parameters. While projections should be based on an ensemble of simulations, this is not currently possible due to the complexity of the CCMs. An inexpensive but realistic approach to simulate changes in stratospheric ozone, and its coupling to the climate system, is needed as a complement to CCMs. A simple climate model (SCM) can be used as a fast emulator of complex atmospheric-ocean climate models. If such an SCM includes a representation of stratospheric ozone, the evolution of the global ozone layer can be simulated for a wide range of GHG and ODS emissions scenarios. MAGICC is an SCM used in previous IPCC reports. In the current version of the MAGICC SCM, stratospheric ozone changes depend only on equivalent effective stratospheric chlorine (EESC). In this work, MAGICC is extended to include an interactive stratospheric ozone layer using a semi-empirical model of ozone responses to CO2and EESC, with changes in ozone affecting the radiative forcing in the SCM. To demonstrate the ability of our new, extended SCM to generate projections of global changes in ozone, tuning parameters from 19 coupled atmosphere-ocean general circulation models (AOGCMs) and 10 carbon cycle models (to create an ensemble of 190 simulations) have been used to generate probability density functions of the dates of return of stratospheric column ozone to 1960 and 1980 levels for different latitudes.

Variable Trends in High Peak Flow Generation Across the Swedish Sub-Arctic

NASA Astrophysics Data System (ADS)

Matti, B.; Dahlke, H. E.; Lyon, S. W.

2015-12-01

There is growing concern about increased frequency and severity of floods and droughts globally in recent years. Improving knowledge on the complexity of hydrological systems and their interactions with climate is essential to be able to determine drivers of these extreme events and to predict changes in these drivers under altered climate conditions. This is particularly true in cold regions such as the Swedish Sub-Arctic where independent shifts in both precipitation and temperature can have significant influence on extremes. This study explores changes in the magnitude and timing of the annual maximum daily flows in 18 Swedish sub-arctic catchments. The Mann-Kendall trend test was used to estimate changes in selected hydrological signatures. Further, a flood frequency analysis was conducted by fitting a Gumbel (Extreme Value type I) distribution whereby selected flood percentiles were tested for stationarity using a generalized least squares regression approach. Our results showed that hydrological systems in cold climates have complex, heterogeneous interactions with climate. Shifts from a snowmelt-dominated to a rainfall-dominated flow regime were evident with all significant trends pointing towards (1) lower flood magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest permafrost thawing and are in agreement with the increasing trends in annual minimum flows. Trends in the selected flood percentiles showed an increase in extreme events over the entire period of record, while trends were variable under shorter periods. A thorough uncertainty analysis emphasized that the applied trend test is highly sensitive to the period of record considered. As such, no clear overall regional pattern could be determined suggesting that how catchments are responding to changes in climatic drivers is strongly influenced by their physical characteristics.

Development and application of earth system models.

PubMed

Prinn, Ronald G

2013-02-26

The global environment is a complex and dynamic system. Earth system modeling is needed to help understand changes in interacting subsystems, elucidate the influence of human activities, and explore possible future changes. Integrated assessment of environment and human development is arguably the most difficult and most important "systems" problem faced. To illustrate this approach, we present results from the integrated global system model (IGSM), which consists of coupled submodels addressing economic development, atmospheric chemistry, climate dynamics, and ecosystem processes. An uncertainty analysis implies that without mitigation policies, the global average surface temperature may rise between 3.5 °C and 7.4 °C from 1981-2000 to 2091-2100 (90% confidence limits). Polar temperatures, absent policy, are projected to rise from about 6.4 °C to 14 °C (90% confidence limits). Similar analysis of four increasingly stringent climate mitigation policy cases involving stabilization of greenhouse gases at various levels indicates that the greatest effect of these policies is to lower the probability of extreme changes. The IGSM is also used to elucidate potential unintended environmental consequences of renewable energy at large scales. There are significant reasons for attention to climate adaptation in addition to climate mitigation that earth system models can help inform. These models can also be applied to evaluate whether "climate engineering" is a viable option or a dangerous diversion. We must prepare young people to address this issue: The problem of preserving a habitable planet will engage present and future generations. Scientists must improve communication if research is to inform the public and policy makers better.

Groundwater in the Boreal Plains: How Climate and Geology Interact to Control Water Table Configurations in a Sub-Humid, Low-Relief Region

NASA Astrophysics Data System (ADS)

Hokanson, K. J.; Devito, K.; Mendoza, C. A.

2017-12-01

The Boreal Plain (BP) region of Canada, a landscape characterized by low-relief, a sub-humid climate and heterogeneous glacial landforms, is experiencing unprecedented anthropogenic and natural disturbance, including climate change and oil & gas operations. Understanding the controls on and the natural variability of water table position, and subsequently predicting changes in water table position under varying physical and climatic scenarios will become important as water security becomes increasingly threatened. The BP is composed of a mosaic of forestland, wetland, and aquatic land covers that contrast in dominant vegetation cover, evapotranspiration, and soil storage that, in turn, influence water table configurations. Additionally, these land-covers overlie heterogeneous glacial landforms with large contrasts in storage and hydraulic properties which, when coupled with wet-dry climate cycles, result in complex water table distributions in time and space. Several forestland-wetland-pond complexes were selected at the Utikuma Research Study Area (URSA) over three distinct surficial geologic materials (glacial fluvial outwash, stagnant ice moraine, lacustrine clay plain) to explore the roles of climate (cumulative departure from the long term yearly mean precipitation), geology, topographic position, and land cover on water table configurations over 15 years (2002 - 2016). In the absence of large groundwater flow systems, local relief and shallow low conductivity substrates promote the formation of near-surface water tables that are less susceptible to climate variation, regardless of topography. Furthermore, in areas of increased storage, wet and dry climate conditions can result in appreciably different water table configurations over time, ranging from mounds to hydraulic depressions, depending on the arrangement of land-covers, dominant surficial geology, and substrate layering.

Preparing Teachers to Support the Development of Climate Literate Students

NASA Astrophysics Data System (ADS)

Haddad, N.; Ledley, T. S.; Ellins, K. K.; Bardar, E. W.; Youngman, E.; Dunlap, C.; Lockwood, J.; Mote, A. S.; McNeal, K.; Libarkin, J. C.; Lynds, S. E.; Gold, A. U.

2014-12-01

The EarthLabs climate project includes curriculum development, teacher professional development, teacher leadership development, and research on student learning, all directed at increasing high school teachers' and students' understanding of the factors that shape our planet's climate. The project has developed four new modules which focus on climate literacy and which are part of the larger Web based EarthLabs collection of Earth science modules. Climate related themes highlighted in the new modules include the Earth system with its positive and negative feedback loops; the range of temporal and spatial scales at which climate, weather, and other Earth system processes occur; and the recurring question, "How do we know what we know about Earth's past and present climate?" which addresses proxy data and scientific instrumentation. EarthLabs climate modules use two central strategies to help students navigate the multiple challenges inherent in understanding climate science. The first is to actively engage students with the content by using a variety of learning modes, and by allowing students to pace themselves through interactive visualizations that address particularly challenging content. The second strategy, which is the focus of this presentation, is to support teachers in a subject area where few have substantive content knowledge or technical skills. Teachers who grasp the processes and interactions that give Earth its climate and the technical skills to engage with relevant data and visualizations are more likely to be successful in supporting students' understanding of climate's complexities. This presentation will briefly introduce the EarthLabs project and will describe the steps the project takes to prepare climate literate teachers, including Web based resources, teacher workshops, and the development of a cadre of teacher leaders who are prepared to continue leading the workshops after project funding ends.

Near real time observational data collection for SPRUCE experiment- PakBus protocol for slow satellite connections

NASA Astrophysics Data System (ADS)

Krassovski, Misha; Hanson, Paul; Riggs, Jeff

2017-04-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This publication shares our experience of establishing near real time data collection and monitoring system via a satellite link using PakBus protocol.

Satellite Observations of the Effect of Natural and Anthropogenic Aerosols on Clouds

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2006-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with clouds and precipitation is still lacking despite decades of research. Understanding the global aerosol system is critical to quantifying anthropogenic climate change, to determine climate sensitivity from observations and to understand the hydrological cycle. While a single instrument was used to demonstrate 50 years ago that the global CO2 levels are rising, posing threat of global warming, we need an array of satellites and field measurements coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week) and variable chemical composition. A new generation of satellites provides exciting opportunities to measure the global distribution of aerosols, distinguishing natural from anthropogenic aerosol and measuring their interaction with clouds and climate.

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

Assessing Flood Risk at Nuclear Power Plants with an Uncertain Climate

NASA Astrophysics Data System (ADS)

Wigmosta, M. S.; Vail, L. W.

2011-12-01

In 2010 a tsunami severely damaged the Fukushima Dai-ichi Nuclear Power Plant in Japan. As a result, the U.S. Nuclear Regulatory Commission directed that a systematic and methodical review of Commission processes and regulations be performed to determine whether the agency should make additional improvements to its regulatory system and to make recommendations to the Commission. Two of the recommendations of the Task Force created to inform the Commission were: establish a logical, systematic, and coherent regulatory framework for adequate protection that appropriately balances defense-in-depth and risk considerations and that the NRC require licensees to reevaluate and upgrade as necessary the design-basis flooding protection of structures, systems, and components for each operating reactor. These recommendations came at the same time as technical discussions about updating approaches to evaluate flood hazard were underway. These discussions included: consideration of climate nonstationarity in flood assessments; transitioning from PMP/PMF assessments to probabilistic flood analyses to better align with risk-informed decision making; and systematic consideration of combined events in flood risk analysis. There is no scientific basis to assume that shifts in long-term mean precipitation and temperature (such as is commonly derived from climate models) relate to flood probability. Flood mechanisms are often more complex and reflect climate pattern anomalies more than mean annual shifts. Instead of discounting historical data due to climatic nonstationarity, it is important to better understand the climate patterns that have triggered floods in the past and to look to climate forecasts to understand the likely changes in the frequency of those historical climate patterns with climate change. It is equally important to have a better understanding of whether climate change will result in flood-generating climate systems heretofore unknown in the particular locale. This presentation will provide a roadmap to ensuring that the flood hazards of existing and future nuclear power plants are well defined.

A Coupled Regional Climate Simulator for the Gulf of St. Lawrence, Canada

NASA Astrophysics Data System (ADS)

Faucher, M.; Saucier, F.; Caya, D.

2003-12-01

The climate of Eastern Canada is characterized by atmosphere-ocean-ice interactions due to the closeness of the North Atlantic Ocean and the Labrador Sea. Also, there are three relatively large inner basins: the Gulf of St-Lawrence, the Hudson Bay / Hudson Strait / Foxe Basin system and the Great Lakes, influencing the evolution of weather systems and therefore the regional climate. These basins are characterized by irregular coastlines and variables sea-ice in winter, so that the interactions between the atmosphere and the ocean are more complex. There are coupled general circulation models (GCMs) that are available to study the climate of Eastern Canada, but their resolution (near 350km) is to low to resolve the details of the regional climate of this area and to provide valuable information for climate impact studies. The goal of this work is to develop a coupled regional climate simulator for Eastern Canada to study the climate and its variability, necessary to assess the future climate in a double CO2 situation. An off-line coupling strategy through the interacting fields is used to link the Canadian Regional Climate Model developed at the "Universite du Quebec a Montreal" (CRCM, Caya and Laprise 1999) to the Gulf of St. Lawrence ocean model developed at the "Institut Maurice-Lamontagne" (GOM, Saucier et al. 2002). This strategy involves running both simulators separately and alternatively, using variables from the other simulator to supply the needed forcing fields every day. We present the results of a first series of seasonal simulations performed with this system to show the ability of our climate simulator to reproduce the known characteristics of the regional circulation such as mesoscale oceanic features, fronts and sea-ice. The simulations were done for the period from December 1st, 1989 to March 31st, 1990. The results are compared with those of previous uncoupled runs (Faucher et al. 2003) and with observations.

A walk on the tundra: Host-parasite interactions in an extreme environment.

PubMed

Kutz, Susan J; Hoberg, Eric P; Molnár, Péter K; Dobson, Andy; Verocai, Guilherme G

2014-08-01

Climate change is occurring very rapidly in the Arctic, and the processes that have taken millions of years to evolve in this very extreme environment are now changing on timescales as short as decades. These changes are dramatic, subtle and non-linear. In this article, we discuss the evolving insights into host-parasite interactions for wild ungulate species, specifically, muskoxen and caribou, in the North American Arctic. These interactions occur in an environment that is characterized by extremes in temperature, high seasonality, and low host species abundance and diversity. We believe that lessons learned in this system can guide wildlife management and conservation throughout the Arctic, and can also be generalized to more broadly understand host-parasite interactions elsewhere. We specifically examine the impacts of climate change on host-parasite interactions and focus on: (I) the direct temperature effects on parasites; (II) the importance of considering the intricacies of host and parasite ecology for anticipating climate change impacts; and (III) the effect of shifting ecological barriers and corridors. Insights gained from studying the history and ecology of host-parasite systems in the Arctic will be central to understanding the role that climate change is playing in these more complex systems.

A walk on the tundra: Host–parasite interactions in an extreme environment

PubMed Central

Kutz, Susan J.; Hoberg, Eric P.; Molnár, Péter K.; Dobson, Andy; Verocai, Guilherme G.

2014-01-01

Climate change is occurring very rapidly in the Arctic, and the processes that have taken millions of years to evolve in this very extreme environment are now changing on timescales as short as decades. These changes are dramatic, subtle and non-linear. In this article, we discuss the evolving insights into host–parasite interactions for wild ungulate species, specifically, muskoxen and caribou, in the North American Arctic. These interactions occur in an environment that is characterized by extremes in temperature, high seasonality, and low host species abundance and diversity. We believe that lessons learned in this system can guide wildlife management and conservation throughout the Arctic, and can also be generalized to more broadly understand host–parasite interactions elsewhere. We specifically examine the impacts of climate change on host–parasite interactions and focus on: (I) the direct temperature effects on parasites; (II) the importance of considering the intricacies of host and parasite ecology for anticipating climate change impacts; and (III) the effect of shifting ecological barriers and corridors. Insights gained from studying the history and ecology of host–parasite systems in the Arctic will be central to understanding the role that climate change is playing in these more complex systems. PMID:25180164

Emerging Methane Sources: A Bang or Whimper? (Invited)

NASA Astrophysics Data System (ADS)

Harriss, R. C.

2013-12-01

In this presentation we examine two emerging methane emission sources that may further accelerate climate change in the 21st century: 1) Will fugitive methane emissions associated with the development of unconventional natural gas resources pose a significant threat of accelerating climate change? 2) Will continued warming of Arctic regions destabilize permafrost and methane hydrates rapidly increasing global atmospheric methane that results in a catastrophic climate change emergency? These risks are currently described in two different guises, with unconventional gas as persistent and gradually unfolding threat and Arctic rapid warming and release of methane as a low-probability event that could in an instant change everything. Current research is far from answering the question of whether these emerging methane sources will lead to a climate change bang or whimper. Both issues reflect the need to understand complex environmental and engineered systems as they interact with social and economic forces. While the evolution of energy systems favors methane as a contemporary transition fuel, researchers and practitioners need to address the fugitive methane leakage, reliability, and safety of natural gas systems. The concept of a methane bridge as a viable direction to decarbonization is appealing; it's just not as big or fast a step as many scientists want.

Constructing Scientific Arguments Using Evidence from Dynamic Computational Climate Models

NASA Astrophysics Data System (ADS)

Pallant, Amy; Lee, Hee-Sun

2015-04-01

Modeling and argumentation are two important scientific practices students need to develop throughout school years. In this paper, we investigated how middle and high school students ( N = 512) construct a scientific argument based on evidence from computational models with which they simulated climate change. We designed scientific argumentation tasks with three increasingly complex dynamic climate models. Each scientific argumentation task consisted of four parts: multiple-choice claim, openended explanation, five-point Likert scale uncertainty rating, and open-ended uncertainty rationale. We coded 1,294 scientific arguments in terms of a claim's consistency with current scientific consensus, whether explanations were model based or knowledge based and categorized the sources of uncertainty (personal vs. scientific). We used chi-square and ANOVA tests to identify significant patterns. Results indicate that (1) a majority of students incorporated models as evidence to support their claims, (2) most students used model output results shown on graphs to confirm their claim rather than to explain simulated molecular processes, (3) students' dependence on model results and their uncertainty rating diminished as the dynamic climate models became more and more complex, (4) some students' misconceptions interfered with observing and interpreting model results or simulated processes, and (5) students' uncertainty sources reflected more frequently on their assessment of personal knowledge or abilities related to the tasks than on their critical examination of scientific evidence resulting from models. These findings have implications for teaching and research related to the integration of scientific argumentation and modeling practices to address complex Earth systems.

Data gathering and simulation of climate change impacts in mountainous areas

NASA Astrophysics Data System (ADS)

Bachelet, D.; Baker, B.; Hicke, J.; Conklin, D.; McKelvey, K.

2007-12-01

High mountains include species most at risk in a warming environment and are a critical link in the water supply chain for both human and natural systems. Scientists are monitoring and simulating these systems as snowpack depth changes, snowmelt timing changes, frozen soils melt and destabilize, and low elevation populations migrate upslope. Natural climate cycles and human activities interact with climate change trends and complicate the interpretation of the signal we observe. For ex. over the past 4 years in Yunnan (China), we documented that herbaceous alpine meadows are contracting as forest tree line advances and alpine shrub biomass increases. This is a result of interactions between human land use alteration and observed shifts in climate. In North America as snowpack decreases, wolverines and lynx denning conditions are jeopardized as human pressure reduces their extent. Coarse scale vegetation shift models using downscaled future climate scenarios fail to capture complex terrain features and microclimatic conditions that can either ensure critical habitat for the in-situ survival of threatened species or make things worse (ex. rockfalls) for climate migrants. Recent simulation efforts focus on high resolution models that address aspect, slope, soil types, and microclimate variations that affect local and migrating plants, their associated pollinators and insect herbivores, modifying habitat availability for birds and mammals

Energetic contribution potential of building-integrated photovoltaics on airports in warm climates

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

Ruether, Ricardo; LABSOLAR - Laboratorio de Energia Solar, UFSC - Universidade Federal de Santa Catarina, Caixa Postal 476, Florianopolis, SC 88040-900; Braun, Priscila

2009-10-15

Especially in warm climates, a considerable fraction of the electricity demand in commercial buildings is due to the intensive use of air-conditioning systems. Airport buildings in sunny and warm regions present a perfect match between energy demand and solar resource availability. Airport buildings are also typically large and horizontal, isolated and free of shading, and have a great potential for the integration of solar photovoltaic (PV) systems. In this work, we assess the potential impact in energy demand reduction at the Florianopolis International Airport in Brazil (27 S, 48 W) with the use of building-integrated photovoltaic (BIPV) systems. We analysemore » the building's hourly energy consumption and solar irradiation data, to assess the match between energy demand and potential generation, and we estimate the PV power necessary to supply both the total amount and fractions of the annual energy demand. Our results show that the integration of PV systems on airport buildings in warm climates can supply the entire electric power consumption of an airport complex, in line with the general concept of a zero-energy building (ZEB). (author)« less

Participatory data collection and monitoring of agricultural pest dynamics for climate-resilient coffee production using Tiko'n, a generic tool to develop agroecological food web models

NASA Astrophysics Data System (ADS)

Rojas, M.; Malard, J. J.; Adamowski, J. F.; Tuy, H.

2016-12-01

Climate variability impacts agricultural processes through many mechanisms. For example, the proliferation of pests and diseases increases with warmer climate and alternated wind patterns, as longer growing seasons allow pest species to complete more reproductive cycles and changes in the weather patterns alter the stages and rates of development of pests and pathogens. Several studies suggest that enhancing plant diversity and complexity in farming systems, such as in agroforestry systems, reduces the vulnerability of farms to extreme climatic events. On the other hand, other authors have argued that vegetation diversity does not necessarily reduce the incidence of pests and diseases, highlighting the importance of understanding how, where and when it is recommendable to diversify vegetation to improve pest and disease control, and emphasising the need for tools to develop, monitor and evaluate agroecosystems. In order to understand how biodiversity can enhance ecosystem services provided by the agroecosystem in the context of climatic variability, it is important to develop comprehensive models that include the role of trophic chains in the regulation of pests, which can be achieved by integrating crop models with pest-predator models, also known as agroecosystem network (AEN) models. Here we present a methodology for the participatory data collection and monitoring necessary for running Tiko'n, an AEN model that can also be coupled to a crop model such as DSSAT. This methodology aims to combine the local and practical knowledge of farmers with the scientific knowledge of entomologists and agronomists, allowing for the simplification of complex ecological networks of plant and insect interactions. This also increases the acceptability, credibility, and comprehension of the model by farmers, allowing them to understand their relationship with the local agroecosystem and their potential to use key agroecosystem principles such as functional diversity to mitigate climate variability impacts. Preliminary results of a study currently being conducted in a coffee agroforestry system in El Quebracho, Guatemala, will be presented, where the data was directly collected by farmers during eight consecutive months. Finally, future recommendations from lessons learnt during this study will be discussed.

Sustainability as Moral Action

ERIC Educational Resources Information Center

Dunn, Merrily S.; Hart-Steffes, Jeanne S.

2012-01-01

When one considers sustainability as a moral action, there are equally complex realities at hand--climate change, resource depletion, water and land rights. One author describes this broad sense of sustainability as "the connection of specific social and environmental problems to the functioning of human and ecological systems" (Jenkins, 2011).…

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

NASA Astrophysics Data System (ADS)

Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

2015-04-01

Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems. 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

The added value of dynamical downscaling in a climate change scenario simulation:A case study for European Alps and East Asia

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Coppola, Erika; Giorgi, Filippo

2010-05-01

Since anthropogenic climate change is a rather important factor for the future human life all over the planet and its effects are not globally uniform, climate information at regional or local scales become more and more important for an accurate assessment of the potential impact of climate change on societies and ecosystems. High resolution information with suitably fine-scale for resolving complex geographical features could be a critical factor for successful linkage between climate models and impact assessment studies. However, scale mismatch between them still remains major problem. One method for overcoming the resolution limitations of global climate models and for adding regional details to coarse-grid global projections is to use dynamical downscaling by means of a regional climate model. In this study, the ECHAM5/MPI-OM (1.875 degree) A1B scenario simulation has been dynamically downscaled by using two different approaches within the framework of RegCM3 modeling system. First, a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS) is applied over the European Alpine region. The Sub-BATS system is composed of 15 km coarse-grid cell and 3 km sub-grid cell. Second, we developed the RegCM3 one-way double-nested system, with the mother domain encompassing the eastern regions of Asia at 60 km grid spacing and the nested domain covering the Korean Peninsula at 20 km grid spacing. By comparing the regional climate model output and the driving global model ECHAM5/MPI-OM output, it is possible to estimate the added value of physically-based dynamical downscaling when for example impact studies at hydrological scale are performed.

Ice sheet climate modeling: past achievements, ongoing challenges, and future endeavors

NASA Astrophysics Data System (ADS)

Lenaerts, J.

2017-12-01

Fluctuations in surface mass balance (SMB) mask out a substantial portion of contemporary Greenland and Antarctic ice sheet mass loss. That implies that we need accurate, consistent, and long-term SMB time series to isolate the mass loss signal. This in turn requires understanding of the processes driving SMB, and how they interplay. The primary controls on present-day ice sheet SMB are snowfall, which is regulated by large-scale atmospheric variability, and surface meltwater production at the ice sheet's edges, which is a complex result of atmosphere-surface interactions. Additionally, wind-driven snow redistribution and sublimation are large SMB contributors on the downslope areas of the ice sheets. Climate models provide an integrated framework to simulate all these individual ice sheet components. Recent developments in RACMO2, a regional climate model bound by atmospheric reanalyses, have focused on enhancing horizontal resolution, including blowing snow, snow albedo, and meltwater processes. Including these physics not only enhanced our understanding of the ice sheet climate system, but also enabled to obtain increasingly accurate estimates of ice sheet SMB. However, regional models are not suitable to capture the mutual interactions between ice sheet and the remainder of the global climate system in transient climates. To take that next step, global climate models are essential. In this talk, I will highlight our present work on improving ice sheet climate in the Community Earth System Model (CESM). In particular, we focus on an improved representation of polar firn, ice sheet clouds, and precipitation. For this exercise, we extensively use field observations, remote sensing data, as well as RACMO2. Next, I will highlight how CESM is used to enhance our understanding of ice sheet SMB, its drivers, and past and present changes.

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.

2016 International Land Model Benchmarking (ILAMB) Workshop Report

NASA Technical Reports Server (NTRS)

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen; Lawrence, David M.; Riley, William J.; Randerson, James T.; Ahlstrom, Anders; Abramowitz, Gabriel; Baldocchi, Dennis D.; Best, Martin J.;

Climate governance as a complex adaptive system. Reply to comments on "Climate change governance, cooperation and self-organization"

NASA Astrophysics Data System (ADS)

Pacheco, Jorge M.; Vasconcelos, Vítor V.; Santos, Francisco C.

2014-12-01

Mark Buchanan recently wrote that "Physics is not only about Physics anymore" [1]. We believe that the subject of our review provides a clear manifestation of this statement, and testifies for the possibility of using methods developed in the realm of theoretical physics to address problems that lie far beyond what conventional Physics thinking would conceive. It is thus rewarding (and we feel very honored) to have our manuscript commented by renowned scientists from a variety of fields.

Uncertainties in Integrated Climate Change Impact Assessments by Sub-setting GCMs Based on Annual as well as Crop Growing Period under Rice Based Farming System of Indo-Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Pillai, S. N.; Singh, H.; Panwar, A. S.; Meena, M. S.; Singh, S. V.; Singh, B.; Paudel, G. P.; Baigorria, G. A.; Ruane, A. C.; McDermid, S.; Boote, K. J.; Porter, C.; Valdivia, R. O.

2016-12-01

Integrated assessment of climate change impact on agricultural productivity is a challenge to the scientific community due to uncertainties of input data, particularly the climate, soil, crop calibration and socio-economic dataset. However, the uncertainty due to selection of GCMs is the major source due to complex underlying processes involved in initial as well as the boundary conditions dealt in solving the air-sea interactions. Under Agricultural Modeling Intercomparison and Improvement Project (AgMIP), the Indo-Gangetic Plains Regional Research Team investigated the uncertainties caused due to selection of GCMs through sub-setting based on annual as well as crop-growth period of rice-wheat systems in AgMIP Integrated Assessment methodology. The AgMIP Phase II protocols were used to study the linking of climate-crop-economic models for two study sites Meerut and Karnal to analyse the sensitivity of current production systems to climate change. Climate Change Projections were made using 29 CMIP5 GCMs under RCP4.5 and RCP 8.5 during mid-century period (2040-2069). Two crop models (APSIM & DSSAT) were used. TOA-MD economic model was used for integrated assessment. Based on RAPs (Representative Agricultural Pathways), some of the parameters, which are not possible to get through modeling, derived from literature and interactions with stakeholders incorporated into the TOA-MD model for integrated assessment.

Climate change impacts on human exposures to air pollution ...

EPA Pesticide Factsheets

This is an abstract for a presentations at the Annual Conference of the International Society on Exposure Science and Environmental Epidemiology. This presentation will serve as an introduction to the symposium. As we consider the potential health impacts of a warming planet, the relationships between climate change and air pollutants become increasingly important to understand. These relationships are complex and highly variable, causing a variety of environmental impacts at local, regional and global scales. Human exposures and health impacts for air pollutants have the potential to be altered by changes in climate through multiple factors that drive population exposures to these pollutants. Research on this topic will provide both state and local governments with the tools and scientific knowledge base to undertake any necessary adaptation of the air pollution regulations and/or public health management systems in the face of climate change.

Climate in Context - How partnerships evolve in regions

NASA Astrophysics Data System (ADS)

Parris, A. S.

2014-12-01

In 2015, NOAA's RISA program will celebrate its 20th year of exploration in the development of usable climate information. In the mid-1990s, a vision emerged to develop interdisciplinary research efforts at the regional scale for several important reasons. Recognizable climate patterns, such as the El Nino Southern Oscillation (ENSO), emerge at the regional level where our understanding of observations and models coalesce. Critical resources for society are managed in a context of regional systems, such as water supply and human populations. Multiple scales of governance (local, state, and federal) with complex institutional relationships can be examined across a region. Climate information (i.e. data, science, research etc) developed within these contexts has greater potential for use. All of this work rests on a foundation of iterative engagement between scientists and decision makers. Throughout these interactions, RISAs have navigated diverse politics, extreme events and disasters, socio-economic and ecological disruptions, and advances in both science and technology. Our understanding of information needs is evolving into a richer understanding of complex institutional, legal, political, and cultural contexts within which people can use science to make informed decisions. The outcome of RISA work includes both cases where climate information was used in decisions and cases where capacity for using climate information and making climate resilient decisions has increased over time. In addition to balancing supply and demand of scientific information, RISAs are engaged in a social process of reconciling climate information use with important drivers of society. Because partnerships are critical for sustained engagement, and because engagement is critically important to the use of science, the rapid development of new capacity in regionally-based science programs focused on providing climate decision support is both needed and challenging. New actors can bolster existing partnerships, but also impact trust developed through engagement. Examining other partnership-driven science initiatives, such as Digital Coast or NIDIS, can help identify critical elements of governance and network management that could be applied to the regional climate programs.

Simulating nitrogen budgets in complex farming systems using INCA: calibration and scenario analyses for the Kervidy catchment (W. France)

NASA Astrophysics Data System (ADS)

Durand, P.

The integrated nitrogen model INCA (Integrated Nitrogen in Catchments) was used to analyse the nitrogen dynamics in a small rural catchment in Western France. The agrosystem studied is very complex, with: extensive use of different organic fertilisers, a variety of crop rotations, a structural excess of nitrogen (i.e. more animal N produced by the intensive farming than the N requirements of the crops and pastures), and nitrate retention in both hydrological stores and riparian zones. The original model features were adapted here to describe this complexity. The calibration results are satisfactory, although the daily variations in stream nitrate are not simulated in detail. Different climate scenarios, based on observed climate records, were tested; all produced a worsening of the pollution in the short term. Scenarios of alternative agricultural practices (reduced fertilisation and catch crops) were also analysed, suggesting that a reduction by 40% of the fertilisation combined with the introduction of catch crops would be necessary to stop the degradation of water quality.

Let the Games Begin: New Opportunities to Address Climate Change Communication, Education, and Decision Support

NASA Astrophysics Data System (ADS)

Rooney-varga, J. N.; Sterman, J.; Jones, A.; Johnston, E.; Rath, K.; Nease, J.

2014-12-01

A rapid transition to a low-carbon, climate-resilient society is not only possible, but could also bring many co-benefits for public health, economic wellbeing, social equity, and more. The science supporting an urgent need for such a transition has never been clearer. Yet, social science data are also clear: the public in the US (and many other similar developed economies) does not, on average, share this sense of urgency, nor have policymakers shown a willingness to put scientific evidence above the perceptions of their constituents. The gulf between scientific and public understanding of climate change has spurred research on climate change communication, learning, and decision-making, identifying barriers such as misconceptions and faulty mental models of the climate and energy systems; poor understanding of complex, dynamic systems generally; and affective and social barriers to learning and action. There is also a growing opportunity to address these barriers, through tools that rely on active learning, that are social, engaging (and even fun), and that are grounded in rigorous science. An increasing number of decision-support computer simulations are being developed, intended to make complex technical problems accessible to non-experts in an interactive format. At the same time, the use of scenario planning, role-playing games, and active learning approaches are gaining ground in policy and education spheres. Simulation-based role-playing games bring these approaches together and can provide powerful learning experiences: they offer the potential to compress time and reality; create experiences without requiring the 'real thing;' explore the consequences of our decisions that often unfold over decades; and open affective and social learning pathways. Here, we offer a perspective on the potential of these tools in climate change education, communication, and decision-support, and a brief demonstration of one tool we have developed, World Energy.

Structural complexity and land-surface energy exchange along a gradient from arctic tundra to boreal forest

USGS Publications Warehouse

Thompson, C.; Beringer, J.; Chapin, F. S.; McGuire, A.D.

2004-01-01

Question: Current climate changes in the Alaskan Arctic, which are characterized by increases in temperature and length of growing season, could alter vegetation structure, especially through increases in shrub cover or the movement of treeline. These changes in vegetation structure have consequences for the climate system. What is the relationship between structural complexity and partitioning of surface energy along a gradient from tundra through shrub tundra to closed canopy forest? Location: Arctic tundra-boreal forest transition in the Alaskan Arctic. Methods: Along this gradient of increasing canopy complexity, we measured key vegetation characteristics, including community composition, biomass, cover, height, leaf area index and stem area index. We relate these vegetation characteristics to albedo and the partitioning of net radiation into ground, latent, and sensible heating fluxes. Results: Canopy complexity increased along the sequence from tundra to forest due to the addition of new plant functional types. This led to non-linear changes in biomass, cover, and height in the understory. The increased canopy complexity resulted in reduced ground heat fluxes, relatively conserved latent heat fluxes and increased sensible heat fluxes. The localized warming associated with increased sensible heating over more complex canopies may amplify regional warming, causing further vegetation change in the Alaskan Arctic.

A conceptual framework for addressing complexity and unfolding transition dynamics when developing sustainable adaptation strategies in urban water management.

PubMed

Fratini, C F; Elle, M; Jensen, M B; Mikkelsen, P S

2012-01-01

To achieve a successful and sustainable adaptation to climate change we need to transform the way we think about change. Much water management research has focused on technical innovation with a range of new solutions developed to achieve a 'more sustainable and integrated urban water management cycle'. But Danish municipalities and utility companies are struggling to bring such solutions into practice. 'Green infrastructure', for example, requires the consideration of a larger range of aspects related to the urban context than the traditional urban water system optimization. There is the need for standardized methods and guidelines to organize transdisciplinary processes where different types of knowledge and perspectives are taken into account. On the basis of the macro-meso-micro pattern inspired by complexity science and transition theory, we developed a conceptual framework to organize processes addressing the complexity characterizing urban water management in the context of climate change. In this paper the framework is used to organize a research process aiming at understanding and unfolding urban dynamics for sustainable transition. The final goal is to enable local authorities and utilities to create the basis for managing and catalysing the technical and organizational innovation necessary for a sustainable transition towards climate change adaptation in urban areas.

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.

Public Perception of Uncertainties Within Climate Change Science.

PubMed

Visschers, Vivianne H M

2018-01-01

Climate change is a complex, multifaceted problem involving various interacting systems and actors. Therefore, the intensities, locations, and timeframes of the consequences of climate change are hard to predict and cause uncertainties. Relatively little is known about how the public perceives this scientific uncertainty and how this relates to their concern about climate change. In this article, an online survey among 306 Swiss people is reported that investigated whether people differentiate between different types of uncertainty in climate change research. Also examined was the way in which the perception of uncertainty is related to people's concern about climate change, their trust in science, their knowledge about climate change, and their political attitude. The results of a principal component analysis showed that respondents differentiated between perceived ambiguity in climate research, measurement uncertainty, and uncertainty about the future impact of climate change. Using structural equation modeling, it was found that only perceived ambiguity was directly related to concern about climate change, whereas measurement uncertainty and future uncertainty were not. Trust in climate science was strongly associated with each type of uncertainty perception and was indirectly associated with concern about climate change. Also, more knowledge about climate change was related to less strong perceptions of each type of climate science uncertainty. Hence, it is suggested that to increase public concern about climate change, it may be especially important to consider the perceived ambiguity about climate research. Efforts that foster trust in climate science also appear highly worthwhile. © 2017 Society for Risk Analysis.

Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

USGS Publications Warehouse

Amy K. Snover,; Nathan J. Mantua,; Littell, Jeremy; Michael A. Alexander,; Michelle M. McClure,; Janet Nye,

2013-01-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.

Advancing Climate Literacy through Investment in Science Education Faculty, and Future and Current Science Teachers: Providing Professional Learning, Instructional Materials, and a Model for Locally-Relevant and Culturally-Responsive Content

NASA Astrophysics Data System (ADS)

Halversen, C.; Apple, J. K.; McDonnell, J. D.; Weiss, E.

2014-12-01

The Next Generation Science Standards (NGSS) call for 5th grade students to "obtain and combine information about ways individual communities use science ideas to protect Earth's resources and environment". Achieving this, and other objectives in NGSS, will require changes in the educational system for both students and teachers. Teachers need access to high quality instructional materials and continuous professional learning opportunities starting in pre-service education. Students need highly engaging and authentic learning experiences focused on content that is strategically interwoven with science practices. Pre-service and early career teachers, even at the secondary level, often have relatively weak understandings of the complex Earth systems science required for understanding climate change and hold alternative ideas and naïve beliefs about the nature of science. These naïve understandings cause difficulties in portraying and teaching science, especially considering what is being called for in NGSS. The ACLIPSE program focuses on middle school pre-service science teachers and education faculty because: (1) the concepts that underlie climate change align well with the disciplinary core ideas and practices in NGSS for middle grades; and (2) middle school is a critical time for capturing students interest in science as student engagement by eighth grade is the most effective predictor of student pursuit of science in high school and college. Capturing student attention at this age is critical for recruitment to STEM careers and lifelong climate literacy. THE ACLIPSE program uses cutting edge research and technology in ocean observing systems to provide educators with new tools to engage students that will lead to deeper understanding of the interactions between the ocean and climate systems. Establishing authentic, meaningful connections between indigenous and place-based, and technological climate observations will help generate a more holistic perspective on climate change and demonstrate that observing systems can enhance understanding. ACLIPSE materials strive to translate research about climate change effectively into understandable narratives of real world phenomena using ocean data, creating meaningful pathways into ocean-climate science for students in ALL communities.

Modeling Costal Zone Responses to Sea-Level Rise Using MoCCS: A Model of Complex Coastal System

NASA Astrophysics Data System (ADS)

Dai, H.; Niedoroda, A. W.; Ye, M.; Saha, B.; Donoghue, J. F.; Kish, S.

2011-12-01

Large-scale coastal systems consisting of several morphological components (e.g. beach, surf zone, dune, inlet, shoreface, and estuary) can be expected to exhibit complex and interacting responses to changes in the rate of sea level rise and storm climate. We have developed a numerical model of complex coastal systems (MoCCS), derived from earlier morphdynamic models, to represent the large-scale time-averaged physical processes that shape each component and govern the component interactions. These control the ongoing evolution of the barrier islands, beach and dune erosion, shoal formation and sand withdrawal at tidal inlets, depth changes in the bay, and changes in storm flooding. The model has been used to study the response of an idealized coastal system with physical characteristics and storm climatology similar to Santa Rosa Island on the Florida Panhandle coast. Five SLR scenarios have been used, covering the range of recently published projections for the next century. Each scenario has been input with a constant and then a time-varying storm climate. The results indicate that substantial increases in the rate of beach erosion are largely due to increased sand transfer to inlet shoals with increased rates of sea level rise. The barrier island undergoes cycles of dune destruction and regrowth, leading to sand deposition. This largely maintains island freeboard but is progressively less effective in offsetting bayside inundation and marsh habitat loss at accelerated sea level rise rates.

Potential climate change impacts on water availability and cooling water demand in the Lusatian Lignite Mining Region, Central Europe

NASA Astrophysics Data System (ADS)

Pohle, Ina; Koch, Hagen; Gädeke, Anne; Grünewald, Uwe; Kaltofen, Michael; Redetzky, Michael

2014-05-01

In the catchments of the rivers Schwarze Elster, Spree and Lusatian Neisse, hydrologic and socioeconomic systems are coupled via a complex water management system in which water users, reservoirs and water transfers are included. Lignite mining and electricity production are major water users in the region: To allow for open pit lignite mining, ground water is depleted and released into the river system while cooling water is used in the thermal power plants. In order to assess potential climate change impacts on water availability in the catchments as well as on the water demand of the thermal power plants, a climate change impact assessment was performed using the hydrological model SWIM and the long term water management model WBalMo. The potential impacts of climate change were considered by using three regional climate change scenarios of the statistical regional climate model STAR assuming a further temperature increase of 0, 2 or 3 K by the year 2050 in the region respectively. Furthermore, scenarios assuming decreasing mining activities in terms of a decreasing groundwater depression cone, lower mining water discharges, and reduced cooling water demand of the thermal power plants are considered. In the standard version of the WBalMo model cooling water demand is considered as static with regard to climate variables. However, changes in the future cooling water demand over time according to the plans of the local mining and power plant operator are considered. In order to account for climate change impacts on the cooling water demand of the thermal power plants, a dynamical approach for calculating water demand was implemented in WBalMo. As this approach is based on air temperature and air humidity, the projected air temperature and air humidity of the climate scenarios at the locations of the power plants are included in the calculation. Due to increasing temperature and decreasing precipitation declining natural and managed discharges, and hence a lower water availability in the region, were simulated by SWIM and WBalMo respectively. Next to changing climate conditions, also the different mining scenarios have considerable impacts on natural and managed discharges. Using the dynamic approach for cooling water demand, the simulated water demands are lower in winter, but higher in summer compared to the static approach. As a consequence of changes in the seasonal pattern of the cooling water demand of the power plants, lower summer discharges downstream of the thermal power plants are simulated using the dynamical approach. Due to the complex water management system in the region included in the water management model WBalMo, also the simulation of reservoir releases and volumes is impacted by the choice of either the static or the dynamic approach for calculating the cooling water demand of the thermal power plants.

Exploring Use of Climate Information in Wildland Fire Management: A Decision Calendar Study

Treesearch

Thomas W. Corringham; Anthony L. Westerling; Barbara J. Morehouse

2006-01-01

Wildfire management is an institutionally complex process involving a complex budget and appropriations cycle, a variety of objectives, and a set of internal and external political constraints. Significant potential exists for enhancing the use of climate information and long-range climate forecasts in wildland fire management in the Western U.S. Written surveys and...

Impacts Of Global/Regional Climate Changes On Environment And Health: Need For Integrated Research And Education Collaboration (Invited)

NASA Astrophysics Data System (ADS)

Tuluri, F.

2013-12-01

The realization of long term changes in climate in research community has to go beyond the comfort zone through climate literacy in academics. Higher education on climate change is the platform to bring together the otherwise disconnected factors such as effective discovery, decision making, innovation, interdisciplinary collaboration, Climate change is a complex process that may be due to natural internal processes within the climate system, or to variations in natural or anthropogenic (human-driven) external forcing. Global climate change indicates a change in either the mean state of the climate or in its variability, persisting for several decades or longer. This includes changes in average weather conditions on Earth, such as a change in average global temperature, as well as changes in how frequently regions experience heat waves, droughts, floods, storms, and other extreme weather. It is important to examine the effects of climate variations on human health and disorders in order to take preventive measures. Similarly, the influence of climate changes on animal management practices, pests and pest management systems, and high value crops such as citrus and vegetables is also equally important for investigation. New genetic agricultural varieties must be explored, and pilot studies should examine biotechnology transfer. Recent climate model improvements have resulted in an enhanced ability to simulate many aspects of climate variability and extremes. However, they are still characterized by systematic errors and limitations in accurately simulating more precisely regional climate conditions. The present situations warrant developing climate literacy on the synergistic impacts of environmental change, and improve development, testing and validation of integrated stress impacts through computer modeling. In the present study we present a detailed study of the current status on the impacts of global/regional climate changes on environment and health with a view to highlighting the need for integrated research and education collaboration at national and global level.

Monitoring Thermal Performance of Hollow Bricks with Different Cavity Fillers in Difference Climate Conditions

NASA Astrophysics Data System (ADS)

Pavlík, Zbyšek; Jerman, Miloš; Fořt, Jan; Černý, Robert

2015-03-01

Hollow brick blocks have found widespread use in the building industry during the last decades. The increasing requirements to the thermal insulation properties of building envelopes given by the national standards in Europe led the brick producers to reduce the production of common solid bricks. Brick blocks with more or less complex systems of internal cavities replaced the traditional bricks and became dominant on the building ceramics market. However, contrary to the solid bricks where the thermal conductivity can easily be measured by standard methods, the complex geometry of hollow brick blocks makes the application of common techniques impossible. In this paper, a steady-state technique utilizing a system of two climatic chambers separated by a connecting tunnel for sample positioning is used for the determination of the thermal conductivity, thermal resistance, and thermal transmittance ( U value) of hollow bricks with the cavities filled by air, two different types of mineral wool, polystyrene balls, and foam polyurethane. The particular brick block is provided with the necessary temperature- and heat-flux sensors and thermally insulated in the tunnel. In the climatic chambers, different temperatures are set. After steady-state conditions are established in the measuring system, the effective thermal properties of the brick block are calculated using the measured data. Experimental results show that the best results are achieved with hydrophilic mineral wool as a cavity filler; the worst performance exhibits the brick block with air-filled cavities.

Transforming Professional Learning and Practice in Assessment for Learning

ERIC Educational Resources Information Center

Poskitt, Jenny

2014-01-01

Assessing student learning is a complex process requiring teachers to have deep knowledge of the curriculum, assessment, and pedagogy. Changing political climates mean that teachers are expected to respond to new approaches or systems and adjust their classroom practice accordingly. Teachers often engage in professional learning (PL) to assist…

A Review of Recent Changes in Southern Ocean Sea Ice, Their Drivers and Forcings

NASA Technical Reports Server (NTRS)

Hobbs, William R.; Massom, Rob; Stammerjohn, Sharon; Reid, Phillip; Williams, Guy; Meier, Walter

2016-01-01

Over the past 37years, satellite records show an increase in Antarctic sea ice cover that is most pronounced in the period of sea ice growth. This trend is dominated by increased sea ice coverage in the western Ross Sea, and is mitigated by a strong decrease in the Bellingshausen and Amundsen seas. The trends in sea ice areal coverage are accompanied by related trends in yearly duration. These changes have implications for ecosystems, as well as global and regional climate. In this review, we summarize the researchto date on observing these trends, identifying their drivers, and assessing the role of anthropogenic climate change. Whilst the atmosphere is thought to be the primary driver, the ocean is also essential in explaining the seasonality of the trend patterns. Detecting an anthropogenic signal in Antarctic sea ice is particularly challenging for a number of reasons: the expected response is small compared to the very high natural variability of the system; the observational record is relatively short; and the ability of global coupled climate models to faithfully represent the complex Antarctic climate system is in doubt.

Using Content-Aligned Assessments to Identify Weaknesses in Students' Understanding of Fundamental Weather and Climate Ideas

NASA Astrophysics Data System (ADS)

Wertheim, J.; Willard, S.

2011-12-01

There is growing interest in ensuring that citizens understand weather and climate sufficiently to make informed decisions, and these topics are gaining increased attention in K-12 education. The National Research Council recently released A Framework for K-12 Science Education with the expectation that U.S. 12th graders must have a sophisticated knowledge of climate change, including the role of deep time, variability, and computer modeling in the prediction of climate impacts on the planet and human activity. This requirement demands that students extend their understanding of climate change to the past and future, but it is important to recognize that many students know little about prerequisite ideas, such as daily and annual weather and climate processes, and this problem must be addressed prior to introducing the complexities of the climate system. In order to diagnose weaknesses in students' foundational understanding of the complex climate system, we primarily assessed a middle school (MS)-level understanding of the core elements of the system, in addition to a high school (HS)-level understanding of seasons. We described grade appropriate, coherent, functioning conceptual models for each targeted idea, and decomposed them into explicit learning goals. We then applied Project 2061's rigorous item development procedure to produce 235 high-quality, misconception-based multiple choice test items. These items were tested with a national sample of approximately 20,000 students, grades 6-12, in two phases (Spring 2010 & 2011). Here we report results from the second phase, including items targeting knowledge about convection, daily and annual air temperature patterns, factors that influence air temperature, and seasons. Overall, HS students outperformed MS students on these items by an average of only 3% (MS:31% correct; HS:34% correct). These data show a few strong misconceptions (e.g., 47% of students think that the North Pole is always angled toward the Sun). But a much more prevalent issue is that most students lack schematic knowledge for any concept tested, as demonstrated by results indicative of random guessing on items that require cognitive demands beyond declarative knowledge. For example, 83% of students know that the maximum height of the sun in the sky above a given place can change during July, but only 32% know both that it changes continuously through the month and could correctly identify if it gets higher or lower. These basic elements of an accurate mental model are needed to explain annual temperature patterns. If students do not have an accurate understanding of processes controlling key elements of the climate system, it is unsurprising that they struggle to comprehend how these elements interact within the system itself. The results of this study underscore the need to 1) ensure that fundamentals are given the necessary attention, even as our expectations for students become increasingly sophisticated; 2) define grade appropriate, coherent, functioning conceptual models for each climate idea and for each grade level; and 3) develop instructional materials that build schematic knowledge.

Development and application of earth system models

PubMed Central

Prinn, Ronald G.

2013-01-01

The global environment is a complex and dynamic system. Earth system modeling is needed to help understand changes in interacting subsystems, elucidate the influence of human activities, and explore possible future changes. Integrated assessment of environment and human development is arguably the most difficult and most important “systems” problem faced. To illustrate this approach, we present results from the integrated global system model (IGSM), which consists of coupled submodels addressing economic development, atmospheric chemistry, climate dynamics, and ecosystem processes. An uncertainty analysis implies that without mitigation policies, the global average surface temperature may rise between 3.5 °C and 7.4 °C from 1981–2000 to 2091–2100 (90% confidence limits). Polar temperatures, absent policy, are projected to rise from about 6.4 °C to 14 °C (90% confidence limits). Similar analysis of four increasingly stringent climate mitigation policy cases involving stabilization of greenhouse gases at various levels indicates that the greatest effect of these policies is to lower the probability of extreme changes. The IGSM is also used to elucidate potential unintended environmental consequences of renewable energy at large scales. There are significant reasons for attention to climate adaptation in addition to climate mitigation that earth system models can help inform. These models can also be applied to evaluate whether “climate engineering” is a viable option or a dangerous diversion. We must prepare young people to address this issue: The problem of preserving a habitable planet will engage present and future generations. Scientists must improve communication if research is to inform the public and policy makers better. PMID:22706645

Two hot to handle: How do we manage the simultaneous impacts of climate change and natural disasters on human health?

NASA Astrophysics Data System (ADS)

Phalkey, R. K.; Louis, V. R.

2016-05-01

Climate change is one of the major challenges we face today. There is recognition alongside evidence that the health impacts of both climate change and natural disasters are significant and rising. The impacts of both are also complex and span well beyond health to include environmental, social, demographic, cultural, and economic aspects of human lives. Nonetheless integrated impact assessments are rare and so are system level approaches or systematic preparedness and adaptation strategies to brace the two simultaneously particularly in low and middle-income countries. Ironically the impacts of both climate change as well as natural disasters will be disproportionately borne by low emitters. Sufficiently large and long-term data from comprehensive weather, socio-economic, demographic and health observational systems are currently unavailable to guide adaptation strategies with the necessary precision. In the absence of these and given the uncertainties around the health impact projections alongside the geographic disparities even within the countries, the main question is how can countries then prepare to brace the unknown? We certainly cannot wait to obtain answers to all the questions before we plan solutions. Strengthening health systems is therefore a pragmatic "zero regrets" strategy and should be adopted hastily before the parallel impacts from climate change and associated extreme weather events (disasters thereof) become too hot to handle.

Detecting hydrological changes through conceptual model

NASA Astrophysics Data System (ADS)

Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

2015-04-01

Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.

Hydrological Responses of Andean Lakes and Tropical Floodplains to Climate Variability and Human Intervention: an Integrative Modelling Framework

NASA Astrophysics Data System (ADS)

Hoyos, I. C.; González Morales, C.; Serna López, J. P.; Duque, C. L.; Canon Barriga, J. E.; Dominguez, F.

2013-12-01

Andean water bodies in tropical regions are significantly influenced by fluctuations associated with climatic and anthropogenic drivers, which implies long term changes in mountain snow peaks, land covers and ecosystems, among others. Our work aims at providing an integrative framework to realistically assess the possible future of natural water bodies with different degrees of human intervention. We are studying in particular the evolution of three water bodies in Colombia: two Andean lakes and a floodplain wetland. These natural reservoirs represent the accumulated effect of hydrological processes in their respective basins, which exhibit different patterns of climate variability and distinct human intervention and environmental histories. Modelling the hydrological responses of these local water bodies to climate variability and human intervention require an understanding of the strong linkage between geophysical and social factors. From the geophysical perspective, the challenge is how to downscale global climate projections in the local context: complex orography and relative lack of data. To overcome this challenge we combine the correlational and physically based analysis of several sources of spatially distributed biophysical and meteorological information to accurately determine aspects such as moisture sources and sinks and past, present and future local precipitation and temperature regimes. From the social perspective, the challenge is how to adequately represent and incorporate into the models the likely response of social agents whose water-related interests are diverse and usually conflictive. To deal with the complexity of these systems we develop interaction matrices, which are useful tools to holistically discuss and represent each environment as a complex system. Our goal is to assess partially the uncertainties of the hydrological balances in these intervened water bodies we establish climate/social scenarios, using hybrid models that combine the computational power of numerical simulations (of both physical and social components) with interactive responses given by users who define strategies and make decisions in real time, providing valuable information about people's attitudes and choices regarding future climate perspectives. Part of our interest with this project is to effectively transfer the knowledge and scientific information gathered to the communities in a way that is useful and propositive. To this end we developed a website (http://peerlagoscolombia.udea.edu.co) that includes relevant information about the project outcomes. We also developed and installed telemetric hydrologic stations in each site, whose data on water storage levels and basic meteorological variables can be accessed online. Acknowledgement: this project is funded by the USAID-NSF PEER program (First cycle, project 31).

An approach to designing a national climate service

PubMed Central

Miles, E. L.; Snover, A. K.; Whitely Binder, L. C.; Sarachik, E. S.; Mote, P. W.; Mantua, N.

2006-01-01

Climate variability and change are considerably important for a wide range of human activities and natural ecosystems. Climate science has made major advances during the last two decades, yet climate information is neither routinely useful for nor used in planning. What is needed is a mechanism, a national climate service (NCS), to connect climate science to decision-relevant questions and support building capacity to anticipate, plan for, and adapt to climate fluctuations. This article contributes to the national debate for an NCS by describing the rationale for building an NCS, the functions and services it would provide, and how it should be designed and evaluated. The NCS is most effectively achieved as a federal interagency partnership with critically important participation by regional climate centers, state climatologists, the emerging National Integrated Drought Information System, and the National Oceanic and Atmospheric Administration (NOAA) Regional Integrated Sciences Assessment (RISA) teams in a sustained relationship with a wide variety of stakeholders. Because the NCS is a service, and because evidence indicates that the regional spatial scale is most important for delivering climate services, given subnational geographical/geophysical complexity, attention is focused on lessons learned from the University of Washington Climate Impacts Group's 10 years of experience, the first of the NOAA RISA teams. PMID:17158218

An approach to designing a national climate service.

PubMed

Miles, E L; Snover, A K; Whitely Binder, L C; Sarachik, E S; Mote, P W; Mantua, N

2006-12-26

Climate variability and change are considerably important for a wide range of human activities and natural ecosystems. Climate science has made major advances during the last two decades, yet climate information is neither routinely useful for nor used in planning. What is needed is a mechanism, a national climate service (NCS), to connect climate science to decision-relevant questions and support building capacity to anticipate, plan for, and adapt to climate fluctuations. This article contributes to the national debate for an NCS by describing the rationale for building an NCS, the functions and services it would provide, and how it should be designed and evaluated. The NCS is most effectively achieved as a federal interagency partnership with critically important participation by regional climate centers, state climatologists, the emerging National Integrated Drought Information System, and the National Oceanic and Atmospheric Administration (NOAA) Regional Integrated Sciences Assessment (RISA) teams in a sustained relationship with a wide variety of stakeholders. Because the NCS is a service, and because evidence indicates that the regional spatial scale is most important for delivering climate services, given subnational geographical/geophysical complexity, attention is focused on lessons learned from the University of Washington Climate Impacts Group's 10 years of experience, the first of the NOAA RISA teams.

Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

NASA Astrophysics Data System (ADS)

Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

2017-12-01

Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.

PubMed

Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu

2017-06-01

To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.

Hydrological Climate Classification: Can We Improve on Köppen-Geiger?

NASA Astrophysics Data System (ADS)

Knoben, W.; Woods, R. A.; Freer, J. E.

2017-12-01

Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which can explain streamflow differences between geographically close locations. Summarizing, this work shows that hydrology needs its own way to structure climate forcing, acknowledging that climates vary gradually on a global scale and explicitly including those climate aspects that drive seasonal changes in hydrologic regimes.

Hydro-meteorological risk reduction and climate change adaptation in the Sava River Basin

NASA Astrophysics Data System (ADS)

Brilly, Mitja; Šraj, Mojca; Kryžanowski, Andrej

2017-04-01

The Sava River Basin covered the teritory of several countries. There were, in past thirty years, several flood hazard events with almost hundred years return period. Parts of the basin suffer by severe droughts also. In the presentation we covered questions of: • Flood hazard in complex hydrology structure • Landslide and flush flood in mountainous regions • Floods on karst polje • Flood risk management in the complex international and hydrological condition. • Impact of man made structures: hydropower storages, inundation ponds, river regulation, alternate streams, levees system, pumping stations, Natura 2000 areas etc. • How to manage droughts in the international river basin The basin is well covered by information and managed by international the SRB Commission (http://savacommission.org/) that could help. We develop study for climate change impact on floods on entire river basin financing by UNECE. There is also study provide climate change impact on the water management provide by World Bank and on which we take part. Recently is out call by world bank for study »Flood risk management plan for the SRB«.

Quantifying the economic risks of climate change

NASA Astrophysics Data System (ADS)

Diaz, Delavane; Moore, Frances

2017-11-01

Understanding the value of reducing greenhouse-gas emissions matters for policy decisions and climate risk management, but quantification is challenging because of the complex interactions and uncertainties in the Earth and human systems, as well as normative ethical considerations. Current modelling approaches use damage functions to parameterize a simplified relationship between climate variables, such as temperature change, and economic losses. Here we review and synthesize the limitations of these damage functions and describe how incorporating impacts, adaptation and vulnerability research advances and empirical findings could substantially improve damage modelling and the robustness of social cost of carbon values produced. We discuss the opportunities and challenges associated with integrating these research advances into cost-benefit integrated assessment models, with guidance for future work.

Polar Research with Unmanned Aircraft and Tethered Balloons

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

Ivey, M; Petty, R; Desilets, D

2014-01-24

The Arctic is experiencing rapid climate change, with nearly double the rate of surface warming observed elsewhere on the planet. While various positive feedback mechanisms have been suggested, the reasons for Arctic amplification are not well understood, nor are the impacts to the global carbon cycle well quantified. Additionally, there are uncertainties associated with the complex interactions between Earth’s surface and the atmosphere. Elucidating the causes and consequences of Arctic warming is one of the many goals of the Climate and Environmental Sciences Division (CESD) of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program, and ismore » part of the larger CESD initiative to develop a robust predictive understanding of Earth’s climate system.« less

The structure of parasite communities in fish hosts: ecology meets geography and climate.

PubMed

Poulin, R

2007-09-01

Parasite communities in fish hosts are not uniform in space: their diversity, composition and abundance vary across the geographical range of a host species. Increasingly urgently, we need to understand the geographic component of parasite communities to better predict how they will respond to global climate change. Patterns of geographical variation in the abundance of parasite populations, and in the diversity and composition of parasite communities, are explored here, and the ways in which they may be affected by climate change are discussed. The time has come to transform fish parasite ecology from a mostly descriptive discipline into a predictive science, capable of integrating complex ecological data to generate forecasts about the future state of host-parasite systems.

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.

Rapid climatic signal propagation from source to sink in a southern California sediment-routing system

USGS Publications Warehouse

Covault, J.A.; Romans, B.W.; Fildani, A.; McGann, M.; Graham, S.A.

2010-01-01

Terrestrial source areas are linked to deep-sea basins by sediment-routing systems, which only recently have been studied with a holistic approach focused on terrestrial and submarine components and their interactions. Here we compare an extensive piston-core and radiocarbon-age data set from offshore southern California to contemporaneous Holocene climate proxies in order to test the hypothesis that climatic signals are rapidly propagated from source to sink in a spatially restricted sediment-routing system that includes the Santa Ana River drainage basin and the Newport deep-sea depositional system. Sediment cores demonstrate that variability in rates of Holocene deep-sea turbidite deposition is related to complex ocean-atmosphere interactions, including enhanced magnitude and frequency of the North American monsoon and El Ni??o-Southern Oscillation cycles, which increased precipitation and fluvial discharge in southern California. This relationship is evident because, unlike many sediment-routing systems, the Newport submarine canyon-and-channel system was consistently linked tothe Santa Ana River,which maintained sediment delivery even during Holocene marine transgression and highstand. Results of this study demonstrate the efficiency of sediment transport and delivery through a spatially restricted, consistently linked routing system and the potential utility of deep-sea turbidite depositional trends as paleoclimate proxies in such settings. ?? 2010 by The University of Chicago.

Integration of modern statistical tools for the analysis of climate extremes into the web-GIS “CLIMATE”

NASA Astrophysics Data System (ADS)

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

2017-11-01

The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called “CLIMATE” to include a dedicated statistical package developed in the R language. The web-GIS “CLIMATE” is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS “CLIMATE” can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.

Science, Practitioners and Faith Communities: using TEK and Faith Knowledge to address climate issues.

NASA Astrophysics Data System (ADS)

Peterson, K.

2017-12-01

Worldview, Lifeway and Science - Communities that are tied to the land or water for their livelihood, and for whom subsistence guides their cultural lifeway, have knowledges that inform their interactions with the environment. These frameworks, sometimes called Traditional Ecological Knowledges (TEK), are based on generations of observations made and shared within lived life-environmental systems, and are tied to practitioners' broader worldviews. Subsistence communities, including Native American tribes, are well aware of the crises caused by climate change impacts. These communities are working on ways to integrate knowledge from their ancient ways with current observations and methods from Western science to implement appropriate adaptation and resilience measures. In the delta region of south Louisiana, the communities hold worldviews that blend TEK, climate science and faith-derived concepts. It is not incongruent for the communities to intertwine conversations from complex and diverse sources, including the academy, to inform their adaptation measures and their imagined solutions. Drawing on over twenty years of work with local communities, science organizations and faith institutions of the lower bayou region of Louisiana, the presenter will address the complexity of traditional communities' work with diverse sources of knowledge to guide local decision-making and to assist outside partners to more effectively address challenges associated with climate change.

Characterizing bias correction uncertainty in wheat yield predictions

NASA Astrophysics Data System (ADS)

Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam

2017-04-01

Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.

Global Food Security in a Changing Climate: Considerations and Projections

NASA Astrophysics Data System (ADS)

Walsh, M. K.; Brown, M. E.; Backlund, P. W.; Antle, J. M.; Carr, E. R.; Easterling, W. E.; Funk, C. C.; Murray, A.; Ngugi, M.; Barrett, C. B.; Ingram, J. S. I.; Dancheck, V.; O'Neill, B. C.; Tebaldi, C.; Mata, T.; Ojima, D. S.; Grace, K.; Jiang, H.; Bellemare, M.; Attavanich, W.; Ammann, C. M.; Maletta, H.

2015-12-01

Global food security is an elusive challenge and important policy focus from the community to the globe. Food is provisioned through food systems that may be simple or labyrinthine, yet each has vulnerabilities to climate change through its effects on food production, transportation, storage, and other integral food system activities. At the same time, the future of food systems is sensitive to socioeconomic trajectories determined by choices made outside of the food system, itself. Constrictions for any reason can lead to decreased food availability, access, utilization, or stability - that is, to diminished food security. Possible changes in trade and other U.S. relationships to the rest of the world under changing conditions to the end of the century are considered through integrated assessment modelling under a range of emissions scenarios. Climate change is likely to diminish continued progress on global food security through production disruptions leading to local availability limitations and price increases, interrupted transport conduits, and diminished food safety, among other causes. In the near term, some high-latitude production export regions may benefit from changes in climate. The types and price of food imports is likely to change, as are export demands, affecting U.S. consumers and producers. Demands placed on foreign assistance programs may increase, as may demand for advanced technologies. Adaptation across the food system has great potential to manage climate change effects on food security, and the complexity of the food system offers multiple potential points of intervention for decision makers at every level. However, effective adaptation is subject to highly localized conditions and socioeconomic factors, and the technical feasibility of an adaptive intervention is not necessarily a guarantee of its application if it is unaffordable or does not provide benefits within a relatively short time frame.

Making sense in a complex landscape: how the Cynefin Framework from Complex Adaptive Systems Theory can inform health promotion practice.

PubMed

Van Beurden, Eric K; Kia, Annie M; Zask, Avigdor; Dietrich, Uta; Rose, Lauren

2013-03-01

Health promotion addresses issues from the simple (with well-known cause/effect links) to the highly complex (webs and loops of cause/effect with unpredictable, emergent properties). Yet there is no conceptual framework within its theory base to help identify approaches appropriate to the level of complexity. The default approach favours reductionism--the assumption that reducing a system to its parts will inform whole system behaviour. Such an approach can yield useful knowledge, yet is inadequate where issues have multiple interacting causes, such as social determinants of health. To address complex issues, there is a need for a conceptual framework that helps choose action that is appropriate to context. This paper presents the Cynefin Framework, informed by complexity science--the study of Complex Adaptive Systems (CAS). It introduces key CAS concepts and reviews the emergence and implications of 'complex' approaches within health promotion. It explains the framework and its use with examples from contemporary practice, and sets it within the context of related bodies of health promotion theory. The Cynefin Framework, especially when used as a sense-making tool, can help practitioners understand the complexity of issues, identify appropriate strategies and avoid the pitfalls of applying reductionist approaches to complex situations. The urgency to address critical issues such as climate change and the social determinants of health calls for us to engage with complexity science. The Cynefin Framework helps practitioners make the shift, and enables those already engaged in complex approaches to communicate the value and meaning of their work in a system that privileges reductionist approaches.

Conservation and adaptation to climate change.

PubMed

Brooke, Cassandra

2008-12-01

The need to adapt to climate change has become increasingly apparent, and many believe the practice of biodiversity conservation will need to alter to face this challenge. Conservation organizations are eager to determine how they should adapt their practices to climate change. This involves asking the fundamental question of what adaptation to climate change means. Most studies on climate change and conservation, if they consider adaptation at all, assume it is equivalent to the ability of species to adapt naturally to climate change as stated in Article 2 of the United Nations Framework Convention on Climate Change. Adaptation, however, can refer to an array of activities that range from natural adaptation, at one end of the spectrum, to sustainability science in coupled human and natural systems at the other. Most conservation organizations deal with complex systems in which adaptation to climate change involves making decisions on priorities for biodiversity conservation in the face of dynamic risks and involving the public in these decisions. Discursive methods such as analytic deliberation are useful for integrating scientific knowledge with public perceptions and values, particularly when large uncertainties and risks are involved. The use of scenarios in conservation planning is a useful way to build shared understanding at the science-policy interface. Similarly, boundary organizations-organizations or institutions that bridge different scales or mediate the relationship between science and policy-could prove useful for managing the transdisciplinary nature of adaptation to climate change, providing communication and brokerage services and helping to build adaptive capacity. The fact that some nongovernmental organizations (NGOs) are active across the areas of science, policy, and practice makes them well placed to fulfill this role in integrated assessments of biodiversity conservation and adaptation to climate change.

Challenges and priorities for modelling livestock health and pathogens in the context of climate change.

PubMed

Özkan, Şeyda; Vitali, Andrea; Lacetera, Nicola; Amon, Barbara; Bannink, André; Bartley, Dave J; Blanco-Penedo, Isabel; de Haas, Yvette; Dufrasne, Isabelle; Elliott, John; Eory, Vera; Fox, Naomi J; Garnsworthy, Phil C; Gengler, Nicolas; Hammami, Hedi; Kyriazakis, Ilias; Leclère, David; Lessire, Françoise; Macleod, Michael; Robinson, Timothy P; Ruete, Alejandro; Sandars, Daniel L; Shrestha, Shailesh; Stott, Alistair W; Twardy, Stanislaw; Vanrobays, Marie-Laure; Ahmadi, Bouda Vosough; Weindl, Isabelle; Wheelhouse, Nick; Williams, Adrian G; Williams, Hefin W; Wilson, Anthony J; Østergaard, Søren; Kipling, Richard P

2016-11-01

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire based exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. Copyright © 2016 Elsevier Inc. All rights reserved.

Enabling Automated Graph-based Search for the Identification and Characterization of Mesoscale Convective Complexes in Satellite Datasets through Integration with the Apache Open Climate Workbench

NASA Astrophysics Data System (ADS)

McGibbney, L. J.; Whitehall, K. D.; Mattmann, C. A.; Goodale, C. E.; Joyce, M.; Ramirez, P.; Zimdars, P.

2014-12-01

We detail how Apache Open Climate Workbench (OCW) (recently open sourced by NASA JPL) was adapted to facilitate an ongoing study of Mesoscale Convective Complexes (MCCs) in West Africa and their contributions within the weather-climate continuum as it relates to climate variability. More than 400 MCCs occur annually over various locations on the globe. In West Africa, approximately one-fifth of that total occur during the summer months (June-November) alone and are estimated to contribute more than 50% of the seasonal rainfall amounts. Furthermore, in general the non-discriminatory socio-economic geospatial distribution of these features correlates with currently and projected densely populated locations. As such, the convective nature of MCCs raises questions regarding their seasonal variability and frequency in current and future climates, amongst others. However, in spite of the formal observation criteria of these features in 1980, these questions have remained comprehensively unanswered because of the untimely and subjective methods for identifying and characterizing MCCs due to limitations data-handling limitations. The main outcome of this work therefore documents how a graph-based search algorithm was implemented on top of the OCW stack with the ultimate goal of improving fully automated end-to-end identification and characterization of MCCs in high resolution observational datasets. Apache OCW as an open source project was demonstrated from inception and we display how it was again utilized to advance understanding and knowledge within the above domain. The project was born out of refactored code donated by NASA JPL from the Earth science community's Regional Climate Model Evaluation System (RCMES), a joint project between the Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), and a scientific collaboration between the University of California at Los Angeles (UCLA) and NASA JPL. The Apache OCW project was then integrated back into the donor code with the aim of more efficiently powering that project. Notwithstanding, the object-oriented approach to creating a core set of libraries Apache OCW has scaled the usability of the project beyond climate model evaluation as displayed in the MCC use case detailed herewith.

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Huh, Oscar K.; Walker, Nan

2004-01-01

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

Assessing Current State Science Teaching and Learning Standards for Ability to Achieve Climate Science Literacy

NASA Astrophysics Data System (ADS)

Busch, K. C.

2012-12-01

Even though there exists a high degree of consensus among scientists about climate change, doubt has actually increased over the last five years within the general U.S. public. In 2006, 79% of those polled agreed that there is evidence for global warming, while only 59% agreed in 2010 (Pew Research Center, 2010). The source for this doubt can be partially attributed to lack of knowledge. Formal education is one mechanism that potentially can address inadequate public understanding as school is the primary place where students - and future citizens - learn about the climate. In a joint effort, several governmental agencies, non-governmental organizations, scientists and educators have created a framework called The Essential Principles of Climate Science Literacy, detailing seven concepts that are deemed vital for individuals and communities to understand Earth's climate system (USGCRP, 2009). Can students reach climate literacy - as defined by these 7 concepts - if they are taught using a curriculum based on the current state standards? To answer this question, the K-12 state science teaching and learning standards for Texas and California - two states that heavily influence nation-wide textbook creation - were compared against the Essential Principles. The data analysis consisted of two stages, looking for: 1) direct reference to "climate" and "climate change" and 2) indirect reference to the 7 Essential Principles through axial coding. The word "climate" appears in the California K-12 science standards 4 times and in the Texas standards 7 times. The word "climate change" appears in the California and Texas standards only 3 times each. Indirect references to the 7 Essential Principles of climate science literacy were more numerous. Broadly, California covered 6 of the principles while Texas covered all 7. In looking at the 7 principles, the second one "Climate is regulated by complex interactions among component of the Earth system" was the most substantively addressed. Least covered were number 6 "Human activities are impacting the climate system" and number 7 "Climate change will have consequences for the Earth system and human lives." Most references, either direct or indirect, occurred in the high school standards for earth science, a class not required for graduation in either state. This research points to the gaps between what the 7 Essential Principles of Climate Literacy defines as essential knowledge and what students may learn in their K-12 science classes. Thus, the formal system does not seem to offer an experience which can potentially develop a more knowledgeable citizenry who will be able to make wise personal and policy decisions about climate change, falling short of the ultimate goal of achieving widespread climate literacy. Especially troubling was the sparse attention to the principles addressing the human connection to the climate - principles number 6 and 7. If climate literate citizens are to make "wise personal and policy decisions" (USGCRP, 2009), these two principles especially are vital. This research, therefore, has been valuable for identifying current shortcomings in state standards.

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes.

PubMed

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2017-11-01

Currently, the temperate forest biome cools the earth's climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (-10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems.

Similarities and Differences in Barriers and Opportunities Affecting Climate Change Adaptation Action in Four North American Landscapes

NASA Astrophysics Data System (ADS)

Lonsdale, Whitney R.; Kretser, Heidi E.; Chetkiewicz, Cheryl-Lesley B.; Cross, Molly S.

2017-12-01

Climate change presents a complex set of challenges for natural resource managers across North America. Despite recognition that climate change poses serious threats to species, ecosystems, and human communities, implementation of adaptation measures is not yet happening on a broad scale. Among different regions, a range of climate change trajectories, varying political contexts, and diverse social and ecological systems generate a myriad of factors that can affect progress on climate change adaptation implementation. In order to understand the general versus site-specific nature of barriers and opportunities influencing implementation, we surveyed and interviewed practitioners, decision-makers, and scientists involved in natural resource management in four different North American regions, northern Ontario (Canada), the Adirondack State Park (US), Arctic Alaska (US), and the Transboundary Rocky Mountains (US and Canada). Common barriers among regions related to a lack of political support and financial resources, as well as challenges related to translating complex and interacting effects of climate change into management actions. Opportunities shared among regions related to collaboration, funding, and the presence of strong leadership. These commonalities indicate the importance of cross-site learning about ways to leverage opportunities and address adaptation barriers; however, regional variations also suggest that adaptation efforts will need to be tailored to fit specific ecological, political, social and economic contexts. Comparative findings on the similarities and differences in barriers and opportunities, as well as rankings of barriers and opportunities by region, offers important contextual insights into how to further refine efforts to advance adaptation actions in those regions.

Similarities and Differences in Barriers and Opportunities Affecting Climate Change Adaptation Action in Four North American Landscapes.

PubMed

Lonsdale, Whitney R; Kretser, Heidi E; Chetkiewicz, Cheryl-Lesley B; Cross, Molly S

2017-12-01

Climate change presents a complex set of challenges for natural resource managers across North America. Despite recognition that climate change poses serious threats to species, ecosystems, and human communities, implementation of adaptation measures is not yet happening on a broad scale. Among different regions, a range of climate change trajectories, varying political contexts, and diverse social and ecological systems generate a myriad of factors that can affect progress on climate change adaptation implementation. In order to understand the general versus site-specific nature of barriers and opportunities influencing implementation, we surveyed and interviewed practitioners, decision-makers, and scientists involved in natural resource management in four different North American regions, northern Ontario (Canada), the Adirondack State Park (US), Arctic Alaska (US), and the Transboundary Rocky Mountains (US and Canada). Common barriers among regions related to a lack of political support and financial resources, as well as challenges related to translating complex and interacting effects of climate change into management actions. Opportunities shared among regions related to collaboration, funding, and the presence of strong leadership. These commonalities indicate the importance of cross-site learning about ways to leverage opportunities and address adaptation barriers; however, regional variations also suggest that adaptation efforts will need to be tailored to fit specific ecological, political, social and economic contexts. Comparative findings on the similarities and differences in barriers and opportunities, as well as rankings of barriers and opportunities by region, offers important contextual insights into how to further refine efforts to advance adaptation actions in those regions.

The Communication Strategy of NASA's Earth Observatory

NASA Astrophysics Data System (ADS)

Simmon, R.; Ward, K.; Riebeek, H.; Allen, J.; Przyborski, P.; Scott, M.; Carlowicz, M. J.

2010-12-01

Climate change is a complex, multi-disciplinary subject. Accurately conveying this complexity to general audiences, while still communicating the basic facts, is challenging. Our approach is to combine climate change information with a wide range of Earth system science topics, illustrated by satellite imagery and data visualizations. NASA's Earth Observatory web site (earthobservatory.nasa.gov) uses the broad range of NASA's remote sensing technologies, data, and research to communicate climate change science. We serve two primary audiences: the "attentive public" --people interested in and willing to seek out information about science, technology, and the environment--and media. We cover the breadth of Earth science, with information about climate change integrated with stories about weather, geology, oceanography, and solar flares. Current event-driven imagery is used as a hook to draw readers. We then supply links to supplemental information, either about current research or the scientific basics. We use analogies, carefully explain jargon or acronyms, and build narratives which both attract readers and make information easier to remember. These narratives are accompanied by primers on topics like energy balance or the water cycle. Text is carefully integrated with illustrations and state-of-the-art data visualizations. Other site features include a growing list of climate questions and answers, addressing common misconceptions about global warming and climate change. Maps of global environmental parameters like temperature, rainfall, and vegetation show seasonal change and long-term trends. Blogs from researchers in the field provide a look at the day-to-day process of science. For the media, public domain imagery is supplied at full resolution and links are provided to primary sources.

Successfully Integrating Climate Change Education into School System Curriculum

NASA Astrophysics Data System (ADS)

Scallion, M.

2017-12-01

Maryland's Eastern Shore is threatened by climate change driven sea level rise. By working with school systems, rather than just with individual teachers, educators can gain access to an entire grade level of students, assuring that all students, regardless of socioeconomic background or prior coursework have an opportunity to explore the climate issue and be part of crafting community level solutions for their communities. We will address the benefits of working with school system partners to achieve a successful integration of in-school and outdoor learning by making teachers and administrators part of the process. We will explore how, through the Maryland and Delaware Climate Change Education, Assessment, and Research Project, teachers, content supervisors and informal educators worked together to create a climate curriculum with local context that effectively meets Common Core and Next Generation Science Standards. Over the course of several weeks during the year, students engage in a series of in-class and field activities directly correlated with their science curriculum. Wetlands and birds are used as examples of the local wildlife and habitat being impacted by climate change. Through these lessons led by Pickering Creek Audubon Center educators and strengthened by material covered by classroom teachers, students get a thorough introduction to the mechanism of climate change, local impacts of climate change on habitats and wildlife, and actions they can take as a community to mitigate the effects of climate change. The project concludes with a habitat and carbon stewardship project that gives students and teachers a sense of hope as they tackle this big issue on a local scale. We'll explore how the MADE-CLEAR Informal Climate Change Education (ICCE) Community of Practice supports Delaware and Maryland environmental educators in collaboratively learning and expanding their programming on the complex issue of climate change. Participants will learn how to include climate change education as part of a larger ecological exploration, giving students and teachers local context to this global issue and memorable outdoor hands-on experiences and student driven adaptation projects.

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 lesser known challenge of climate change: thermal variance and sex-reversal in vertebrates with temperature-dependent sex determination.

PubMed

Neuwald, Jennifer L; Valenzuela, Nicole

2011-03-23

Climate change is expected to disrupt biological systems. Particularly susceptible are species with temperature-dependent sex determination (TSD), as in many reptiles. While the potentially devastating effect of rising mean temperatures on sex ratios in TSD species is appreciated, the consequences of increased thermal variance predicted to accompany climate change remain obscure. Surprisingly, no study has tested if the effect of thermal variance around high-temperatures (which are particularly relevant given climate change predictions) has the same or opposite effects as around lower temperatures. Here we show that sex ratios of the painted turtle (Chrysemys picta) were reversed as fluctuations increased around low and high unisexual mean-temperatures. Unexpectedly, the developmental and sexual responses around female-producing temperatures were decoupled in a more complex manner than around male-producing values. Our novel observations are not fully explained by existing ecological models of development and sex determination, and provide strong evidence that thermal fluctuations are critical for shaping the biological outcomes of climate change.

Climate change impact modelling needs to include cross-sectoral interactions

NASA Astrophysics Data System (ADS)

Harrison, Paula A.; Dunford, Robert W.; Holman, Ian P.; Rounsevell, Mark D. A.

2016-09-01

Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single-sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single-sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single-sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation, which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale.

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.

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

Willner, Sven N.; Hartin, Corinne; Gieseke, Robert

Here, pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary productionmore » and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system. The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2.« less

Controls of multi-modal wave conditions in a complex coastal setting

USGS Publications Warehouse

Hegermiller, Christie; Rueda, Ana C.; Erikson, Li H.; Barnard, Patrick L.; Antolinez, J.A.A.; Mendez, Fernando J.

2017-01-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Controls of Multimodal Wave Conditions in a Complex Coastal Setting

NASA Astrophysics Data System (ADS)

Hegermiller, C. A.; Rueda, A.; Erikson, L. H.; Barnard, P. L.; Antolinez, J. A. A.; Mendez, F. J.

2017-12-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Integrating Climate Change Adaptation into Public Health Practice: Using Adaptive Management to Increase Adaptive Capacity and Build Resilience

PubMed Central

McDowell, Julia Z.; Luber, George

2011-01-01

Background: Climate change is expected to have a range of health impacts, some of which are already apparent. Public health adaptation is imperative, but there has been little discussion of how to increase adaptive capacity and resilience in public health systems. Objectives: We explored possible explanations for the lack of work on adaptive capacity, outline climate–health challenges that may lie outside public health’s coping range, and consider changes in practice that could increase public health’s adaptive capacity. Methods: We conducted a substantive, interdisciplinary literature review focused on climate change adaptation in public health, social learning, and management of socioeconomic systems exhibiting dynamic complexity. Discussion: There are two competing views of how public health should engage climate change adaptation. Perspectives differ on whether climate change will primarily amplify existing hazards, requiring enhancement of existing public health functions, or present categorically distinct threats requiring innovative management strategies. In some contexts, distinctly climate-sensitive health threats may overwhelm public health’s adaptive capacity. Addressing these threats will require increased emphasis on institutional learning, innovative management strategies, and new and improved tools. Adaptive management, an iterative framework that embraces uncertainty, uses modeling, and integrates learning, may be a useful approach. We illustrate its application to extreme heat in an urban setting. Conclusions: Increasing public health capacity will be necessary for certain climate–health threats. Focusing efforts to increase adaptive capacity in specific areas, promoting institutional learning, embracing adaptive management, and developing tools to facilitate these processes are important priorities and can improve the resilience of local public health systems to climate change. PMID:21997387

Uncertainties in Future Regional Sea Level Trends: How to Deal with the Internal Climate Variability?

NASA Astrophysics Data System (ADS)

Becker, M.; Karpytchev, M.; Hu, A.; Deser, C.; Lennartz-Sassinek, S.

2017-12-01

Today, the Climate models (CM) are the main tools for forecasting sea level rise (SLR) at global and regional scales. The CM forecasts are accompanied by inherent uncertainties. Understanding and reducing these uncertainties is becoming a matter of increasing urgency in order to provide robust estimates of SLR impact on coastal societies, which need sustainable choices of climate adaptation strategy. These CM uncertainties are linked to structural model formulation, initial conditions, emission scenario and internal variability. The internal variability is due to complex non-linear interactions within the Earth Climate System and can induce diverse quasi-periodic oscillatory modes and long-term persistences. To quantify the effects of internal variability, most studies used multi-model ensembles or sea level projections from a single model ran with perturbed initial conditions. However, large ensembles are not generally available, or too small, and computationally expensive. In this study, we use a power-law scaling of sea level fluctuations, as observed in many other geophysical signals and natural systems, which can be used to characterize the internal climate variability. From this specific statistical framework, we (1) use the pre-industrial control run of the National Center for Atmospheric Research Community Climate System Model (NCAR-CCSM) to test the robustness of the power-law scaling hypothesis; (2) employ the power-law statistics as a tool for assessing the spread of regional sea level projections due to the internal climate variability for the 21st century NCAR-CCSM; (3) compare the uncertainties in predicted sea level changes obtained from a NCAR-CCSM multi-member ensemble simulations with estimates derived for power-law processes, and (4) explore the sensitivity of spatial patterns of the internal variability and its effects on regional sea level projections.

Potential impacts of climate change on the ecology of dengue and its mosquito vector the Asian tiger mosquito (Aedes albopictus)

NASA Astrophysics Data System (ADS)

Erickson, R. A.; Hayhoe, K.; Presley, S. M.; Allen, L. J. S.; Long, K. R.; Cox, S. B.

2012-09-01

Shifts in temperature and precipitation patterns caused by global climate change may have profound impacts on the ecology of certain infectious diseases. We examine the potential impacts of climate change on the transmission and maintenance dynamics of dengue, a resurging mosquito-vectored infectious disease. In particular, we project changes in dengue season length for three cities: Atlanta, GA; Chicago, IL and Lubbock, TX. These cities are located on the edges of the range of the Asian tiger mosquito within the United States of America and were chosen as test cases. We use a disease model that explicitly incorporates mosquito population dynamics and high-resolution climate projections. Based on projected changes under the Special Report on Emissions Scenarios (SRES) A1fi (higher) and B1 (lower) emission scenarios as simulated by four global climate models, we found that the projected warming shortened mosquito lifespan, which in turn decreased the potential dengue season. These results illustrate the difficulty in predicting how climate change may alter complex systems.

The development and application of landscape evolution models to coupled coast-estuarine environments

NASA Astrophysics Data System (ADS)

Morris, Chloe; Coulthard, Tom; Parsons, Daniel R.; Manson, Susan; Barkwith, Andrew

2017-04-01

Landscape Evolution Models (LEMs) are proven to be useful tools in understanding the morphodynamics of coast and estuarine systems. However, perhaps owing to the lack of research in this area, current models are not capable of simulating the dynamic interactions between these systems and their co-evolution at the meso-scale. Through a novel coupling of numerical models, this research is designed to explore coupled coastal-estuarine interactions, controls on system behaviour and the influence that environmental change could have. This will contribute to the understanding of the morphodynamics of these systems and how they may behave and evolve over the next century in response to climate changes, with the aim of informing management practices. This goal is being achieved through the modification and coupling of the one-line Coastline Evolution Model (CEM) with the hydrodynamic LEM CAESAR-Lisflood (C-L). The major issues faced with coupling these programs are their differing complexities and the limited graphical visualisations produced by the CEM that hinder the dissemination of results. The work towards overcoming these issues and reported here, include a new version of the CEM that incorporates a range of more complex geomorphological processes and boasts a graphical user interface that guides users through model set-up and projects a live output during model runs. The improved version is a stand-alone tool that can be used for further research projects and for teaching purposes. A sensitivity analysis using the Morris method has been completed to identify which key variables, including wave climate, erosion and weathering values, dominate the control of model behaviour. The model is being applied and tested using the evolution of the Holderness Coast, Humber Estuary and Spurn Point on the east coast of England (UK), which possess diverse geomorphologies and complex, co-evolving sediment pathways. Simulations using the modified CEM are currently being completed to ascertain the processes influential to the morphodynamics and evolution of these systems; presently this includes increasing sea levels and changing wave climate patterns. Outputs and findings from these runs will be presented and discussed, with the aid of the improved graphical visualisations and animations that illustrate the evolution of simulated environments.

Air Pollution and Climate Change Effects on Allergies in the Anthropocene: Abundance, Interaction, and Modification of Allergens and Adjuvants.

PubMed

Reinmuth-Selzle, Kathrin; Kampf, Christopher J; Lucas, Kurt; Lang-Yona, Naama; Fröhlich-Nowoisky, Janine; Shiraiwa, Manabu; Lakey, Pascale S J; Lai, Senchao; Liu, Fobang; Kunert, Anna T; Ziegler, Kira; Shen, Fangxia; Sgarbanti, Rossella; Weber, Bettina; Bellinghausen, Iris; Saloga, Joachim; Weller, Michael G; Duschl, Albert; Schuppan, Detlef; Pöschl, Ulrich

2017-04-18

Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions.

Air Pollution and Climate Change Effects on Allergies in the Anthropocene: Abundance, Interaction, and Modification of Allergens and Adjuvants

PubMed Central

2017-01-01

Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions. PMID:28326768

Combining Statistics and Physics to Improve Climate Downscaling

NASA Astrophysics Data System (ADS)

Gutmann, E. D.; Eidhammer, T.; Arnold, J.; Nowak, K.; Clark, M. P.

2017-12-01

Getting useful information from climate models is an ongoing problem that has plagued climate science and hydrologic prediction for decades. While it is possible to develop statistical corrections for climate models that mimic current climate almost perfectly, this does not necessarily guarantee that future changes are portrayed correctly. In contrast, convection permitting regional climate models (RCMs) have begun to provide an excellent representation of the regional climate system purely from first principles, providing greater confidence in their change signal. However, the computational cost of such RCMs prohibits the generation of ensembles of simulations or long time periods, thus limiting their applicability for hydrologic applications. Here we discuss a new approach combining statistical corrections with physical relationships for a modest computational cost. We have developed the Intermediate Complexity Atmospheric Research model (ICAR) to provide a climate and weather downscaling option that is based primarily on physics for a fraction of the computational requirements of a traditional regional climate model. ICAR also enables the incorporation of statistical adjustments directly within the model. We demonstrate that applying even simple corrections to precipitation while the model is running can improve the simulation of land atmosphere feedbacks in ICAR. For example, by incorporating statistical corrections earlier in the modeling chain, we permit the model physics to better represent the effect of mountain snowpack on air temperature changes.

Nevada Infrastructure for Climate Change Science, Education, and Outreach

NASA Astrophysics Data System (ADS)

Dana, G. L.; Lancaster, N.; Mensing, S. A.; Piechota, T.

2008-12-01

The Great Basin is characterized by complex basin and range topography, arid to semiarid climate, and a history of sensitivity to climate change. Mountain areas comprise about 10% of the landscape, yet are the areas of highest precipitation and generate 85% of groundwater recharge and most surface runoff. These characteristics provide an ideal natural laboratory to study the effects of climate change. The Nevada system of Higher Education, including the University of Nevada, Las Vegas, the University of Nevada, Reno, the Desert Research Institute, and Nevada State College have begun a five year research and infrastructure building program, funded by the National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) with the vision "to create a statewide interdisciplinary program and virtual climate change center that will stimulate transformative research, education, and outreach on the effects of regional climate change on ecosystem resources (especially water) and support use of this knowledge by policy makers and stakeholders." Six major strategies are proposed to develop infrastructure needs and attain our vision: 1) Develop a capability to model climate change at a regional and sub-regional scale(Climate Modeling Component) 2) Analyze effects on ecosystems and disturbance regimes (Ecological Change Component) 3) Quantify and model changes in water balance and resources under climate change (Water Resources Component) 4) Assess effects on human systems and enhance policy making and outreach to communities and stakeholders (Policy, Decision-Making, and Outreach Component) 5) Develop a data portal and software to support interdisciplinary research via integration of data from observational networks and modeling (Cyberinfrastructure Component) and 6) Train teachers and students at all levels and provide public outreach in climate change issues (Education Component). Two new climate observational transects will be established across Great Basin Ranges, one anticipated on a mountain range in southern Nevada and the second to be located in north-central Nevada. Climatic, hydrologic and ecological data from these transects will be downloaded into high capacity data storage units and made available to researchers through creation of the Nevada climate change portal. Our research will aim to answer two interdisciplinary science questions key to understanding the effects of future climate change on Great Basin mountain ecosystems and the potential management strategies for responding to these changes: 1) How will climate change affect water resources and linked ecosystem resources and human systems? And 2) How will climate change affect disturbance regimes (e.g., wildland fires, invasive species, insect outbreaks, droughts) and linked systems? Infrastructure developed through this project will provide new interdisciplinary capability to detect, analyze, and model effects of regional climate change in mountainous regions of the west and provide a major contribution to existing climate change research and monitoring networks.

Q-BIC3 - A Québec-Bavarian international collaboration for adapting regional watershed management to climate change

NASA Astrophysics Data System (ADS)

Ludwig, Ralf

2010-05-01

Adapting to the impacts of climate change is certainly one of the major challenges in water resources management over the next decades. Adaptation to climate change risks is most crucial in this domain, since projected increase in mean air temperature in combination with an expected increase in the temporal variability of precipitation patterns will contribute to pressure on current water availability, allocation and management practices. The latter often involve the utilization of valuable infrastructure, such as dams, reservoirs and water intakes, for which adaptation options must by developed over long-term and often dynamic planning horizons. Research to establish novel methodologies for improved adaptation to climate change is thus very important and only beginning to emerge in regional watershed management. The presented project Q-BIC³, funded by the Bavarian Minstry for the Environment and the Québec Ministère du Développement économique, de l'Innovation et de l'Exportation, aims to develop and apply a newly designed spectrum of tools to support the improved assessment of adaptation options to climate change in regional watershed management. It addresses in particular selected study sites in Québec and Bavaria. The following key issues have been prioritized within Q-BIC³: i) The definition of potential adaptation options in the context of climate change for pre-targeted water management key issues using a subsequent and logical chain of modelling tools (climate, hydrological and water management modeling tools) ii) The definition of an approach that accounts for hydrological projection uncertainties in the search for potential adaptation options in the context of climate change iii) The investigation of the required complexity in hydrological models to estimate climate change impacts and to develop specific adaptation options for Québec and Bavaria watersheds. iv) The development and prototyping of a regionally transferable and modular modelling system for integrated watershed management under climate change conditions. The study sites under investigation, namely the Haut-Saint Francois and Gatineau watersheds in Québec and the Isar and Regnitz catchments in Bavaria, are under heavy anthropogenic use. Intense dam and reservoir operations and even water transfer systems are in place to satisfy multi-purpose demands on available water resources. These are imposing extreme modifications to the natural flow regimes. In the first phase of the project, climatic forcing, stemming from an ensemble of selected GCM and RCM runs, is applied to a variety of hydrological models with different complexity. The derived projections of future hydrological conditions serve to investigate, whether current operation rules and/or existing infrastructure needs to be adapted to a changing environment. First findings demonstrate the large uncertainties associated to the model chain outputs, but also indicate that related adaptation is indispensable to meet the challenges of the rapidly changing man-environment systems.

a Study of the Impact of Doubling Carbon Dioxide and Solar Radiation Variations on the Climate System.

NASA Astrophysics Data System (ADS)

Chu, Shaoping

The exchange of moisture and heat between the atmosphere and the Earth's surface fundamentally affect the dynamics and thermodynamics of the climate system. In order to trace moisture flow through the climate system and examine its impact on climate, a hydrologic cycle and a land energy balance have been developed and incorporated into a coupled climate-thermodynamic sea ice (CCSI) model. The expanded CCSI model has been tested by comparing computed climate parameters with available observations and GCM modeling results. In general, the expanded model does a good job in simulating the large scale features of the atmospheric circulation and precipitation in both space and time. The expanded model has been used to examine the possibility that increased levels of CO_2 in the atmosphere may induce the growth of Northern Hemisphere ice sheets. Results of the study indicate that if summer ice albedo is high enough, and there is some mechanism for initially maintaining ice through the summer season, then it may be possible to have ice sheet growth under the conditions CO_2 induced warming, mainly the result of decreased summer ice melt in response to the higher land ice albedo, and not an increase in precipitation. The expanded model has also been used to examine the impact of Milankovitch solar radiation variations on the climate system, to study the mechanisms that produce glacial-interglacial cycles, especially with respect to the initiation of ice sheets. The results show the Milankovitch solar radiation variations affect the climate system most in the polar regions with the mean annual surface air temperature varying directly in response to changes in the annually averaged incoming solar radiation. However, the seasonal variations in the surface air temperatures are much more complex with large magnitude variations for brief times during the year. The study indicates that ice sheets may start to grow under the conditions of low insolation that occurred at 25, 70, and 115 kyr BP and a land ice minimum albedo of 0.53, with the largest growth rate at 115 kyr BP, approximately when the current 100 kyr cycle began as observed in the geological record.

Study of method for reducing fuel consumption and amount of specific emissions of harmful substances with exhaust gases of passenger cars when using “climate control” system

NASA Astrophysics Data System (ADS)

Burakova, L. N.; Anisimov, I. A.; Burakova, A. D.; Burakova, O. D.

2018-05-01

The article deals with the issue of improving fuel efficiency and the ecological nature of passenger cars, servicing the administrative and management personnel of the oil and gas complex. It is established that fuel consumption and the amount of specific emissions of harmful substances with exhaust gases of cars when using the “climate control” system depend on the effective ambient temperature, the color of the opaque car body elements, the power of the car engine and the interior volume. However, the simplest controlled factor is the color of the opaque car body elements, which is characterized by the coefficient of light reflection. In the course of experimental studies, the authors established the dependences of a change in fuel consumption and a share of reducing emissions of harmful substances with exhaust gases of passenger cars with the “climate control” system on the coefficient of light reflection. A method has been developed to reduce fuel consumption and the amount of specific emissions of harmful substances with the exhaust gases of passenger cars using the “climate control” system, which involves painting the vehicle roof white and allows reducing fuel consumption by 5.5-10.3%, and the amount of specific emissions of harmful substances by 0.8-2.3%.

Future changes in coastal upwelling ecosystems with global warming: The case of the California Current System.

PubMed

Xiu, Peng; Chai, Fei; Curchitser, Enrique N; Castruccio, Frederic S

2018-02-12

Coastal upwelling ecosystems are among the most productive ecosystems in the world, meaning that their response to climate change is of critical importance. Our understanding of climate change impacts on marine ecosystems is largely limited to the open ocean, mainly because coastal upwelling is poorly reproduced by current earth system models. Here, a high-resolution model is used to examine the response of nutrients and plankton dynamics to future climate change in the California Current System (CCS). The results show increased upwelling intensity associated with stronger alongshore winds in the coastal region, and enhanced upper-ocean stratification in both the CCS and open ocean. Warming of the open ocean forces isotherms downwards, where they make contact with water masses with higher nutrient concentrations, thereby enhancing the nutrient flux to the deep source waters of the CCS. Increased winds and eddy activity further facilitate upward nutrient transport to the euphotic zone. However, the plankton community exhibits a complex and nonlinear response to increased nutrient input, as the food web dynamics tend to interact differently. This analysis highlights the difficulty in understanding how the marine ecosystem responds to a future warming climate, given to range of relevant processes operating at different scales.

Operationalising a social-ecological system perspective on the Arctic Ocean.

PubMed

Crépin, Anne-Sophie; Gren, Åsa; Engström, Gustav; Ospina, Daniel

2017-12-01

We propose a framework to support management that builds on a social-ecological system perspective on the Arctic Ocean. We illustrate the framework's application for two policy-relevant scenarios of climate-driven change, picturing a shift in zooplankton composition and alternatively a crab invasion. We analyse archetypical system dynamics between the socio-economic, the natural, and the governance systems in these scenarios. Our holistic approach can help managers identify looming problems arising from complex system interactions and prioritise among problems and solutions, even when available data are limited.

Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale

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

Zabaras, Nicolas J.

2016-11-08

Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario.

Changes in Migration Pattern of Transhumance due to Climate Change: An Empirical Analysis of Gaddi Community of Himachal Himalaya, India

NASA Astrophysics Data System (ADS)

Mishra, Himanshu; Wasini Pandey, Bindhy

2017-04-01

Transhumance is a complex and traditional livelihood system seeking to maintain equilibrium between pastures, livestock and local people in variable and inhospitable environments. In Western Himalayas in the Indian state of Himachal Pradesh, pastoral groups of Gaddis inhabit almost inaccessible areas, where scarce resources and extreme climatic conditions limit options for alternative land use and livelihood systems. In such a harsh and unforgiving environment, mobility in the form of transhumance has been the traditional ecological response to climatic extremes. However, recently, such additional factors as global as well as regional climate change have brought about changes in the tree line, snow line and pastoral grounds along the historical route of seasonal migration of the Gaddis. The growing unpredictability of the once static route of migration has raised the possibility of Gaddis shifting to alternative land use and land management techniques. In the present research, we explore how transhumant pastoralism has been sustained and stimulated in the context of socioeconomic and climate change in the mountainous region of Himachal Pradesh and the future challenges that it faces. Based on case study research conducted in Chamba district in Himachal Pradesh; we have analysed the status, opportunities, and constraints of transhumant pastoralism in the changing context and modeled the possible alternative land use decisions. Finally we conclude that unless there are affirmative and progressive policy and institutional framework to support transhumant system, the indigenous practice will soon disappear from this part of the world. Keywords: Climate change, Gaddis, Himachal Pradesh, Transhumance, Alternative Land Use

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields.

PubMed

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.

Dissemination of Climate Model Output to the Public and Commercial Sector

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

Robert Stockwell, PhD

2010-09-23

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature andmore » precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).« less

Potential limitations of NRC in predicting energetic requirements of beef females within western U.S. grazing systems

USDA-ARS?s Scientific Manuscript database

Assessment of beef cow energy balance and efficiency in grazing-extensive rangelands has occurred on a nominal basis over short time intervals and has not accounted for the complexity of metabolic and digestive responses; behavioral adaptations to climatic, terrain, and vegetation variables; and doc...

Mass failures and other processes of sediment production in Pacific northwest forest landscapes

Treesearch

Frederick J. Swanson; Lee E. Benda; Stanley H. Duncan; Gordon E. Grant; Walter F. Megahan; Leslie M. Reid; Robert R. Ziemer

1987-01-01

Abstract - Accelerated sediment production by mass failures and other erosion processes is an important link between management of forest resources and fish resources. Dominant processes and the rates of sediment production vary greatly throughout the Pacific Northwest in response to geologic and climatic factors. The complex sediment routing systems characteristic...

Curricular Innovation for Sustainability: The Piedmont/Ponderosa Model of Faculty Development

ERIC Educational Resources Information Center

Barlett, Peggy F.; Chase, Geoffrey W.

2012-01-01

Curricular innovation is at the center of the challenges many colleges and universities face as they seek to help students address more successfully than previous generations the complex, multi-faceted, systemic challenges of global climate change, population growth, loss of biodiversity, environmental justice, toxic wastes, and food insecurity.…

LCMS landscape change monitoring system—results from an information needs assessment

Treesearch

Kevin Megown; Brian Schwind; Don Evans; Mark Finco

2015-01-01

Understanding changes in land use and land cover over space and time provides an important means to evaluate complex interactions between human and biophysical systems, to project future conditions, and to design mitigation and adaptive management strategies. Assessing and monitoring landscape change is evolving into a foundational element of climate change adaptation...

Salmon and the Adaptive Capacity of Nimiipuu (Nez Perce) Culture to Cope with Change

ERIC Educational Resources Information Center

Colombi, Benedict J.

2012-01-01

Change due to natural disturbances and disasters, population growth and decline, economic crises, and environmental and climate change creates significant cultural challenges. Rapid change and the transformation it brings also involve complex relationships between sovereign tribes, resources, and the global system. This article explores how salmon…

Innoversity in knowledge-for-action and adaptation to climate change: the first steps of an 'evidence-based climatic health' transfrontier training program.

PubMed

Lapaige, Véronique; Essiembre, Hélène

2010-01-01

It has become increasingly clear to the international scientific community that climate change is real and has important consequences for human health. To meet these new challenges, the World Health Organization recommends reinforcing the adaptive capacity of health systems. One of the possible avenues in this respect is to promote awareness and knowledge translation in climatic health, at both the local and global scales. Within such perspective, two major themes have emerged in the field of public health research: 1) the development of advanced training adapted to 'global environment' change and to the specific needs of various groups of actors (doctors, nurses, public health practitioners, health care managers, public service managers, local communities, etc) and 2) the development of strategies for implementing research results and applying various types of evidence to the management of public health issues affected by climate change. Progress on these two fronts will depend on maximum innovation in transdisciplinary and transsectoral collaborations. The general purpose of this article is to present the program of a new research and learning chair designed for this double set of developmental objectives - a chair that emphasizes 'innoversity' (the dynamic relationship between innovation and diversity) and 'transfrontier ecolearning for adaptive actions'. The Écoapprentissages, santé mentale et climat collaborative research chair (University of Montreal and Quebec National Public Health Institute) based in Montreal is a center for 'transdisciplinary research' on the transfrontier knowledge-for-action that can aid adaptation of the public health sector, the public mental health sector, and the public service sector to climate change, as well as a center for complex collaborations on evidence-based climatic health 'training'. This program-focused article comprises two main sections. The first section presents the 'general' and 'specific contexts' in which the chair emerged. The 'general context' pertains to the health-related challenge of finding ways to integrate, transfer, and implement knowledge, a particularly pointed challenge in Canada. The 'specific context' refers to the emerging research field of adaptation of public health to climate change. In the second section, the characteristics of the research chair are more extensively detailed (the vision of 'innoversity' and ' transfrontier knowledge-for-action,' the approach of shared responsibility and complex collaboration, objectives, and major axes of research). We conclude with a call for complex collaboration toward knowledge-for-action in public health services/mental health services/public services' adaptation to climate change: this call is aimed at individual and institutional actors in the North and South/West and East concerned by these issues.

Evaluating the Benefits of Adaptation of Critical Infrastructures to Hydrometeorological Risks.

PubMed

Thacker, Scott; Kelly, Scott; Pant, Raghav; Hall, Jim W

2018-01-01

Infrastructure adaptation measures provide a practical way to reduce the risk from extreme hydrometeorological hazards, such as floods and windstorms. The benefit of adapting infrastructure assets is evaluated as the reduction in risk relative to the "do nothing" case. However, evaluating the full benefits of risk reduction is challenging because of the complexity of the systems, the scarcity of data, and the uncertainty of future climatic changes. We address this challenge by integrating methods from the study of climate adaptation, infrastructure systems, and complex networks. In doing so, we outline an infrastructure risk assessment that incorporates interdependence, user demands, and potential failure-related economic losses. Individual infrastructure assets are intersected with probabilistic hazard maps to calculate expected annual damages. Protection measure costs are integrated to calculate risk reduction and associated discounted benefits, which are used to explore the business case for investment in adaptation. A demonstration of the methodology is provided for flood protection of major electricity substations in England and Wales. We conclude that the ongoing adaptation program for major electricity assets is highly cost beneficial. © 2017 Society for Risk Analysis.

A Model for Climate Change Adaptation

NASA Astrophysics Data System (ADS)

Pasqualini, D.; Keating, G. N.

2009-12-01

Climate models predict serious impacts on the western U.S. in the next few decades, including increased temperatures and reduced precipitation. In combination, these changes are linked to profound impacts on fundamental systems, such as water and energy supplies, agriculture, population stability, and the economy. Global and national imperatives for climate change mitigation and adaptation are made actionable at the state level, for instance through greenhouse gas (GHG) emission regulations and incentives for renewable energy sources. However, adaptation occurs at the local level, where energy and water usage can be understood relative to local patterns of agriculture, industry, and culture. In response to the greenhouse gas emission reductions required by California’s Assembly Bill 32 (2006), Sonoma County has committed to sharp emissions reductions across several sectors, including water, energy, and transportation. To assist Sonoma County develop a renewable energy (RE) portfolio to achieve this goal we have developed an integrated assessment model, CLEAR (CLimate-Energy Assessment for Resiliency) model. Building on Sonoma County’s existing baseline studies of energy use, carbon emissions and potential RE sources, the CLEAR model simulates the complex interactions among technology deployment, economics and social behavior. This model enables assessment of these and other components with specific analysis of their coupling and feedbacks because, due to the complex nature of the problem, the interrelated sectors cannot be studied independently. The goal is an approach to climate change mitigation and adaptation that is replicable for use by other interested communities. The model user interfaces helps stakeholders and policymakers understand options for technology implementation.

Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions.

PubMed

Fox, Naomi J; Marion, Glenn; Davidson, Ross S; White, Piran C L; Hutchings, Michael R

2012-03-06

Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.

The complex planetary synchronization structure of the solar system

NASA Astrophysics Data System (ADS)

Scafetta, N.

2014-01-01

The complex planetary synchronization structure of the solar system, which since Pythagoras of Samos (ca. 570-495 BC) is known as the music of the spheres, is briefly reviewed from the Renaissance up to contemporary research. Copernicus' heliocentric model from 1543 suggested that the planets of our solar system form a kind of mutually ordered and quasi-synchronized system. From 1596 to 1619 Kepler formulated preliminary mathematical relations of approximate commensurabilities among the planets, which were later reformulated in the Titius-Bode rule (1766-1772), which successfully predicted the orbital position of Ceres and Uranus. Following the discovery of the ~ 11 yr sunspot cycle, in 1859 Wolf suggested that the observed solar variability could be approximately synchronized with the orbital movements of Venus, Earth, Jupiter and Saturn. Modern research has further confirmed that (1) the planetary orbital periods can be approximately deduced from a simple system of resonant frequencies; (2) the solar system oscillates with a specific set of gravitational frequencies, and many of them (e.g., within the range between 3 yr and 100 yr) can be approximately constructed as harmonics of a base period of ~ 178.38 yr; and (3) solar and climate records are also characterized by planetary harmonics from the monthly to the millennial timescales. This short review concludes with an emphasis on the contribution of the author's research on the empirical evidences and physical modeling of both solar and climate variability based on astronomical harmonics. The general conclusion is that the solar system works as a resonator characterized by a specific harmonic planetary structure that also synchronizes the Sun's activity and the Earth's climate. The special issue Pattern in solar variability, their planetary origin and terrestrial impacts (Mörner et al., 2013) further develops the ideas about the planetary-solar-terrestrial interaction with the personal contribution of 10 authors.

Interdisciplinary knowledge exchange across scales in a globally changing marine environment.

PubMed

McDonald, Karlie S; Hobday, Alistair J; Fulton, Elizabeth A; Thompson, Peter A

2018-07-01

The effects of anthropogenic global environmental change on biotic and abiotic processes have been reported in aquatic systems across the world. Complex synergies between concurrent environmental stressors and the resilience of the system to regime shifts, which vary in space and time, determine the capacity for marine systems to maintain structure and function with global environmental change. Consequently, an interdisciplinary approach that facilitates the development of new methods for the exchange of knowledge between scientists across multiple scales is required to effectively understand, quantify and predict climate impacts on marine ecosystem services. We use a literature review to assess the limitations and assumptions of current pathways to exchange interdisciplinary knowledge and the transferability of research findings across spatial and temporal scales and levels of biological organization to advance scientific understanding of global environmental change in marine systems. We found that species-specific regional scale climate change research is most commonly published, and "supporting" is the ecosystem service most commonly referred to in publications. In addition, our paper outlines a trajectory for the future development of integrated climate change science for sustaining marine ecosystem services such as investment in interdisciplinary education and connectivity between disciplines. © 2018 John Wiley & Sons Ltd.

Human Health and Climate Change: Leverage Points for Adaptation in Urban Environments

PubMed Central

Proust, Katrina; Newell, Barry; Brown, Helen; Capon, Anthony; Browne, Chris; Burton, Anthony; Dixon, Jane; Mu, Lisa; Zarafu, Monica

2012-01-01

The design of adaptation strategies that promote urban health and well-being in the face of climate change requires an understanding of the feedback interactions that take place between the dynamical state of a city, the health of its people, and the state of the planet. Complexity, contingency and uncertainty combine to impede the growth of such systemic understandings. In this paper we suggest that the collaborative development of conceptual models can help a group to identify potential leverage points for effective adaptation. We describe a three-step procedure that leads from the development of a high-level system template, through the selection of a problem space that contains one or more of the group’s adaptive challenges, to a specific conceptual model of a sub-system of importance to the group. This procedure is illustrated by a case study of urban dwellers’ maladaptive dependence on private motor vehicles. We conclude that a system dynamics approach, revolving around the collaborative construction of a set of conceptual models, can help communities to improve their adaptive capacity, and so better meet the challenge of maintaining, and even improving, urban health in the face of climate change. PMID:22829795

Biological feedbacks as cause and demise of the Neoproterozoic icehouse: astrobiological prospects for faster evolution and importance of cold conditions.

PubMed

Janhunen, Pekka; Kaartokallio, Hermanni; Oksanen, Ilona; Lehto, Kirsi; Lehto, Harry

2007-02-14

Several severe glaciations occurred during the Neoproterozoic eon, and especially near its end in the Cryogenian period (630-850 Ma). While the glacial periods themselves were probably related to the continental positions being appropriate for glaciation, the general coldness of the Neoproterozoic and Cryogenian as a whole lacks specific explanation. The Cryogenian was immediately followed by the Ediacaran biota and Cambrian Metazoan, thus understanding the climate-biosphere interactions around the Cryogenian period is central to understanding the development of complex multicellular life in general. Here we present a feedback mechanism between growth of eukaryotic algal phytoplankton and climate which explains how the Earth system gradually entered the Cryogenian icehouse from the warm Mesoproterozoic greenhouse. The more abrupt termination of the Cryogenian is explained by the increase in gaseous carbon release caused by the more complex planktonic and benthic foodwebs and enhanced by a diversification of metazoan zooplankton and benthic animals. The increased ecosystem complexity caused a decrease in organic carbon burial rate, breaking the algal-climatic feedback loop of the earlier Neoproterozoic eon. Prior to the Neoproterozoic eon, eukaryotic evolution took place in a slow timescale regulated by interior cooling of the Earth and solar brightening. Evolution could have proceeded faster had these geophysical processes been faster. Thus, complex life could theoretically also be found around stars that are more massive than the Sun and have main sequence life shorter than 10 Ga. We also suggest that snow and glaciers are, in a statistical sense, important markers for conditions that may possibly promote the development of complex life on extrasolar planets.

Biological Feedbacks as Cause and Demise of Neoproterozoic Icehouse: Astrobiological Prospects for Faster Evolution and Importance of Cold Conditions

PubMed Central

Janhunen, Pekka; Kaartokallio, Hermanni; Oksanen, Ilona; Lehto, Kirsi; Lehto, Harry

2007-01-01

Several severe glaciations occurred during the Neoproterozoic eon, and especially near its end in the Cryogenian period (630–850 Ma). While the glacial periods themselves were probably related to the continental positions being appropriate for glaciation, the general coldness of the Neoproterozoic and Cryogenian as a whole lacks specific explanation. The Cryogenian was immediately followed by the Ediacaran biota and Cambrian Metazoan, thus understanding the climate-biosphere interactions around the Cryogenian period is central to understanding the development of complex multicellular life in general. Here we present a feedback mechanism between growth of eukaryotic algal phytoplankton and climate which explains how the Earth system gradually entered the Cryogenian icehouse from the warm Mesoproterozoic greenhouse. The more abrupt termination of the Cryogenian is explained by the increase in gaseous carbon release caused by the more complex planktonic and benthic foodwebs and enhanced by a diversification of metazoan zooplankton and benthic animals. The increased ecosystem complexity caused a decrease in organic carbon burial rate, breaking the algal-climatic feedback loop of the earlier Neoproterozoic eon. Prior to the Neoproterozoic eon, eukaryotic evolution took place in a slow timescale regulated by interior cooling of the Earth and solar brightening. Evolution could have proceeded faster had these geophysical processes been faster. Thus, complex life could theoretically also be found around stars that are more massive than the Sun and have main sequence life shorter than 10 Ga. We also suggest that snow and glaciers are, in a statistical sense, important markers for conditions that may possibly promote the development of complex life on extrasolar planets. PMID:17299594

"Participatory Cli-Fi": Crowdsourcing Voicemails from the Future to Spark Engagement and Discern Perceptions of Climate Change

NASA Astrophysics Data System (ADS)

Stovall, G.; Eklund, K.; Redsecker, K.; Hernandez, T.; Pfirman, S. L.; Orlove, B. S.

2016-12-01

Communicating climate science alone is not enough to engage the public with climate change: the gap between the abstract science and its impact on their future lives is often too great. We constructed FutureCoast, a collaborative game, to use participatory storymaking as the art that bridges that gap. The FutureCoast game pretended the voicemail system of the future "had a leak in it" and invited people to call and leave voicemail messages that seem to have leaked from the future. These crowdsourced voicemails are short first-person stories that often create complex, visceral experiences of potential climate impacts in listeners. We transcribed and coded this audio for content and affect, finding both a wide array of anticipated climate futures and trends in public sentiment about climate related impacts. Our analysis found the public engages with climate change in both rational and emotional manners which should be considered when motivating them to action. This presentation highlights our methodology and assessment of innovative gameful engagement, and summarizes how the FutureCoast "participatory cli-fi" approach has been employed in community and classroom settings after the close of the active period of the game.

Emerging migration flows in a changing climate in dryland Africa

NASA Astrophysics Data System (ADS)

Kniveton, Dominic R.; Smith, Christopher D.; Black, Richard

2012-06-01

Fears of the movement of large numbers of people as a result of changes in the environment were first voiced in the 1980s (ref. ). Nearly thirty years later the numbers likely to migrate as a result of the impacts of climate change are still, at best, guesswork. Owing to the high prevalence of rainfed agriculture, many livelihoods in sub-Saharan African drylands are particularly vulnerable to changes in climate. One commonly adopted response strategy used by populations to deal with the resulting livelihood stress is migration. Here, we use an agent-based model developed around the theory of planned behaviour to explore how climate and demographic change, defined by the ENSEMBLES project and the United Nations Statistics Division of the Department of Economic and Social Affairs, combine to influence migration within and from Burkina Faso. The emergent migration patterns modelled support framing the nexus of climate change and migration as a complex adaptive system. Using this conceptual framework, we show that the extent of climate-change-related migration is likely to be highly nonlinear and the extent of this nonlinearity is dependent on population growth; therefore supporting migration policy interventions based on both demographic and climate change adaptation.

Climate change adaptation for the US National Wildlife Refuge System

USGS Publications Warehouse

Griffith, Brad; Scott, J. Michael; Adamcik, Robert S.; Ashe, Daniel; Czech, Brian; Fischman, Robert; Gonzalez, Patrick; Lawler, Joshua J.; McGuire, A. David; Pidgorna, Anna

2009-01-01

Since its establishment in 1903, the National Wildlife Refuge System (NWRS) has grown to 635 units and 37 Wetland Management Districts in the United States and its territories. These units provide the seasonal habitats necessary for migratory waterfowl and other species to complete their annual life cycles. Habitat conversion and fragmentation, invasive species, pollution, and competition for water have stressed refuges for decades, but the interaction of climate change with these stressors presents the most recent, pervasive, and complex conservation challenge to the NWRS. Geographic isolation and small unit size compound the challenges of climate change, but a combined emphasis on species that refuges were established to conserve and on maintaining biological integrity, diversity, and environmental health provides the NWRS with substantial latitude to respond. Individual symptoms of climate change can be addressed at the refuge level, but the strategic response requires system-wide planning. A dynamic vision of the NWRS in a changing climate, an explicit national strategic plan to implement that vision, and an assessment of representation, redundancy, size, and total number of units in relation to conservation targets are the first steps toward adaptation. This adaptation must begin immediately and be built on more closely integrated research and management. Rigorous projections of possible futures are required to facilitate adaptation to change. Furthermore, the effective conservation footprint of the NWRS must be increased through land acquisition, creative partnerships, and educational programs in order for the NWRS to meet its legal mandate to maintain the biological integrity, diversity, and environmental health of the system and the species and ecosystems that it supports.

Key Concepts for and Assessment of an Undergraduate Class that Engages Engineering Students in Climate Change Grand Challenge

NASA Astrophysics Data System (ADS)

Powers, S. E.; DeWaters, J.; Dhaniyala, S.

2015-12-01

Engineers must take a leading role in addressing the challenges of mitigating climate change and adapting to the inevitable changes that our world is facing. Yet climate change classes targeting engineering students are scarce. Technical education must focus on the problem formulation and solutions that consider multiple, complex interactions between engineered systems and the Earth's climate system and recognize that transformation raises societal challenges, including trade-offs among benefits, costs, and risks. Moreover, improving engineering students' climate science literacy will require strategies that also inspire students' motivation to work toward their solution. A climate science course for engineers has been taught 5 semesters as part of a NASA Innovations in Climate Education program grant (NNXlOAB57A). The basic premise of this project was that effective instruction must incorporate scientifically-based knowledge and observations and foster critical thinking, problem solving, and decision-making skills. Lecture, in-class cooperative and computer-based learning and a semester project provide the basis for engaging students in evaluating effective mitigation and adaptation solutions. Policy and social issues are integrated throughout many of the units. The objective of this presentation is to highlight the content and pedagogical approach used in this class that helped to contribute to significant gains in engineering students' climate literacy and critical thinking competencies. A total of 89 students fully participated in a pre/post climate literacy questionnaire. As a whole, students demonstrated significant gains in climate-related content knowledge (p<0.001), affect (p<0.001), and behavior (p=0.002). Mean post scores were above a 'passing' cutoff (70%) for all three subscales. Assessment of semester project reports with a critical thinking rubric showed that the students did an excellent job of formulating problem statements and solutions in a manner that incorporated a multidimensional systems perspective. These skills are sometimes foreign to technically focused, number crunching engineering students, but are critical for using their engineering skills and profession to address climate change mitigation and adaptation strategies.

Climate Resiliency Planning: Making Extreme Event Science Useful for Managers and Planners in Northern Nevada

NASA Astrophysics Data System (ADS)

McCarthy, M.; Kenneston, A.; Wall, T. U.; Brown, T. J.; Redmond, K. T.

2014-12-01

Effective climate resiliency planning at the regional level requires extensive interactive dialogue among climate scientists, emergency managers, public health officials, urban planners, social scientists, and policy makers. Engaging federal, tribal, state, local governments and private sector business and infrastructure owners/operators in defining, assessing and characterizing the impacts of extreme events allows communities to understand how different events "break the system" forcing local communities to seek support and resources from state/federal governments and/or the private sector and what actions can be taken proactively to mitigate consequences and accelerate recovery. The Washoe County Regional Resiliency Study was prepared in response to potential climate variability related impacts specific to the Northern Nevada Region. The last several decades have seen dramatic growth in the region, coupled with increased resource demands that have forced local governments to consider how those impacts will affect the region and may, in turn, impact the region's ability to provide essential services. The Western Regional Climate Center of the Desert Research Institute provided a synthesis of climate studies with predictions regarding plausible changes in the local climate of Northern California and Nevada for the next 50 years. In general, these predictions indicate that the region's climate is undergoing a gradual shift, which will primarily affect the frequency, amount, and form of precipitation in the Sierra Nevada and Great Basin. Changes in water availability and other extreme events may have serious and long lasting effects in the Northern Nevada Region, and create a variety of social, environmental and economic concerns. A range of extreme events were considered including Adverse Air Quality, Droughts, Floods, Heat Waves, High Wind, Structure Fires, Wildland Fires, and Major Winter Storms. Due to the complexity of our climate systems, and the difficulty in specifying how severe the climate effects may be or how those impacts compound existing hazards in the system, the Resiliency Study focused on identifying a variety of 'no regrets' policy options that can help the local communities anticipate, respond and recover faster and more efficiently to climate extremes.

Climate and Salmon Restoration in the Columbia River Basin: The Role and Usability of Seasonal Forecasts.

NASA Astrophysics Data System (ADS)

Pulwarty, Roger S.; Redmond, Kelly T.

1997-03-01

The Pacific Northwest is dependent on the vast and complex Columbia River system for power production, irrigation, navigation, flood control, recreation, municipal and industrial water supplies, and fish and wildlife habitat. In recent years Pacific salmon populations in this region, a highly valued cultural and economic resource, have declined precipitously. Since 1980, regional entities have embarked on the largest effort at ecosystem management undertaken to date in the United States, primarily aimed at balancing hydropower demands with salmon restoration activities. It has become increasingly clear that climatically driven fluctuations in the freshwater and marine environments occupied by these fish are an important influence on population variability. It is also clear that there are significant prospects of climate predictability that may prove advantageous in managing the water resources shared by the long cast of regional interests. The main thrusts of this study are 1) to describe the climate and management environments of the Columbia River basin, 2) to assess the present degree of use and benefits of available climate information, 3) to identify new roles and applications made possible by recent advances in climate forecasting, and 4) to understand, from the point of view of present and potential users in specific contexts of salmon management, what information might be needed, for what uses, and when, where, and how it should be provided. Interviews were carried out with 32 individuals in 19 organizations involved in salmon management decisions. Primary needs were in forecasting runoff volume and timing, river transit times, and stream temperatures, as much as a year or more in advance. Most respondents desired an accuracy of 75% for a seasonal forecast. Despite the significant influence of precipitation and its subsequent hydrologic impacts on the regional economy, no specific use of the present climate forecasts was uncovered. Understanding the limitations to information use forms a major component of this study. The complexity of the management environment, the lack of well-defined linkages among potential users and forecasters, and the lack of supplementary background information relating to the forecasts pose substantial barriers to future use of forecasts. Recommendations to address these problems are offered. The use of climate information and forecasts to reduce the uncertainty inherent in managing large systems for diverse needs bears significant promise.

Challenges and priorities for modelling livestock health and pathogens in the context of climate change

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

Özkan, Şeyda

Climate change has the potential to impair livestock health, with consequences for animal welfare, productivity, greenhouse gas emissions, and human livelihoods and health. Modelling has an important role in assessing the impacts of climate change on livestock systems and the efficacy of potential adaptation strategies, to support decision making for more efficient, resilient and sustainable production. However, a coherent set of challenges and research priorities for modelling livestock health and pathogens under climate change has not previously been available. To identify such challenges and priorities, researchers from across Europe were engaged in a horizon-scanning study, involving workshop and questionnaire basedmore » exercises and focussed literature reviews. Eighteen key challenges were identified and grouped into six categories based on subject-specific and capacity building requirements. Across a number of challenges, the need for inventories relating model types to different applications (e.g. the pathogen species, region, scale of focus and purpose to which they can be applied) was identified, in order to identify gaps in capability in relation to the impacts of climate change on animal health. The need for collaboration and learning across disciplines was highlighted in several challenges, e.g. to better understand and model complex ecological interactions between pathogens, vectors, wildlife hosts and livestock in the context of climate change. Collaboration between socio-economic and biophysical disciplines was seen as important for better engagement with stakeholders and for improved modelling of the costs and benefits of poor livestock health. The need for more comprehensive validation of empirical relationships, for harmonising terminology and measurements, and for building capacity for under-researched nations, systems and health problems indicated the importance of joined up approaches across nations. The challenges and priorities identified can help focus the development of modelling capacity and future research structures in this vital field. Well-funded networks capable of managing the long-term development of shared resources are required in order to create a cohesive modelling community equipped to tackle the complex challenges of climate change. - Highlights: • Experts identified challenges for health and pathogen modelling under climate change. • Eighteen key challenges and associated research priorities were identified. • Increasing capacity will require improved organisation and sharing knowledge. • Better communication across the diverse topics and approaches in this field is needed.« less

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

Dust in the Earth system: the biogeochemical linking of land, air and sea.

PubMed

Ridgwell, Andy J

2002-12-15

Understanding the response of the Earth's climate system to anthropogenic perturbation has been a pressing priority for society since the late 1980s. However, recent years have seen a major paradigm shift in how such an understanding can be reached. Climate change demands analysis within an integrated 'Earth-system' framework, taken to encompass the suite of interacting physical, chemical, biological and human processes that, in transporting and transforming materials and energy, jointly determine the conditions for life on the whole planet. This is a highly complex system, characterized by multiple nonlinear responses and thresholds, with linkages often between apparently disparate components. The interconnected nature of the Earth system is wonderfully illustrated by the diverse roles played by atmospheric transport of mineral 'dust', particularly in its capacity as a key pathway for the delivery of nutrients essential to plant growth, not only on land, but perhaps more importantly, in the ocean. Dust therefore biogeochemically links land, air and sea. This paper reviews the biogeochemical role of mineral dust in the Earth system and its interaction with climate, and, in particular, the potential importance of both past and possible future changes in aeolian delivery of the micro-nutrient iron to the ocean. For instance, if, in the future, there was to be a widespread stabilization of soils for the purpose of carbon sequestration on land, a reduction in aeolian iron supply to the open ocean would occur. The resultant weakening of the oceanic carbon sink could potentially offset much of the carbon sequestered on land. In contrast, during glacial times, enhanced dust supply to the ocean could have 'fertilized' the biota and driven atmospheric CO(2) lower. Dust might even play an active role in driving climatic change; since changes in dust supply may affect climate, and changes in climate, in turn, influence dust, a 'feedback loop' is formed. Possible feedback mechanisms are identified, recognition of whose operation could be crucial to our understanding of major climatic transitions over the past few million years.

Possible climates on terrestrial exoplanets.

PubMed

Forget, F; Leconte, J

2014-04-28

What kind of environment may exist on terrestrial planets around other stars? In spite of the lack of direct observations, it may not be premature to speculate on exoplanetary climates, for instance, to optimize future telescopic observations or to assess the probability of habitable worlds. To begin with, climate primarily depends on (i) the atmospheric composition and the volatile inventory; (ii) the incident stellar flux; and (iii) the tidal evolution of the planetary spin, which can notably lock a planet with a permanent night side. The atmospheric composition and mass depends on complex processes, which are difficult to model: origins of volatiles, atmospheric escape, geochemistry, photochemistry, etc. We discuss physical constraints, which can help us to speculate on the possible type of atmosphere, depending on the planet size, its final distance for its star and the star type. Assuming that the atmosphere is known, the possible climates can be explored using global climate models analogous to the ones developed to simulate the Earth as well as the other telluric atmospheres in the solar system. Our experience with Mars, Titan and Venus suggests that realistic climate simulators can be developed by combining components, such as a 'dynamical core', a radiative transfer solver, a parametrization of subgrid-scale turbulence and convection, a thermal ground model and a volatile phase change code. On this basis, we can aspire to build reliable climate predictors for exoplanets. However, whatever the accuracy of the models, predicting the actual climate regime on a specific planet will remain challenging because climate systems are affected by strong positive feedbacks. They can drive planets with very similar forcing and volatile inventory to completely different states. For instance, the coupling among temperature, volatile phase changes and radiative properties results in instabilities, such as runaway glaciations and runaway greenhouse effect.

The essential interactions between understanding climate variability and climate change

NASA Astrophysics Data System (ADS)

Neelin, J. D.

2017-12-01

Global change is sometimes perceived as a field separate from other aspects of atmospheric and oceanic sciences. Despite the long history of communication between the scientific communities studying global change and those studying interannual variability and weather, increasing specialization and conflicting societal demands on the fields can put these interactions at risk. At the same time, current trajectories for greenhouse gas emissions imply substantial adaptation to climate change will be necessary. Instead of simply projecting effects to be avoided, the field is increasingly being asked to provide regional-level information for specific adaptation strategies—with associated requirements for increased precision on projections. For extreme events, challenges include validating models for rare events, especially for events that are unprecedented in the historical record. These factors will be illustrated with examples of information transfer to climate change from work on fundamental climate processes aimed originally at timescales from hours to interannual. Work to understand the effects that control probability distributions of moisture, temperature and precipitation in historical weather can yield new factors to examine for the changes in the extremes of these distributions under climate change. Surprisingly simple process models can give insights into the behavior of vastly more complex climate models. Observation systems and model ensembles aimed at weather and interannual variations prove valuable for global change and vice versa. Work on teleconnections in the climate system, such as the remote impacts of El Niño, is informing analysis of projected regional rainfall change over California. Young scientists need to prepare to work across the full spectrum of climate variability and change, and to communicate their findings, as they and our society head for future that is more interesting than optimal.

PyMCT: A Very High Level Language Coupling Tool For Climate System Models

NASA Astrophysics Data System (ADS)

Tobis, M.; Pierrehumbert, R. T.; Steder, M.; Jacob, R. L.

2006-12-01

At the Climate Systems Center of the University of Chicago, we have been examining strategies for applying agile programming techniques to complex high-performance modeling experiments. While the "agile" development methodology differs from a conventional requirements process and its associated milestones, the process remain a formal one. It is distinguished by continuous improvement in functionality, large numbers of small releases, extensive and ongoing testing strategies, and a strong reliance on very high level languages (VHLL). Here we report on PyMCT, which we intend as a core element in a model ensemble control superstructure. PyMCT is a set of Python bindings for MCT, the Fortran-90 based Model Coupling Toolkit, which forms the infrastructure for the inter-component communication in the Community Climate System Model (CCSM). MCT provides a scalable model communication infrastructure. In order to take maximum advantage of agile software development methodologies, we exposed MCT functionality to Python, a prominent VHLL. We describe how the scalable architecture of MCT allows us to overcome the relatively weak runtime performance of Python, so that the performance of the combined system is not severely impacted. To demonstrate these advantages, we reimplemented the CCSM coupler in Python. While this alone offers no new functionality, it does provide a rigorous test of PyMCT functionality and performance. We reimplemented the CPL6 library, presenting an interesting case study of the comparison between conventional Fortran-90 programming and the higher abstraction level provided by a VHLL. The powerful abstractions provided by Python will allow much more complex experimental paradigms. In particular, we hope to build on the scriptability of our coupling strategy to enable systematic sensitivity tests. Our most ambitious objective is to combine our efforts with Bayesian inverse modeling techniques toward objective tuning at the highest level, across model architectures.

GRACE, time-varying gravity, Earth system dynamics and climate change

NASA Astrophysics Data System (ADS)

Wouters, B.; Bonin, J. A.; Chambers, D. P.; Riva, R. E. M.; Sasgen, I.; Wahr, J.

2014-11-01

Continuous observations of temporal variations in the Earth's gravity field have recently become available at an unprecedented resolution of a few hundreds of kilometers. The gravity field is a product of the Earth's mass distribution, and these data—provided by the satellites of the Gravity Recovery And Climate Experiment (GRACE)—can be used to study the exchange of mass both within the Earth and at its surface. Since the launch of the mission in 2002, GRACE data has evolved from being an experimental measurement needing validation from ground truth, to a respected tool for Earth scientists representing a fixed bound on the total change and is now an important tool to help unravel the complex dynamics of the Earth system and climate change. In this review, we present the mission concept and its theoretical background, discuss the data and give an overview of the major advances GRACE has provided in Earth science, with a focus on hydrology, solid Earth sciences, glaciology and oceanography.

The MICE facility - a new tool to study plant-soil C cycling with a holistic approach.

PubMed

Studer, Mirjam S; Künzli, Roland; Maier, Reto; Schmidt, Michael W I; Siegwolf, Rolf T W; Woodhatch, Ivan; Abiven, Samuel

2017-06-01

Plant-soil interactions are recognized to play a crucial role in the ecosystem response to climate change. We developed a facility to disentangle the complex interactions behind the plant-soil C feedback mechanisms. The MICE ('Multi-Isotope labelling in a Controlled Environment') facility consists of two climate chambers with independent control of the atmospheric conditions (light, CO 2 , temperature, humidity) and the soil environment (temperature, moisture). Each chamber holds 15 plant-soil systems with hermetical separation of the shared above ground (shoots) from the individual belowground compartments (roots, rhizosphere, soil). Stable isotopes (e.g. 13 C, 15 N, 2 H, 18 O) can be added to either compartment and traced within the whole system. The soil CO 2 efflux rate is monitored, and plant material, leached soil water and gas samples are taken frequently. The facility is a powerful tool to improve our mechanistic understanding of plant-soil interactions that drive the C cycle feedback to climate change.

GRACE, time-varying gravity, Earth system dynamics and climate change.

PubMed

Wouters, B; Bonin, J A; Chambers, D P; Riva, R E M; Sasgen, I; Wahr, J

2014-11-01

Continuous observations of temporal variations in the Earth's gravity field have recently become available at an unprecedented resolution of a few hundreds of kilometers. The gravity field is a product of the Earth's mass distribution, and these data-provided by the satellites of the Gravity Recovery And Climate Experiment (GRACE)-can be used to study the exchange of mass both within the Earth and at its surface. Since the launch of the mission in 2002, GRACE data has evolved from being an experimental measurement needing validation from ground truth, to a respected tool for Earth scientists representing a fixed bound on the total change and is now an important tool to help unravel the complex dynamics of the Earth system and climate change. In this review, we present the mission concept and its theoretical background, discuss the data and give an overview of the major advances GRACE has provided in Earth science, with a focus on hydrology, solid Earth sciences, glaciology and oceanography.

Combustion-derived substances in deep basins of Puget Sound: historical inputs from fossil fuel and biomass combustion.

PubMed

Kuo, Li-Jung; Louchouarn, Patrick; Herbert, Bruce E; Brandenberger, Jill M; Wade, Terry L; Crecelius, Eric

2011-04-01

Reconstructions of 250 years historical inputs of two distinct types of black carbon (soot/graphitic black carbon (GBC) and char-BC) were conducted on sediment cores from two basins of the Puget Sound, WA. Signatures of polycyclic aromatic hydrocarbons (PAHs) were also used to support the historical reconstructions of BC to this system. Down-core maxima in GBC and combustion-derived PAHs occurred in the 1940s in the cores from the Puget Sound Main Basin, whereas in Hood Canal such peak was observed in the 1970s, showing basin-specific differences in inputs of combustion byproducts. This system showed relatively higher inputs from softwood combustion than the northeastern U.S. The historical variations in char-BC concentrations were consistent with shifts in climate indices, suggesting an influence of climate oscillations on wildfire events. Environmental loading of combustion byproducts thus appears as a complex function of urbanization, fuel usage, combustion technology, environmental policies, and climate conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Consequences of ecological, evolutionary and biogeochemical uncertainty for coral reef responses to climatic stress.

PubMed

Mumby, Peter J; van Woesik, Robert

2014-05-19

Coral reefs are highly sensitive to the stress associated with greenhouse gas emissions, in particular ocean warming and acidification. While experiments show negative responses of most reef organisms to ocean warming, some autotrophs benefit from ocean acidification. Yet, we are uncertain of the response of coral reefs as systems. We begin by reviewing sources of uncertainty and complexity including the translation of physiological effects into demographic processes, indirect ecological interactions among species, the ability of coral reefs to modify their own chemistry, adaptation and trans-generational plasticity. We then incorporate these uncertainties into two simple qualitative models of a coral reef system under climate change. Some sources of uncertainty are far more problematic than others. Climate change is predicted to have an unambiguous negative effect on corals that is robust to several sources of uncertainty but sensitive to the degree of biogeochemical coupling between benthos and seawater. Macroalgal, zoanthid, and herbivorous fish populations are generally predicted to increase, but the ambiguity (confidence) of such predictions are sensitive to the source of uncertainty. For example, reversing the effect of climate-related stress on macroalgae from being positive to negative had no influence on system behaviour. By contrast, the system was highly sensitive to a change in the stress upon herbivorous fishes. Minor changes in competitive interactions had profound impacts on system behaviour, implying that the outcomes of mesocosm studies could be highly sensitive to the choice of taxa. We use our analysis to identify new hypotheses and suggest that the effects of climatic stress on coral reefs provide an exceptional opportunity to test emerging theories of ecological inheritance. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Las Vegas Sustainability Atlas: Modeling Place-based Interactions and Implications in the Las Vegas Valley Bioregion

NASA Astrophysics Data System (ADS)

Ego, H.; McCown, K.; Saghafi, N.; Gross, E.; Hunter, W.; Zawarus, P.; Gann, A.; Piechota, T. C.

2014-12-01

Las Vegas, Nevada, with 2 million residents and 40 million annual visitors, is one of the driest metropolitan environments of its size in the world. The metro imports nearly all of its resources, including energy, water and food. Rapid population increases, drought, and temperature increases due to climate change create challenges for planning resilient systems in the Las Vegas Valley. Because of its growth rate, aridity, Las Vegas, Nevada is a significant and relevant region for the study of the water, energy, food and climate nexus. Cities in the United States and the world are seeing increasing trends in urbanization and water scarcity. How does the water-energy-climate-food nexus affect each metropolitan area? How can this complex information be used for resiliency planning? How can it be related to the public, so they can understand the issues in a way that makes them meaningful participants in the planning process? The topic of our presentation is a 'resiliency atlas.' The atlas is a place-based model tested in Las Vegas to explore bioregional distinctiveness of the water-energy-climate-food nexus, including regional transportation systems. The atlas integrates the systems within a utilitarian organization of information. Systems in this place-based model demonstrate how infrastructure services are efficiently provided for the Las Vegas Valley population. This resiliency atlas can clarify how the nexus applies to place; and how it can be used to spur geographically germane adaption strategies. In the Las Vegas Valley, climate change (drought and high sustained temperatures) and population affect water, energy, and food systems. This clarity of a place based model can help educate the public about the resilience of their place, and facilitate and organize the planning process in the face of uncertainty.

Braking effect of climate and topography on global change-induced upslope forest expansion.

PubMed

Alatalo, Juha M; Ferrarini, Alessandro

2017-03-01

Forests are expected to expand into alpine areas due to global climate change. It has recently been shown that temperature alone cannot realistically explain this process and that upslope tree advance in a warmer scenario may depend on the availability of sites with adequate geomorphic/topographic characteristics. Here, we show that, besides topography (slope and aspect), climate itself can produce a braking effect on the upslope advance of subalpine forests and that tree limit is influenced by non-linear and non-monotonic contributions of the climate variables which act upon treeline upslope advance with varying relative strengths. Our results suggest that global climate change impact on the upslope advance of subalpine forests should be interpreted in a more complex way where climate can both speed up and slow down the process depending on complex patterns of contribution from each climate and non-climate variable.

Landscape evolution and agricultural land salinization in coastal area: A conceptual model.

PubMed

Bless, Aplena Elen; Colin, François; Crabit, Armand; Devaux, Nicolas; Philippon, Olivier; Follain, Stéphane

2018-06-01

Soil salinization is a major threat to agricultural lands. Among salt-affected lands, coastal areas could be considered as highly complex systems, where salinization degradation due to anthropogenic pressure and climate-induced changes could significantly alter system functioning. For such complex systems, conceptual models can be used as evaluation tools in a preliminary step to identify the main evolutionary processes responsible for soil and water salinization. This study aimed to propose a conceptual model for water fluxes in a coastal area affected by salinity, which can help to identify the relationships between agricultural landscape evolution and actual salinity. First, we conducted field investigations from 2012 to 2016, mainly based on both soil (EC 1/5 ) and water (EC w ) electrical conductivity survey. This allowed us to characterize spatial structures for EC 1/5 and EC w and to identify the river as a preponderant factor in land salinization. Subsequently, we proposed and used a conceptual model for water fluxes and conducted a time analysis (1962-2012) for three of its main constitutive elements, namely climate, river, and land systems. When integrated within the conceptual model framework, it appeared that the evolution of all constitutive elements since 1962 was responsible for the disruption of system equilibrium, favoring overall salt accumulation in the soil root zone. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Ruane, A. C.

2016-12-01

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

Beyond Wiki to Judgewiki for Transparent Climate Change Decisions

NASA Astrophysics Data System (ADS)

Capron, M. E.

2008-12-01

Climate Change is like the prisoner's dilemma, a zero-sum game, or cheating in sports. Everyone and every country is tempted to selfishly maintain or advance their standard of living. The tremendous difference between standards of living amplifies the desire to opt out of Climate Change solutions adverse to economic competitiveness. Climate Change is also exceedingly complex. No one person, one organization, one country, or partial collection of countries has the capacity and the global support needed to make decisions on Climate Change solutions. There are thousands of potential actions, tens of thousands of known and unknown environmental and economic impacts. Some actions are belatedly found to be unsustainable beyond token volumes, corn ethanol or soy-biodiesel for example. Mankind can address human nature and complexity with a globally transparent information and decision process available to all 7 billion of us. We need a process that builds trust and simplifies complexity. Fortunately, we have the Internet for trust building communication and computers to simplify complexity. Mankind can produce new software tailored to the challenge. We would combine group information collection software (a wiki) with a decision-matrix (a judge), market forecasting, and video games to produce the tool mankind needs for trust building transparent decisions on Climate Change actions. The resulting software would be a judgewiki.

Aerosol Complexity and Implications for Predictability and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Colarco, Peter

2016-01-01

There are clear NWP and climate impacts from including aerosol radiative and cloud interactions. Changes in dynamics and cloud fields affect aerosol lifecycle, plume height, long-range transport, overall forcing of the climate system, etc. Inclusion of aerosols in NWP systems has benefit to surface field biases (e.g., T2m, U10m). Including aerosol affects has impact on analysis increments and can have statistically significant impacts on, e.g., tropical cyclogenesis. Above points are made especially with respect to aerosol radiative interactions, but aerosol-cloud interaction is a bigger signal on the global system. Many of these impacts are realized even in models with relatively simple (bulk) aerosol schemes (approx.10 -20 tracers). Simple schemes though imply simple representation of aerosol absorption and importantly for aerosol-cloud interaction particle-size distribution. Even so, more complex schemes exhibit a lot of diversity between different models, with issues such as size selection both for emitted particles and for modes. Prospects for complex sectional schemes to tune modal (and even bulk) schemes toward better selection of size representation. I think this is a ripe topic for more research -Systematic documentation of benefits of no vs. climatological vs. interactive (direct and then direct+indirect) aerosols. Document aerosol impact on analysis increments, inclusion in NWP data assimilation operator -Further refinement of baseline assumptions in model design (e.g., absorption, particle size distribution). Did not get into model resolution and interplay of other physical processes with aerosols (e.g., moist physics, obviously important), chemistry

Using Models to Teach about Climate Change: A look at NGSS Expectations and Teacher Perceptions

NASA Astrophysics Data System (ADS)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2013-12-01

The Next Generation Science Standards have been updated from the previous version of the standards with some much needed emphasis on topics in climate and climate change. In particular, the standards have focused on K-12 students learning about science models, which is extremely important when discussing climate change. The NGSS suggest that students be able to 1) develop and use science models (not just use them to explain a concept) because this is how scientists actually use models during the scientific process; and 2) understand systems and system models across all science concepts and all age levels because it leads to further understanding about a more complex natural system (like climate change). To summarize, the NGSS expects that K-12 students should develop and use system models across disciplines and age groups in a way that is similar to how scientists use them in practice, which is to make predictions about unanswered questions. Research indicates that students who learn about science content using an approach that aligns more authentically with the way real science inquiry is done have a better understanding of the content, better understanding of the nature of science, improved critical thinking skills, and improved problem solving skills. Research also indicates that most teachers are aware of this method to teach science content, but sometimes have trouble implementing it into the classroom effectively for many reasons. If accepted, this presentation will share an approach to incorporate modeling into the classroom effectively as well as report the results from a study that qualitatively look at three teacher's perspectives on using models in the classroom while teaching units about climate change, in order to identify how/why teachers struggle to teach about models involved in content related to climate change. Preliminary results indicate that the teachers in this study view models as an effective way to explain a concept to their students, but none of them mention or discuss the predictive power of models. Although models are a useful way to explain a complex phenomenon concisely, arguably the most important role science models play in scientific inquiry is their ability to allow scientists to make prediction, especially when it comes to climate change. Since all three teachers overlooked the predictive power of models, it indicates that that they do not have a firm understanding of the role science models play in making scientific predictions. In conclusion, there is discrepancy between what the NGSS indicate students should be learning about modeling and what teachers are prepared to teach. In order to better prepare teachers to meet the demands required of them, they need to be better educated about models, what they are, what they do, and how scientists use them. By preparing teachers to teach K-12 students about the role models play in climate research, we can build a more knowledgeable society that is better prepared to make informed decisions on how to deal with issues in our changing climate.

Implication of climate change on urban drainage systems of Chicago and Mainstream and DesPlaines (MS/DP) Tunnel and Reservoir Plan (TARP)

NASA Astrophysics Data System (ADS)

Luo, H.; Schmidt, A.; Garcia, M. H.; Oberg, N.

2016-12-01

The impact of changing climate patterns and rainfall extremes on sewer system and river basin has been brought to attention to the researchers worldwide. In 1972, the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) adopted the Tunnel and Reservoir Plan (TARP) to address combined sewer overflow (CSO) pollution and flooding problems in the Chicago land area. The hydrosystem laboratory in University of Illinois at Urbana-Champaign developed a series of numerical models accordingly to analyze the complex hydraulic behavior of the as-built TARP system. Due to the interconnected nature of City of Chicago sewer network and MS/DP TARP system, a tightly coupled hydrological and hydraulic model MetroFlow was developed to facilitate such analysis by integrating previous developed models. This study utilized MetroFlow to predict the hydrologic/hydraulic response of the system for a set of pre-determined design and historical storm events. Accordingly, combined sewer overflows (CSO) of Chicago combined sewer system and MS/DP TARP system were evaluated under current and future weather scenarios. The total CSOs from TARP system can be considered as urban point pollution source to the surrounding receiving bodies, hence the potential impact of climate change on CSO fluxes is essential reference to wastewater infrastructure design and operations of the hydraulic regulating structures under storm events to mitigate predicted risks.

Uncertainty Management in Remote Sensing of Climate Data. Summary of A Workshop

NASA Technical Reports Server (NTRS)

McConnell, M.; Weidman, S.

2009-01-01

Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis (NRC, 2007). Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data, including statistical methods used to calibrate and validate satellite instruments, lack an overall mathematically based framework.

Broad-scale climate influences on spring-spawning herring (Clupea harengus, L.) recruitment in the Western Baltic Sea.

PubMed

Gröger, Joachim P; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea.

Broad-Scale Climate Influences on Spring-Spawning Herring (Clupea harengus, L.) Recruitment in the Western Baltic Sea

PubMed Central

Gröger, Joachim P.; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea. PMID:24586279

Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system

Treesearch

Robert A. Riggs; Robert E. Keane; Norm Cimon; Rachel Cook; Lisa Holsinger; John Cook; Timothy DelCurto; L.Scott Baggett; Donald Justice; David Powell; Martin Vavra; Bridgett Naylor

2015-01-01

Landscape fire succession models (LFSMs) predict spatially-explicit interactions between vegetation succession and disturbance, but these models have yet to fully integrate ungulate herbivory as a driver of their processes. We modified a complex LFSM, FireBGCv2, to include a multi-species herbivory module, GrazeBGC. The system is novel in that it explicitly...

High skill in low-frequency climate response through fluctuation dissipation theorems despite structural instability.

PubMed

Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris

2010-01-12

Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.

The plight of the Marsh Arabs, an environmental and human rights crisis: an application of complexity theory.

PubMed

Newman, Susan Dunreath

2007-01-01

Saddam Hussein's calculated destruction of the marshes of southern Iraq had an overwhelming impact on the marsh ecosystem, the physical environment, and its inhabitants. Hussein succeeded in disrupting the 5000-year-old culture of the Marsh Arabs, severely affecting the health and well-being of this unique culture. Complexity science provides a foundation that supports an appreciation of the effects that changes in environment and climate have on health. Application of a complexity model provides guidance for understanding the intricate networks of connectivity among the components of the ecological system of the marshes of Southern Iraq that is necessary for restoration efforts.

Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Chen, Chia-Jeng; Lee, Tsung-Yu

2017-04-01

Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping with extreme events in empirical seasonal predictions are also carried out. Findings from this work will contribute to the development of an integrated water resources planning and management system.

Quantifying the drivers of water security risks in a complex northern deltaic ecosystem

NASA Astrophysics Data System (ADS)

Rokaya, P.; Wheater, H. S.; Lindenschmidt, K. E.

2017-12-01

There is still a need for improved, scientific evaluations of potential impacts of a changing flow regime on the northern deltaic ecosystems. This is particularly the case for the Slave River Delta (SRD) which is believed to be drying. Although streamflow regulation in the major headwater tributary and climate change have been presented as major contributors of hydro-ecological change in the SRD, a wide range of drivers such as large scale water withdrawal, land-use change and flow modulation by the upstream delta (i.e. the Peace-Athabasca Delta) could pose challenges to water security. However, limited numbers of studies with inadequate data make it difficult to understand the principal drivers of the hydro-ecological changes. One of the least explored drivers is the upstream delta which attenuates the peak flows, retains the floodwater and reduces the downstream flood intensity. This can have significant impact on the productivity and ecological diversity of the SRD, which are governed by water and nutrient-rich sediment supplied during flood events. Thus, the Slave River basin presents a complex river system where multiple drivers are in interplay resulting in a different (new) flow regime. However, any river flow alterations could significantly affect this ecologically and socio-economically delicate ecosystem. In this study, we investigate the critical challenges related to water security in a complex deltaic ecosystem, quantifying the relative impacts of climate change, human interventions and the upstream delta on the SRD. We demonstrate that the sustainability issues of northern deltaic systems are dynamic, complex and multi-faceted, and require an understanding of intricate relationships and feedback mechanisms between human and natural systems.

Understanding global climate change scenarios through bioclimate stratification

NASA Astrophysics Data System (ADS)

Soteriades, A. D.; Murray-Rust, D.; Trabucco, A.; Metzger, M. J.

2017-08-01

Despite progress in impact modelling, communicating and understanding the implications of climatic change projections is challenging due to inherent complexity and a cascade of uncertainty. In this letter, we present an alternative representation of global climate change projections based on shifts in 125 multivariate strata characterized by relatively homogeneous climate. These strata form climate analogues that help in the interpretation of climate change impacts. A Random Forests classifier was calculated and applied to 63 Coupled Model Intercomparison Project Phase 5 climate scenarios at 5 arcmin resolution. Results demonstrate how shifting bioclimate strata can summarize future environmental changes and form a middle ground, conveniently integrating current knowledge of climate change impact with the interpretation advantages of categorical data but with a level of detail that resembles a continuous surface at global and regional scales. Both the agreement in major change and differences between climate change projections are visually combined, facilitating the interpretation of complex uncertainty. By making the data and the classifier available we provide a climate service that helps facilitate communication and provide new insight into the consequences of climate change.

Simulation of long-term influence from technical systems on permafrost with various short-scale and hourly operation modes in Arctic region

NASA Astrophysics Data System (ADS)

Vaganova, N. A.

2017-12-01

Technogenic and climatic influences have a significant impact on the degradation of permafrost. Long-term forecasts of such changes during long-time periods have to be taken into account in the oil and gas and construction industries in view to development the Arctic and Subarctic regions. There are considered constantly operating technical systems (for example, oil and gas wells) that affect changes in permafrost, as well as the technical systems that have a short-term impact on permafrost (for example, flare systems for emergency flaring of associated gas). The second type of technical systems is rather complex for simulation, since it is required to reserve both short and long-scales in computations with variable time steps describing the complex technological processes. The main attention is paid to the simulation of long-term influence on the permafrost from the second type of the technical systems.

Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model

NASA Astrophysics Data System (ADS)

O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.

2015-12-01

Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.

Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission

DOE PAGES

Parham, Paul E.; Waldock, Joanna; Christophides, George K.; ...

2015-02-16

Arguably one of the most important effects of climate change is the potential impact on human health. While this is likely to take many forms, the implications for future transmission of vector-borne diseases (VBDs), given their ongoing contribution to global disease burden, are both extremely important and highly uncertain. In part, this is due not only to data limitations and methodological challenges when integrating climate-driven VBD models and climate change projections, but, perhaps most crucially, the multitude of epidemiological, ecological, and socioeconomic factors that drive VBD transmission, and this complexity has generated considerable debate over the last 10-15 years. Inmore » this article, and Theme Issue, we seek to elucidate current knowledge around this topic, identify key themes and uncertainties, evaluate ongoing challenges and open research questions, and, crucially, offer some solutions for the field moving forwards. Although many of these challenges are ubiquitous across multiple VBDs, more specific issues also arise in different vector-pathogen systems. This Theme Issue seeks to cover both, reflected in the breadth and depth of the topics and VBD-systems considered, itself strongly indicative of the challenging, but necessary, multidisciplinary nature of this research field.« less

Analysis of the El Niño/La Niña-Southern Oscillation variability and malaria in the Estado Sucre, Venezuela.

PubMed

Delgado-Petrocelli, Laura; Córdova, Karenia; Camardiel, Alberto; Aguilar, Víctor H; Hernández, Denise; Ramos, Santiago

2012-09-01

The last decade has seen an unprecedented, worldwide acceleration of environmental and climate changes. These processes impact the dynamics of natural systems, which include components associated with human communities such as vector-borne diseases. The dynamics of environmental and climate variables, altered by global change as reported by the Intergovernmental Panel on Climate Change, affect the distribution of many tropical diseases. Complex systems, e.g. the El Niño/La Niña-Southern Oscillation (ENSO), in which environmental variables operate synergistically, can provoke the reemergence and emergence of vector-borne diseases at new sites. This research investigated the influence of ENSO events on malaria incidence by determining the relationship between climate variations, expressed as warm, cold and neutral phases, and their relation to the number of malaria cases in some north-eastern municipalities of Venezuela (Estado Sucre) during the period 1990-2000. Significant differences in malaria incidence were found, particularly in the La Niña ENSO phases (cold) of moderate intensity. These findings should be taken into account for surveillance and control in the future as they shed light on important indicators that can lead to reduced vulnerability to malaria.

A Bayesian Approach to Evaluating Consistency between Climate Model Output and Observations

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Cressie, N.; Teixeira, J.

2010-12-01

Like other scientific and engineering problems that involve physical modeling of complex systems, climate models can be evaluated and diagnosed by comparing their output to observations of similar quantities. Though the global remote sensing data record is relatively short by climate research standards, these data offer opportunities to evaluate model predictions in new ways. For example, remote sensing data are spatially and temporally dense enough to provide distributional information that goes beyond simple moments to allow quantification of temporal and spatial dependence structures. In this talk, we propose a new method for exploiting these rich data sets using a Bayesian paradigm. For a collection of climate models, we calculate posterior probabilities its members best represent the physical system each seeks to reproduce. The posterior probability is based on the likelihood that a chosen summary statistic, computed from observations, would be obtained when the model's output is considered as a realization from a stochastic process. By exploring how posterior probabilities change with different statistics, we may paint a more quantitative and complete picture of the strengths and weaknesses of the models relative to the observations. We demonstrate our method using model output from the CMIP archive, and observations from NASA's Atmospheric Infrared Sounder.

Slowing down as an early warning signal for abrupt climate change.

PubMed

Dakos, Vasilis; Scheffer, Marten; van Nes, Egbert H; Brovkin, Victor; Petoukhov, Vladimir; Held, Hermann

2008-09-23

In the Earth's history, periods of relatively stable climate have often been interrupted by sharp transitions to a contrasting state. One explanation for such events of abrupt change is that they happened when the earth system reached a critical tipping point. However, this remains hard to prove for events in the remote past, and it is even more difficult to predict if and when we might reach a tipping point for abrupt climate change in the future. Here, we analyze eight ancient abrupt climate shifts and show that they were all preceded by a characteristic slowing down of the fluctuations starting well before the actual shift. Such slowing down, measured as increased autocorrelation, can be mathematically shown to be a hallmark of tipping points. Therefore, our results imply independent empirical evidence for the idea that past abrupt shifts were associated with the passing of critical thresholds. Because the mechanism causing slowing down is fundamentally inherent to tipping points, it follows that our way to detect slowing down might be used as a universal early warning signal for upcoming catastrophic change. Because tipping points in ecosystems and other complex systems are notoriously hard to predict in other ways, this is a promising perspective.

Climate change and health in Israel: adaptation policies for extreme weather events.

PubMed

Green, Manfred S; Pri-Or, Noemie Groag; Capeluto, Guedi; Epstein, Yoram; Paz, Shlomit

2013-06-27

Climatic changes have increased the world-wide frequency of extreme weather events such as heat waves, cold spells, floods, storms and droughts. These extreme events potentially affect the health status of millions of people, increasing disease and death. Since mitigation of climate change is a long and complex process, emphasis has recently been placed on the measures required for adaptation. Although the principles underlying these measures are universal, preparedness plans and policies need to be tailored to local conditions. In this paper, we conducted a review of the literature on the possible health consequences of extreme weather events in Israel, where the conditions are characteristic of the Mediterranean region. Strong evidence indicates that the frequency and duration of several types of extreme weather events are increasing in the Mediterranean Basin, including Israel. We examined the public health policy implications for adaptation to climate change in the region, and proposed public health adaptation policy options. Preparedness for the public health impact of increased extreme weather events is still relatively limited and clear public health policies are urgently needed. These include improved early warning and monitoring systems, preparedness of the health system, educational programs and the living environment. Regional collaboration should be a priority.

Slowing down as an early warning signal for abrupt climate change

PubMed Central

Dakos, Vasilis; Scheffer, Marten; van Nes, Egbert H.; Brovkin, Victor; Petoukhov, Vladimir; Held, Hermann

2008-01-01

In the Earth's history, periods of relatively stable climate have often been interrupted by sharp transitions to a contrasting state. One explanation for such events of abrupt change is that they happened when the earth system reached a critical tipping point. However, this remains hard to prove for events in the remote past, and it is even more difficult to predict if and when we might reach a tipping point for abrupt climate change in the future. Here, we analyze eight ancient abrupt climate shifts and show that they were all preceded by a characteristic slowing down of the fluctuations starting well before the actual shift. Such slowing down, measured as increased autocorrelation, can be mathematically shown to be a hallmark of tipping points. Therefore, our results imply independent empirical evidence for the idea that past abrupt shifts were associated with the passing of critical thresholds. Because the mechanism causing slowing down is fundamentally inherent to tipping points, it follows that our way to detect slowing down might be used as a universal early warning signal for upcoming catastrophic change. Because tipping points in ecosystems and other complex systems are notoriously hard to predict in other ways, this is a promising perspective. PMID:18787119

The Consortium for Climate Risk in the Urban Northeast: A NOAA RISA Project

NASA Astrophysics Data System (ADS)

Rosenzweig, C.

2011-12-01

The Consortium for Climate Risk in the Urban Northeast, or CCRUN, was funded in October 2010 under NOAA's Regional Integrated Sciences and Assessments (RISA) program to serve stakeholder needs in assessing and managing risks from climate variability and change. It is currently also the only RISA team with a principal focus on climate change adaptation in urban settings. While CCRUN's initial focus is on the major cities of the urban Northeast corridor (Philadelphia, New York and Boston), its work will ultimately expand to cover small and medium-sized cities in the relevant portions of Massachusetts, Rhode Island, Connecticut, New York, New Jersey and Pennsylvania as well, so that local needs for targeted climate-risk information can be served in a coordinated way. CCRUN is designed to address the complex challenges that are associated with densely populated, highly interconnected urban areas, including such as urban heat island effects; poor air quality; intense coastal development, and multifunctional settlement along inland waterways; complex overlapping institutional jurisdictions; integrated infrastructure systems; and highly diverse, and in some cases, fragile socio-economic communities. These challenges can best be addressed by the stakeholder-driven interdisciplinary approach taken by the CCRUN RISA team. As an important added benefit, the research accomplishments and lessons learned through stakeholder engagement will provide a foundation for managing climate risks in other urban areas in the United States. CCRUN's initial projects are focused in three broad sectors: Water, Coasts, and Health. Research in each of these sectors is linked through the cross-cutting themes of climate change and community vulnerability, the latter of which is especially important in considerations of environmental justice and equity. CCRUN's stakeholder-driven approach to research can therefore support investigations of the impacts of a changing climate, population growth, and urban and economic policies on the social, racial and ethnic dimensions of livelihoods and of communities in the urban Northeast corridor. Disadvantaged socio-economic groups have been particularly underserved in the area of climate change, and one of CCRUN's long-term goals is the building of adaptive capacity among such groups to current and future climate extremes.

Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies

NASA Astrophysics Data System (ADS)

Chang, Kelly M.; Hess, Jeremy J.; Balbus, John M.; Buonocore, Jonathan J.; Cleveland, David A.; Grabow, Maggie L.; Neff, Roni; Saari, Rebecca K.; Tessum, Christopher W.; Wilkinson, Paul; Woodward, Alistair; Ebi, Kristie L.

2017-11-01

Background: Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2 °C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making. Methods/Design: We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission ‘Managing the health effects of climate change’ through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes. Results/Synthesis: Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system. Discussion: Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake.

Teleconnection Locator: TeleLoc

NASA Astrophysics Data System (ADS)

Bowen, M. K.; Duffy, D.

2016-12-01

Extreme climate events, such as tropical storms, droughts, and floods, have an enormous impact on all aspects of society. Being able to detect the causes of such events on a global scale is paramount to being able to predict when and where these events will occur. These teleconnections, where a small change in a closed, complex system creates drastic disturbances elsewhere in the system, are generally represented by an index, one of the most famous being the El Nino Southern Oscillation (ENSO). However, due to the enormity, complexity, and technical challenges surrounding climate and its data, it is hypothesized that many of these teleconnections have as of yet gone undiscovered. TeleLoc (Teleconnection Locator) is a machine-learning framework combining a number of techniques for finding correlations between weather trends and extreme climate events. The current focus is on connecting global trends with tropical cyclones. A combination of two data sets, The International Best Track Archive for Climate Stewardship (IBTrACS) and the Modern-Era Retrospective analysis for Research and Applications (MERRA2), are being utilized. PostGIS is used for raw data storage, and a Python API has been developed as the core of the framework. Cyclones are first clustered using a combination of Symbolic Aggregate ApproXimation (this allows for a symbolic, sequential representation of the various time-series variables of interest) and DBSCAN. This serves to break the events into subcategories, which alleviates computational load for the next step. Events which are clustered together (those with similar characteristics) are compared against global climate variables of interest, which are also converted to a symbolic form, leading up to the event using Association Rule Mining. Results will be shown where cyclones have been clustered, specifically in the West Pacific storm basin, as well as the global variable symbolic subsections with a high support that have been singled out for analysis.

Climate Model Ensemble Methodology: Rationale and Challenges

NASA Astrophysics Data System (ADS)

Vezer, M. A.; Myrvold, W.

2012-12-01

A tractable model of the Earth's atmosphere, or, indeed, any large, complex system, is inevitably unrealistic in a variety of ways. This will have an effect on the model's output. Nonetheless, we want to be able to rely on certain features of the model's output in studies aiming to detect, attribute, and project climate change. For this, we need assurance that these features reflect the target system, and are not artifacts of the unrealistic assumptions that go into the model. One technique for overcoming these limitations is to study ensembles of models which employ different simplifying assumptions and different methods of modelling. One then either takes as reliable certain outputs on which models in the ensemble agree, or takes the average of these outputs as the best estimate. Since the Intergovernmental Panel on Climate Change's Fourth Assessment Report (IPCC AR4) modellers have aimed to improve ensemble analysis by developing techniques to account for dependencies among models, and to ascribe unequal weights to models according to their performance. The goal of this paper is to present as clearly and cogently as possible the rationale for climate model ensemble methodology, the motivation of modellers to account for model dependencies, and their efforts to ascribe unequal weights to models. The method of our analysis is as follows. We will consider a simpler, well-understood case of taking the mean of a number of measurements of some quantity. Contrary to what is sometimes said, it is not a requirement of this practice that the errors of the component measurements be independent; one must, however, compensate for any lack of independence. We will also extend the usual accounts to include cases of unknown systematic error. We draw parallels between this simpler illustration and the more complex example of climate model ensembles, detailing how ensembles can provide more useful information than any of their constituent models. This account emphasizes the epistemic importance of considering degrees of model dependence, and the practice of ascribing unequal weights to models of unequal skill.

Integrating observation and statistical forecasts over sub-Saharan Africa to support Famine Early Warning

USGS Publications Warehouse

Funk, Chris; Verdin, James P.; Husak, Gregory

2007-01-01

Famine early warning in Africa presents unique challenges and rewards. Hydrologic extremes must be tracked and anticipated over complex and changing climate regimes. The successful anticipation and interpretation of hydrologic shocks can initiate effective government response, saving lives and softening the impacts of droughts and floods. While both monitoring and forecast technologies continue to advance, discontinuities between monitoring and forecast systems inhibit effective decision making. Monitoring systems typically rely on high resolution satellite remote-sensed normalized difference vegetation index (NDVI) and rainfall imagery. Forecast systems provide information on a variety of scales and formats. Non-meteorologists are often unable or unwilling to connect the dots between these disparate sources of information. To mitigate these problem researchers at UCSB's Climate Hazard Group, NASA GIMMS and USGS/EROS are implementing a NASA-funded integrated decision support system that combines the monitoring of precipitation and NDVI with statistical one-to-three month forecasts. We present the monitoring/forecast system, assess its accuracy, and demonstrate its application in food insecure sub-Saharan Africa.

Chapter 15: Potential Surprises: Compound Extremes and Tipping Elements

NASA Technical Reports Server (NTRS)

Kopp, R. E.; Hayhoe, K.; Easterling, D. R.; Hall, T.; Horton, R.; Kunkel, K. E.; LeGrande, A. N.

2017-01-01

The Earth system is made up of many components that interact in complex ways across a broad range of temporal and spatial scales. As a result of these interactions the behavior of the system cannot be predicted by looking at individual components in isolation. Negative feedbacks, or self-stabilizing cycles, within and between components of the Earth system can dampen changes (Ch. 2: Physical Drivers of Climate Change). However, their stabilizing effects render such feedbacks of less concern from a risk perspective than positive feedbacks, or self-reinforcing cycles. Positive feedbacks magnify both natural and anthropogenic changes. Some Earth system components, such as arctic sea ice and the polar ice sheets, may exhibit thresholds beyond which these self-reinforcing cycles can drive the component, or the entire system, into a radically different state. Although the probabilities of these state shifts may be difficult to assess, their consequences could be high, potentially exceeding anything anticipated by climate model projections for the coming century.

Ocean-Atmosphere Coupled Model Simulations of Precipitation in the Central Andes

NASA Technical Reports Server (NTRS)

Nicholls, Stephen D.; Mohr, Karen I.

2015-01-01

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. In addition, South American meteorology and climate are also made further complicated by ENSO, a powerful coupled ocean-atmosphere phenomenon. Modelling studies in this region have typically resorted to either atmospheric mesoscale or atmosphere-ocean coupled global climate models. The latter offers full physics and high spatial resolution, but it is computationally inefficient typically lack an interactive ocean, whereas the former offers high computational efficiency and ocean-atmosphere coupling, but it lacks adequate spatial and temporal resolution to adequate resolve the complex orography and explicitly simulate precipitation. Explicit simulation of precipitation is vital in the Central Andes where rainfall rates are light (0.5-5 mm hr-1), there is strong seasonality, and most precipitation is associated with weak mesoscale-organized convection. Recent increases in both computational power and model development have led to the advent of coupled ocean-atmosphere mesoscale models for both weather and climate study applications. These modelling systems, while computationally expensive, include two-way ocean-atmosphere coupling, high resolution, and explicit simulation of precipitation. In this study, we use the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST), a fully-coupled mesoscale atmosphere-ocean modeling system. Previous work has shown COAWST to reasonably simulate the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data when ECMWF interim analysis data were used for boundary conditions on a 27-9-km grid configuration (Outer grid extent: 60.4S to 17.7N and 118.6W to 17.4W).

Estimating the impact of internal climate variability on ice sheet model simulations

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2016-12-01

Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR.

Stress Testing Water Resource Systems at Regional and National Scales with Synthetic Drought Event Sets

NASA Astrophysics Data System (ADS)

Hall, J. W.; Mortazavi-Naeini, M.; Coxon, G.; Guillod, B. P.; Allen, M. R.

2017-12-01

Water resources systems can fail to deliver the services required by water users (and deprive the environment of flow requirements) in many different ways. In an attempt to make systems more resilient, they have also been made more complex, for example through a growing number of large-scale transfers, optimized storages and reuse plants. These systems may be vulnerable to complex variants of hydrological variability in space and time, and behavioural adaptations by water users. In previous research we have used non-parametric stochastic streamflow generators to test the vulnerability of water resource systems. Here we use a very large ensemble of regional climate model outputs from the weather@home crowd-sourced citizen science project, which has generated more than 30,000 years of synthetic weather for present and future climates in the UK and western Europe, using the HadAM3P regional climate model. These simulations have been constructed in order to preserve prolonged drought characteristics, through treatment of long-memory processes in ocean circulations and soil moisture. The weather simulations have been propagated through the newly developed DynaTOP national hydrological for Britain, in order to provide low flow simulations at points of water withdrawal for public water supply, energy and agricultural abstractors. We have used the WATHNET water resource simulation model, set up for the Thames Basin and for all of the large water resource zones in England, to simulate the frequency, severity and duration of water shortages in all of these synthetic weather conditions. In particular, we have sought to explore systemic vulnerabilities associated with inter-basin transfers and the trade-offs between different water users. This analytical capability is providing the basis for (i) implementation of the Duty of Resilience, which has been placed upon the water industry in the 2014 Water Act and (ii) testing reformed abstraction arrangements which the UK government is committed to implementing.

A global satellite assisted precipitation climatology

USGS Publications Warehouse

Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

2015-01-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0,http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

A global satellite-assisted precipitation climatology

NASA Astrophysics Data System (ADS)

Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

2015-10-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high-resolution (0.05°) global precipitation climatologies that perform reasonably well in data-sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, doi:10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

Impact of choice of future climate change projection on growth chamber experimental outcomes: a preliminary study in potato.

PubMed

Leisner, Courtney P; Wood, Joshua C; Vaillancourt, Brieanne; Tang, Ying; Douches, Dave S; Robin Buell, C; Winkler, Julie A

2018-04-01

Understanding the impacts of climate change on agriculture is essential to ensure adequate future food production. Controlled growth experiments provide an effective tool for assessing the complex effects of climate change. However, a review of the use of climate projections in 57 previously published controlled growth studies found that none considered within-season variations in projected future temperature change, and few considered regional differences in future warming. A fixed, often arbitrary, temperature perturbation typically was applied for the entire growing season. This study investigates the utility of employing more complex climate change scenarios in growth chamber experiments. A case study in potato was performed using three dynamically downscaled climate change projections for the mid-twenty-first century that differ in terms of the timing during the growing season of the largest projected temperature changes. The climate projections were used in growth chamber experiments for four elite potato cultivars commonly planted in Michigan's major potato growing region. The choice of climate projection had a significant influence on the sign and magnitude of the projected changes in aboveground biomass and total tuber count, whereas all projections suggested an increase in total tuber weight and a decrease in specific gravity, a key market quality trait for potato, by mid-century. These results demonstrate that the use of more complex climate projections that extend beyond a simple incremental change can provide additional insights into the future impacts of climate change on crop production and the accompanying uncertainty.

Evaluating the impact of climate change on landslide occurrence, hazard, and risk: from global to regional scale.

NASA Astrophysics Data System (ADS)

Gariano, Stefano Luigi; Guzzetti, Fausto

2017-04-01

According to the fifth report of the Intergovernmental Panel on Climate Change, "warming of the climate system is unequivocal". The influence of climate changes on slope stability and landslides is also undisputable. Nevertheless, the quantitative evaluation of the impact of global warming, and the related changes in climate, on landslides remains a complex question to be solved. The evidence that climate and landslides act at only partially overlapping spatial and temporal scales complicates the evaluation. Different research fields, including e.g., climatology, physics, hydrology, geology, hydrogeology, geotechnics, soil science, environmental science, and social science, must be considered. Climatic, environmental, demographic, and economic changes are strictly correlated, with complex feedbacks, to landslide occurrence and variation. Thus, a holistic, multidisciplinary approach is necessary. We reviewed the literature on landslide-climate studies, and found a bias in their geographical distribution, with several studies centered in Europe and North America, and large parts of the world not investigated. We examined advantages and drawbacks of the approaches adopted to evaluate the effects of climate variations on landslides, including prospective modelling and retrospective methods that use landslide and climate records, and paleo-environmental information. We found that the results of landslide-climate studies depend more on the emission scenarios, the global circulation models, the regional climate models, and the methods to downscale the climate variables, than on the description of the variables controlling slope processes. Using ensembles of projections based on a range of emissions scenarios would reduce (or at least quantify) the uncertainties in the obtained results. We performed a preliminary global assessment of the future landslide impact, presenting a global distribution of the projected impact of climate change on landslide activity and abundance. Where global warming is expected to increase, the frequency and intensity of severe rainfall events, a primary trigger of shallow, rapid-moving landslides that cause many landslide fatalities, an increase in the number of people exposed to landslide risk is to be expected. Furthermore, we defined a group of objective and reproducible methods for the quantitative evaluation of the past and future (expected) variations in landslide occurrence and distribution, and in the impact and risk to the population, as a result of changes in climatic and environmental factors (particularly, land use changes), at regional scale. The methods were tested in a southern Italian region, but they can easily applied in other physiographic and climatic regions, where adequate information is available.

Climate change, carbon, and forestry in northwestern North America: proceedings of a workshop November 14-15, 2001 Orcas Island, Washington.

Treesearch

David L. Peterson; John L. Innes; Kelly O’Brian

2004-01-01

Interactions between forests, climatic change and the Earth’s carbon cycle are complex and represent a challenge for forest managers – they are integral to the sustainable management of forests. In this volume, a number of papers are presented that describe some of the complex relationships between climate, the global carbon cycle and forests. Research has demonstrated...

Actionable Science Lessons Emerging from the Department of Interior Climate Science Center Network

NASA Astrophysics Data System (ADS)

McMahon, G.; Meadow, A. M.; Mikels-Carrasco, J.

2015-12-01

The DOI Advisory Committee on Climate Change and Natural Resource Science (ACCCNRS) has recommended that co-production of actionable science be the core programmatic focus of the Climate Science Center enterprise. Efforts by the Southeast Climate Science Center suggest that the complexity of many climate adaptation decision problems (many stakeholders that can influence implementation of a decision; the problems that can be viewed at many scales in space and time; dynamic objectives with competing values; complex, non-linear systems) complicates development of research-based information that scientists and non-scientists view as comprehensible, trustworthy, legitimate, and accurate. Going forward, organizers of actionable science efforts should consider inclusion of a broad set of stakeholders, beyond formal decisionmakers, and ensure that sufficient resources are available to explore the interests and values of this broader group. Co-produced research endeavors should foster agency and collaboration across a wide range of stakeholders. We recognize that stakeholder agency may be constrained by scientific or political power structures that limit the ability to initiate discussion, make claims, and call things into question. Co-production efforts may need to be preceded by more descriptive assessments that summarize existing climate science in ways that stakeholders can understand and link with their concerns. Such efforts can build rapport and trust among scientists and non-scientists, and may help stakeholders and scientists alike to frame adaptation decision problems amenable to a co-production effort. Finally, university and government researchers operate within an evaluation structure that rewards researcher-driven science that, at the extreme, "throws information over the fence" in the hope that information users will make better decisions. Research evaluation processes must reward more consultative, collaborative, and collegial research approaches if researchers are to widely adopt co-production methods

Nonlinear Dynamics of Complex Coevolutionary Systems in Historical Times

NASA Astrophysics Data System (ADS)

Perdigão, Rui A. P.

2016-04-01

A new theoretical paradigm for statistical-dynamical modeling of complex coevolutionary systems is introduced, with the aim to provide historical geoscientists with a practical tool to analyse historical data and its underlying phenomenology. Historical data is assumed to represent the history of dynamical processes of physical and socio-economic nature. If processes and their governing laws are well understood, they are often treated with traditional dynamical equations: deterministic approach. If the governing laws are unknown or impracticable, the process is often treated as if being random (even if it is not): statistical approach. Although single eventful details - such as the exact spatiotemporal structure of a particular hydro-meteorological incident - may often be elusive to a detailed analysis, the overall dynamics exhibit group properties summarized by a simple set of categories or dynamical regimes at multiple scales - from local short-lived convection patterns to large-scale hydro-climatic regimes. The overwhelming microscale complexity is thus conveniently wrapped into a manageable group entity, such as a statistical distribution. In a stationary setting whereby the distribution is assumed to be invariant, alternating regimes are approachable as dynamical intermittence. For instance, in the context of bimodal climatic oscillations such as NAO and ENSO, each mode corresponds to a dynamical regime or phase. However, given external forcings or longer-term internal variability and multiscale coevolution, the structural properties of the system may change. These changes in the dynamical structure bring about a new distribution and associated regimes. The modes of yesteryear may no longer exist as such in the new structural order of the system. In this context, aside from regime intermittence, the system exhibits structural regime change. New oscillations may emerge whilst others fade into the annals of history, e.g. particular climate fluctuations during the Little Ice Age. Traditional theories of stochastic processes and dynamical systems are grounded on the existence of so-called dynamical invariants; properties that remain unchanged as the dynamics unfold, assuming structural invariance and ergodicity of the underlying system. However, such theories are no longer optimal when trying to understand and model long-term historical records of coevolutionary systems. A new paradigm is thus needed. Therefore, we introduce a new class of dynamical systems that reinvent themselves as the dynamics unfold. Rather than only changing variables and parameters under a rigid framework, the governing laws are malleable themselves. The novel formulation captures and explains the coevolutionary dynamics of multiscale hydroclimatic systems, bringing along a physically sound understanding of their regimes, transitions and extremes over a long-term history.

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.

Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions.

PubMed

Snover, Amy K; Mantua, Nathan J; Littell, Jeremy S; Alexander, Michael A; McClure, Michelle M; Nye, Janet

2013-12-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación. © 2013 Society for Conservation Biology.

Inter-model variability in hydrological extremes projections for Amazonian sub-basins

NASA Astrophysics Data System (ADS)

Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier

2014-05-01

Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.

Evolution in Australia's mesic biome under past and future climates: Insights from a phylogenetic study of the Australian Rock Orchids (Dendrobium speciosum complex, Orchidaceae).

PubMed

Simpson, Lalita; Clements, Mark A; Crayn, Darren M; Nargar, Katharina

2018-01-01

The Australian mesic biome spans c. 33° of latitude along Australia's east coast and ranges and is dissected by historical and contemporary biogeographical barriers. To investigate the impact of these barriers on evolutionary diversification and to predict the impact of future climate change on the distribution of species and genetic diversity within this biome, we inferred phylogenetic relationships within the Dendrobium speciosum complex (Orchidaceae) across its distribution and undertook environmental niche modelling (ENM) under past, contemporary and projected future climates. Neighbor Joining tree inference, NeighborNet and Structure analyses of Amplified Fragment Length Polymorphism (AFLP) profiles for D. speciosum sampled from across its distribution showed that the complex consists of two highly supported main groups that are geographically separated by the St. Lawrence gap, an area of dry sclerophyll forest and woodland. The presence of several highly admixed individuals identified by the Structure analysis provided evidence of genetic exchange between the two groups across this gap. Whereas previous treatments have recognised between one to eleven species, the molecular results support the taxonomic treatment of the complex as a single species with two subspecies. The ENM analysis supported the hypothesis that lineage divergence within the complex was driven by past climatic changes. The St. Lawrence gap represented a stronger biogeographic barrier for the D. speciosum complex during the cool and dry glacial climatic conditions of the Pleistocene than under today's interglacial conditions. Shallow genetic divergence was found within the two lineages, which mainly corresponded to three other biogeographic barriers: the Black Mountain Corridor, Glass House Mountains and the Hunter Valley. Our ENM analyses provide further support for the hypothesis that biogeographic barriers along Australia's east coast were somewhat permeable to genetic exchange due to past episodic range expansions and contractions caused by climatic change resulting in recurrent contact between previously isolated populations. An overall southward shift in the distribution of the complex under future climate scenarios was predicted, with the strongest effects on the northern lineage. This study contributes to our understanding of the factors shaping biodiversity patterns in Australia's mesic biome. Copyright © 2017 Elsevier Inc. All rights reserved.

Titan's atmosphere and climate

NASA Astrophysics Data System (ADS)

Hörst, S. M.

2017-03-01

Titan is the only moon with a substantial atmosphere, the only other thick N2 atmosphere besides Earth's, the site of extraordinarily complex atmospheric chemistry that far surpasses any other solar system atmosphere, and the only other solar system body with stable liquid currently on its surface. The connection between Titan's surface and atmosphere is also unique in our solar system; atmospheric chemistry produces materials that are deposited on the surface and subsequently altered by surface-atmosphere interactions such as aeolian and fluvial processes resulting in the formation of extensive dune fields and expansive lakes and seas. Titan's atmosphere is favorable for organic haze formation, which combined with the presence of some oxygen-bearing molecules indicates that Titan's atmosphere may produce molecules of prebiotic interest. The combination of organics and liquid, in the form of water in a subsurface ocean and methane/ethane in the surface lakes and seas, means that Titan may be the ideal place in the solar system to test ideas about habitability, prebiotic chemistry, and the ubiquity and diversity of life in the universe. The Cassini-Huygens mission to the Saturn system has provided a wealth of new information allowing for study of Titan as a complex system. Here I review our current understanding of Titan's atmosphere and climate forged from the powerful combination of Earth-based observations, remote sensing and in situ spacecraft measurements, laboratory experiments, and models. I conclude with some of our remaining unanswered questions as the incredible era of exploration with Cassini-Huygens comes to an end.

Data Mashups: Linking Human Health and Wellbeing with Weather, Climate and the Environment

NASA Astrophysics Data System (ADS)

Fleming, L. E.; Sarran, C.; Golding, B.; Haines, A.; Kessel, A.; Djennad, M.; Hajat, S.; Nichols, G.; Gordon Brown, H.; Depledge, M.

2016-12-01

A large part of the global disease burden can be linked to environmental factors, underpinned by unhealthy behaviours. Research into these linkages suffers from lack of common tools and databases for investigations across many different scientific disciplines to explore these complex associations. The MEDMI (Medical and Environmental Data-a Mash-up Infrastructure) Partnership brings together leading organisations and researchers in climate, weather, environment, and human health. We have created a proof-of-concept central data and analysis system with the UK Met Office and Public Health England data as the internet-based MEDMI Platform (www.data-mashup.org.uk) to serve as a common resource for researchers to link and analyse complex meteorological, environmental and epidemiological data in the UK. The Platform is hosted on its own dedicated server, with secure internet and in-person access with appropriate safeguards for ethical, copyright, security, preservation, and data sharing issues. Via the Platform, there is a demonstration Browser Application with access to user-selected subsets of the data for: a) analyses using time series (e.g. mortality/environmental variables), and b) data visualizations (e.g. infectious diseases/environmental variables). One demonstration project is linking climate change, harmful algal blooms and oceanographic modelling building on the hydrodynamic-biogeochemical coupled models; in situ and satellite observations as well as UK HAB data and hospital episode statistics data are being used for model verification and future forecasting. The MEDMI Project provides a demonstration of the potential, barriers and challenges, of these "data mashups" of environment and health data. Although there remain many challenges to creating and sustaining such a shared resource, these activities and resources are essential to truly explore the complex interactions between climate and other environmental change and health at the local and global scale.

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.

A tale of two California droughts: Lessons amidst record warmth and dryness in a region of complex physical and human geography

NASA Astrophysics Data System (ADS)

Swain, Daniel L.

2015-11-01

The state of California has experienced the worst drought in its historical record during 2012-2015. Adverse effects of this multiyear event have been far from uniformly distributed across the region, ranging from remarkably mild in most of California's densely populated coastal cities to very severe in more rural, agricultural, and wildfire-prone regions. This duality of impacts has created a tale of two very different California droughts—highlighting enhanced susceptibility to climate stresses at the environmental and socioeconomic margins of California. From a geophysical perspective, the persistence of related atmospheric anomalies has raised a number of questions regarding the drought's origins—including the role of anthropogenic climate change. Recent investigations underscore the importance of understanding the underlying physical causes of extremes in the climate system, and the present California drought represents an excellent case study for such endeavors. Meanwhile, a powerful El Niño event in the Pacific Ocean offers the simultaneous prospect of partial drought relief but also an increased risk of flooding during the 2015-2016 winter—a situation illustrative of the complex hydroclimatic risks California and other regions are likely to face in a warming world.

The role of non-CO2 mitigation within the dairy sector in pursuing climate goals

NASA Astrophysics Data System (ADS)

Rolph, K.; Forest, C. E.

2017-12-01

Mitigation of non-CO2 climate forcing agents must complement the mitigation of carbon dioxide (CO2) to achieve long-term temperature and climate policy goals. By using multi-gas mitigation strategies, society can limit the rate of temperature change on decadal timescales and reduce the cost of implementing policies that only consider CO2 mitigation. The largest share of global non-CO2 greenhouse gas emissions is attributed to agriculture, with activities related to dairy production contributing the most in this sector. Approximately 4% of global anthropogenic greenhouse gas emissions is released from the dairy sub-sector, primarily through enteric fermentation, feed production, and manure management. Dairy farmers can significantly reduce their emissions by implementing better management practices. This study assesses the potential mitigation of projected climate change if greenhouse gases associated with the dairy sector were reduced. To compare the performance of several mitigation measures under future climate change, we employ a fully coupled earth system model of intermediate complexity, the MIT Integrated Global System Model (IGSM). The model includes an interactive carbon-cycle capable of addressing important feedbacks between the climate and terrestrial biosphere. Mitigation scenarios are developed using estimated emission reductions of implemented management practices studied by the USDA-funded Sustainable Dairy Project (Dairy-CAP). We examine pathways to reach the US dairy industry's voluntary goal of reducing dairy emissions 25% by 2020. We illustrate the importance of ongoing mitigation efforts in the agricultural industry to reduce non-CO2 greenhouse gas emissions towards established climate goals.

Modelling the morphodynamics and co-evolution of coast and estuarine environments

NASA Astrophysics Data System (ADS)

Morris, Chloe; Coulthard, Tom; Parsons, Daniel R.; Manson, Susan; Barkwith, Andrew

2017-04-01

The morphodynamics of coast and estuarine environments are known to be sensitive to environmental change and sea-level rise. However, whilst these systems have received considerable individual research attention, how they interact and co-evolve is relatively understudied. These systems are intrinsically linked and it is therefore advantageous to study them holistically in order to build a more comprehensive understanding of their behaviour and to inform sustainable management over the long term. Complex environments such as these are often studied using numerical modelling techniques. Inherent from the limited research in this area, existing models are currently not capable of simulating dynamic coast-estuarine interactions. A new model is being developed through coupling the one-line Coastline Evolution Model (CEM) with CAESAR-Lisflood (C-L), a hydrodynamic Landscape Evolution Model. It is intended that the eventual model be used to advance the understanding of these systems and how they may evolve over the mid to long term in response to climate change. In the UK, the Holderness Coast, Humber Estuary and Spurn Point system offers a diverse and complex case study for this research. Holderness is one of the fastest eroding coastlines in Europe and research suggests that the large volumes of material removed from its cliffs are responsible for the formation of the Spurn Point feature and for the Holocene infilling of the Humber Estuary. Marine, fluvial and coastal processes are continually reshaping this system and over the next century, it is predicted that climate change could lead to increased erosion along the coast and supply of material to the Humber Estuary and Spurn Point. How this manifests will be hugely influential to the future morphology of these systems and the existence of Spurn Point. Progress to date includes a new version of the CEM that has been prepared for integration into C-L and includes an improved graphical user interface and more complex geomorphological processes. Preliminary results from simulations of the Holderness Coast and Spurn Point support findings of other authors, who suggest that changes to the wave climate influences sediment transport patterns in the nearshore zone. The angle of wave approach to the Holderness shows particular significance compared to the height of waves, with an optimum volume of material transported at 42 degrees. Further applications and results of this new model will be presented and discussed.

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes

PubMed Central

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2018-01-01

Currently, the temperate forest biome cools the earth’s climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (−10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems. PMID:29628526

Are drought vulnerability indices useful tools in order to evaluate the state of a water supply system?

NASA Astrophysics Data System (ADS)

Preziosi, E.; Del Bon, A.; Romano, E.; Petrangeli, A. B.; Casadei, S.

2012-04-01

Water resources availability is affected both by anthropic drivers (increasing demand, modification in the uses) and natural ones such as precipitation decrease related to global climate changes. Water managers and water policy makers are more and more aware that they are facing a changing climate in which the availability of water is claimed to be decreasing in many parts of the world. The possibility that droughts will be more frequent and severe in the next decades is getting a real possibility and a wise manager should know in advance how to face this new reality. Hence new tools and, more important, a methodology to assess the weakest points of a complex water supply system to water scarcity scenarios, are necessary. The importance of simulation models to assess in advance the impacts of possible conditions of severe water shortage and the effects of feasible mitigation options on water supply systems is well known. Vulnerability is commonly used to characterize the performance of water supply systems, and it can be a helpful indicator in the evaluation of the most likely failures in a complex system in ordinary as well as in more severe climatic conditions. However a common procedure about the exploitation of modeling results is not established yet. In this research the water supply network of a case study area in Central Italy was modeled under different climatic and management hypothesis. In this area both ground water resources (well fields in alluvial aquifers and Apennine springs) and surface water resources stored in two large reservoirs, are exploited mainly for drinking water supply and irrigation. Climate scenarios were drawn based on three simplistic hypothesis: firstly a progressive reduction of precipitation in 55 years, secondly an increase in its variance during time, lastly a combination of the two. The model results were elaborated to calculate different indices, in order to analyze the variation of vulnerability of the water supply system to drought, in time and space. For our case study the model results show that the safety of the water supply system mainly relies on the reservoirs capacity and that the foreseen exploitation of the Apennine springs for drinking water supply could be seriously limited by the discharge natural decrease in fall. A decrease of the water system vulnerability to drought determined by a hypothetical but feasible mitigation option (augmentation of the total reservoir capacity with small reservoirs) was positively tested by the model. As a conclusion, vulnerability indices as well as synoptic risk maps, appear to be useful tools in order to analyze model results. Additionally they could provide scientific based scenarios to be used in a decision making framework considering negotiating among the main users.

Climatic variability leads to later seasonal flowering of Floridian plants.

PubMed

Von Holle, Betsy; Wei, Yun; Nickerson, David

2010-07-21

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses.

Response of the tropical Pacific to abrupt climate change 8,200 years ago

NASA Astrophysics Data System (ADS)

Atwood, A. R.; Battisti, D.; Bitz, C. M.; Sachs, J. P.

2017-12-01

The relatively stable climate of the Holocene epoch was punctuated by a period of large and abrupt climate change ca. 8,200 yr BP, when an outburst of glacial meltwater into the Labrador Sea drove large and abrupt climate changes across the globe. However, little is known about the response of the tropical Pacific to this event. We present the first evidence for large perturbations to the eastern tropical Pacific climate, based on sedimentary biomarker and hydrogen isotopic records from a freshwater lake in the Galápagos Islands. We inform these reconstructions with freshwater forcing simulations performed with the Community Climate System Model version 4. Together, the biomarker records and model simulations provide evidence for a mechanistic link between (1) a southward shift of the Intertropical Convergence Zone in the eastern equatorial Pacific and (2) decreased frequency and/or intensity of Eastern Pacific El Niño events during the 8,200 BP event. While climate theory and modeling studies support a southward shift of the ITCZ in response to a weakened AMOC, the dynamical drivers for the observed change in ENSO variability are less well developed. To explore these linkages, we perform simulations with an intermediate complexity model of the tropical Pacific. These results provide valuable insight into the controls of tropical Pacific climate variability and the mechanisms behind the global response to abrupt climate change.

The Aerosol-Monsoon Climate System of Asia

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kyu-Myong, Kim

2012-01-01

In Asian monsoon countries such as China and India, human health and safety problems caused by air-pollution are worsening due to the increased loading of atmospheric pollutants stemming from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash flood or prolonged drought, has caused major loss of human lives, and damages in crop and properties with devastating societal impacts on Asian countries. Historically, air-pollution and monsoon research are treated as separate problems. However a growing number of recent studies have suggested that the two problems may be intrinsically intertwined and need to be studied jointly. Because of complexity of the dynamics of the monsoon systems, aerosol impacts on monsoons and vice versa must be studied and understood in the context of aerosol forcing in relationship to changes in fundamental driving forces of the monsoon climate system (e.g. sea surface temperature, land-sea contrast etc.) on time scales from intraseasonal variability (weeks) to climate change ( multi-decades). Indeed, because of the large contributions of aerosols to the global and regional energy balance of the atmosphere and earth surface, and possible effects of the microphysics of clouds and precipitation, a better understanding of the response to climate change in Asian monsoon regions requires that aerosols be considered as an integral component of a fully coupled aerosol-monsoon system on all time scales. In this paper, using observations and results from climate modeling, we will discuss the coherent variability of the coupled aerosol-monsoon climate system in South Asia and East Asia, including aerosol distribution and types, with respect to rainfall, moisture, winds, land-sea thermal contrast, heat sources and sink distributions in the atmosphere in seasonal, interannual to climate change time scales. We will show examples of how elevated absorbing aerosols (dust and black carbon) may interact with monsoon dynamics to produce feedback effects on the atmospheric water cycle, leading to in accelerated melting of snowpacks over the Himalayas and Tibetan Plateau, and subsequent changes in evolution of the pre-monsoon and peak monsoon rainfall, moisture and wind distributions in South Asia and East Asia.

Potential for added value in precipitation simulated by high-resolution nested Regional Climate Models and observations

NASA Astrophysics Data System (ADS)

di Luca, Alejandro; de Elía, Ramón; Laprise, René

2012-03-01

Regional Climate Models (RCMs) constitute the most often used method to perform affordable high-resolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.

Application of scenario-neutral methods to quantify impacts of climate change on water resources in East Africa

NASA Astrophysics Data System (ADS)

Ascott, M.; Macdonald, D.; Lapworth, D.; Tindimugaya, C.

2017-12-01

Quantification of the impact of climate change on water resources is essential for future resource planning. Unfortunately, climate change impact studies in African regions are often hindered by the extent in variability in future rainfall predictions, which also diverge from current drying trends. To overcome this limitation, "scenario-neutral" methods have been developed which stress a hydrological system using a wide range of climate futures to build a "climate response surface". We developed a hydrological model and scenario-neutral framework to quantify climate change impacts on river flows in the Katonga catchment, Uganda. Using the lumped catchment model GR4J, an acceptable calibration to historic daily flows (1966 - 2010, NSE = 0.69) was achieved. Using a delta change approach, we then systematically changed rainfall and PET inputs to develop response surfaces for key metrics, developed with Ugandan water resources planners (e.g. Q5, Q95). Scenarios from the CMIP5 models for 2030s and 2050s were then overlain on the response surface. The CMIP5 scenarios show consistent increases in temperature but large variability in rainfall increases, which results in substantial variability in increases in river flows. The developed response surface covers a wide range of climate futures beyond the CMIP5 projections, and can help water resources planners understand the sensitivity of water resource systems to future changes. When future climate scenarios are available, these can be directly overlain on the response surface without the need to re-run the hydrological model. Further work will consider using scenario-neutral approaches in more complex, semi-distributed models (e.g. SWAT), and will consider land use and socioeconomic change.

A Multi-Faceted Approach to Analyse the Effects of Environmental Variables on Geographic Range and Genetic Structure of a Perennial Psammophilous Geophyte: The Case of the Sea Daffodil Pancratium maritimum L. in the Mediterranean Basin

PubMed Central

Di Febbraro, Mirko; Imparato, Gennaro; Innangi, Michele; Véla, Errol; Menale, Bruno

2016-01-01

The Mediterranean coastline is a dynamic and complex system which owes its complexity to its past and present vicissitudes, e.g. complex tectonic history, climatic fluctuations, and prolonged coexistence with human activities. A plant species that is widespread in this habitat is the sea daffodil, Pancratium maritimum (Amaryllidaceae), which is a perennial clonal geophyte of the coastal sands of the Mediterranean and neighbouring areas, well adapted to the stressful conditions of sand dune environments. In this study, an integrated approach was used, combining genetic and environmental data with a niche modelling approach, aimed to investigate: (1) the effect of climate change on the geographic range of this species at different times {past (last inter-glacial, LIG; and last glacial maximum, LGM), present (CURR), near-future (FUT)} and (2) the possible influence of environmental variables on the genetic structure of this species in the current period. The genetic results show that 48 sea daffodil populations (867 specimens) display a good genetic diversity in which the marginal populations (i.e. Atlantic Sea populations) present lower values. Recent genetic signature of bottleneck was detected in few populations (8%). The molecular variation was higher within the populations (77%) and two genetic pools were well represented. Comparing the different climatic simulations in time, the global range of this plant increased, and a further extension is foreseen in the near future thanks to projections on the climate of areas currently—more temperate, where our model suggested a forecast for a climate more similar to the Mediterranean coast. A significant positive correlation was observed between the genetic distance and Precipitation of Coldest Quarter variable in current periods. Our analyses support the hypothesis that geomorphology of the Mediterranean coasts, sea currents, and climate have played significant roles in shaping the current genetic structure of the sea daffodil especially during LGM because of strong variation in coastline caused by glaciations. PMID:27749920

Climatic effects on the nasal complex: a CT imaging, comparative anatomical, and morphometric investigation of Macaca mulatta and Macaca fascicularis.

PubMed

Márquez, Samuel; Laitman, Jeffrey T

2008-11-01

Previous studies exploring the effects of climate on the nasal region have largely focused on external craniofacial linear parameters, using dry crania of modern human populations. This investigation augments traditional craniofacial morphometrics with internal linear and volumetric measures of the anatomic units comprising the nasal complex (i.e., internal nasal cavity depth, maxillary sinus volumes). The study focuses on macaques (i.e., Macaca mulatta and Macaca fascicularis) living at high and low altitudes, rather than on humans, since the short residency of migratory human populations may preclude using them as reliable models to test the long-term relationship of climate to nasal morphology. It is hypothesized that there will be significant differences in nasal complex morphology among macaques inhabiting different climates. This study integrated three different approaches: CT imaging, comparative anatomy, and morphometrics-in an effort to better understand the morphological structure and adaptive nature of the nasal complex. Results showed statistically significant differences when subsets of splanchnocranial and neurocranial variables were regressed against total maxillary sinus volume for particular taxa. For example, basion-hormion was significant for M. fascicularis, whereas choanal dimensions were significant only for M. mulatta. Both taxa revealed strong correlation between sinus volume and prosthion to staphylion distance, which essentially represents the length of the nasal cavity floor-and is by extension an indicator of the air conditioning capacity of the nasal region. These results clearly show that climatic effects play a major role in shaping the anatomy of the nasal complex in closely related species. The major influence upon these differing structures appears to be related to respiratory-related adaptations subserving differing climatic factors. In addition, the interdependence of the paranasal sinuses with other parts of the complex strongly indicates a functional role for them in nasal complex/upper respiratory functions. Copyright 2008 Wiley-Liss, Inc.

Developing Climate Resilience Toolkit Decision Support Training Sectio

NASA Astrophysics Data System (ADS)

Livezey, M. M.; Herring, D.; Keck, J.; Meyers, J. C.

2014-12-01

The Climate Resilience Toolkit (CRT) is a Federal government effort to address the U.S. President's Climate Action Plan and Executive Order for Climate Preparedness. The toolkit will provide access to tools and products useful for climate-sensitive decision making. To optimize the user experience, the toolkit will also provide access to training materials. The National Oceanic and Atmospheric Administration (NOAA) has been building a climate training capability for 15 years. The target audience for the training has historically been mainly NOAA staff with some modified training programs for external users and stakeholders. NOAA is now using this climate training capacity for the CRT. To organize the CRT training section, we collaborated with the Association of Climate Change Officers to determine the best strategy and identified four additional complimentary skills needed for successful decision making: climate literacy, environmental literacy, risk assessment and management, and strategic execution and monitoring. Developing the climate literacy skills requires knowledge of climate variability and change, as well as an introduction to the suite of available products and services. For the development of an environmental literacy category, specific topics needed include knowledge of climate impacts on specific environmental systems. Climate risk assessment and management introduces a process for decision making and provides knowledge on communication of climate information and integration of climate information in planning processes. The strategic execution and monitoring category provides information on use of NOAA climate products, services, and partnership opportunities for decision making. In order to use the existing training modules, it was necessary to assess their level of complexity, catalog them, and develop guidance for users on a curriculum to take advantage of the training resources to enhance their learning experience. With the development of this CRT training section, NOAA has made significant progress in sharing resources with the external community.

Java Climate Model: a tool for interaction between science, policy and citizens, to avoid dangerous anthropogenic interference in the climate system

NASA Astrophysics Data System (ADS)

Matthews, B.

2003-04-01

To reach an effective global agreement to help avoid "dangerous anthropogenic interference in the climate system" (UNFCCC article 2) we must balance many complex interacting issues, and also inspire the active engagement of citizens around the world. So we have to transfer understanding back from computers and experts, into the ultimate "integrated assessment model" which remains the global network of human heads. The Java Climate Model (JCM) tries to help provide a quantitative framework for this global dialogue, by enabling anybody to explore many mitigation policy options and scientific uncertainties simply by adjusting parameter controls with a mouse in a web browser. The instant response on linked plots helps to demonstrate cause and effect, and the sensitivity to various assumptions, risk and value judgements. JCM implements the same simple models and formulae as used by IPCC for the TAR projections, in efficient modular structure, including carbon cycle and atmospheric chemistry, radiative forcing, changes in temperature and sealevel, including some feedbacks. As well as explore the SRES scenarios, the user can create a wide variety of inverse scenarios for stabilising CO2, forcing, or temperature. People ask how local emissions which they can control, may influence the vast global natural and human systems, and change local climate impacts which affect them directly. JCM includes regional emissions and socioeconomic data, and scaled climate impact maps. However to complete this loop in a fast interactive model is a challenge! For transparency and accessibility, pop-up information is provided in ten languages, and documentation ranges from key cross-cutting questions, to them details of the model formulae, including all source code.

The impact of warming on greenhouse gas fluxes: an experimental comparison which reveals the varied response of ecosystems to climate change.

NASA Astrophysics Data System (ADS)

Stockdale, James; Ineson, Philip

2016-04-01

Modelled predictions of the response of terrestrial systems to climate change are highly variable, yet the response of net ecosystem exchange (NEE) is a vital ecosystem behaviour to understand due to its inherent feedback to the carbon cycle. The establishment and subsequent monitoring of replicated experimental manipulations are a direct method to reveal these responses, yet are difficult to achieve as they typically resource-heavy and labour intensive. We actively manipulated the temperature at three agricultural grasslands in southern England and deployed novel 'SkyLine' systems, recently developed at the University of York, to continuously monitor GHG fluxes. Each 'SkyLine' is a low-cost and fully autonomous technology yet produces fluxes at a near-continuous temporal frequency and across a wide spatial area. The results produced by 'SkyLine' enable the detail response of each system to increased temperature over diurnal and seasonal timescales. Unexpected differences in NEE are shown between superficially similar ecosystems which, upon investigation, suggest that interactions between a variety of environmental variables are key and that knowledge of pre-existing environmental conditions help to predict a systems response to future climate. For example, the prevailing hydrological conditions at each site appear to affect its response to changing temperature. The high-frequency data shown here, combined with the fully-replicated experimental design reveal complex interactions which must be understood to improve predictions of ecosystem response to a changing climate.

To Tip or Not to Tip: The Case of the Congo Basin Rainforest Realm

NASA Astrophysics Data System (ADS)

Pietsch, S.; Bednar, J. E.; Fath, B. D.; Winter, P. A.

2017-12-01

The future response of the Congo basin rainforest, the second largest tropical carbon reservoir, to climate change is still under debate. Different Climate projections exist stating increase and decrease in rainfall and different changes in rainfall patterns. Within this study we assess all options of climate change possibilities to define the climatic thresholds of Congo basin rainforest stability and assess the limiting conditions for rainforest persistence. We use field data from 199 research plots from the Western Congo basin to calibrate and validate a complex BioGeoChemistry model (BGC-MAN) and assess model performance against an array of possible future climates. Next, we analyze the reasons for the occurrence of tipping points, their spatial and temporal probability of occurrence, will present effects of hysteresis and derive probabilistic spatial-temporal resilience landscapes for the region. Additionally, we will analyze attractors of forest growth dynamics and assess common linear measures for early warning signals of sudden shifts in system dynamics for their robustness in the context of the Congo Basin case, and introduce the correlation integral as a nonlinear measure of risk assessment.

Midcontinent Prairie-Pothole wetlands and climate change: An Introduction to the Supplemental Issue

USGS Publications Warehouse

Mushet, David M.

2016-01-01

The multitude of wetlands in the Prairie Pothole Region of North America forms one of Earth’s largest wetland complexes. The midcontinent location exposes this ecologically and economically important wetland system to a highly variable climate, markedly influencing ponded-water levels, hydroperiods, chemical characteristics, and biota of individual basins. Given their dominance on the landscape and recognized value, great interest in how projected future changes in climate will affect prairie-pothole wetlands has developed and spawned much scientific research. On June 2, 2015, a special symposium, “Midcontinent Prairie-Pothole Wetlands: Influence of a Changed Climate,” was held at the annual meeting of the Society of Wetland Scientists in Providence, Rhode Island, USA. The symposium’s twelve presenters covered a wide range of relevant topics delivered to a standing-room-only audience. Following the symposium, the presenters recognized the need to publish their presented papers as a combined product to facilitate widespread distribution. The need for additional papers to more fully cover the topic of prairie-pothole wetlands and climate change was also identified. This supplemental issue of Wetlands is the realization of that vision.

Integrated assessment of the impact of climate and land use changes on groundwater quantity and quality in Mancha Oriental (Spain)

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Peña-Haro, S.; Garcia-Prats, A.; Mocholi-Almudever, A. F.; Henriquez-Dole, L.; Macian-Sorribes, H.; Lopez-Nicolas, A.

2014-09-01

Climate and land use change (global change) impacts on groundwater systems cannot be studied in isolation, as various and complex interactions in the hydrological cycle take part. Land-use and land-cover (LULC) changes have a great impact on the water cycle and contaminant production and transport. Groundwater flow and storage are changing in response not only to climatic changes but also to human impacts on land uses and demands (global change). Changes in future climate and land uses will alter the hydrologic cycles and subsequently impact the quantity and quality of regional water systems. Predicting the behavior of recharge and discharge conditions under future climatic and land use changes is essential for integrated water management and adaptation. In the Mancha Oriental system in Spain, in the last decades the transformation from dry to irrigated lands has led to a significant drop of the groundwater table in one of the largest groundwater bodies in Spain, with the consequent effect on stream-aquifer interaction in the connected Jucar River. Streamflow depletion is compromising the related ecosystems and the supply to the downstream demands, provoking a complex management issue. The intense use of fertilizer in agriculture is also leading to locally high groundwater nitrate concentrations. Understanding the spatial and temporal distribution of water availability and water quality is essential for a proper management of the system. In this paper we analyze the potential impact of climate and land use change in the system by using an integrated modelling framework consisting of the sequentially coupling of a watershed agriculturally-based hydrological model (SWAT) with the ground-water model MODFLOW and mass-transport model MT3D. SWAT model outputs (mainly groundwater recharge and pumping, considering new irrigation needs under changing ET and precipitation) are used as MODFLOW inputs to simulate changes in groundwater flow and storage and impacts on stream-aquifer interaction. SWAT and MODFLOW outputs (nitrate loads from SWAT, groundwater velocity field from MODFLOW) are used as MT3D inputs for assessing the fate and transport of nitrate leached from the topsoil. Results on river discharge, crop yields, groundwater levels and groundwater nitrate concentrations obtained from simulation fit well to the observed values. Three climate change scenarios have been considered, corresponding to 3 different GCMs for emission scenario A1B, covering the control period, and short, medium and long-term future periods. A multi-temporal analysis of LULC change was carried out, helped by the study of historical trends by remote sensing images and key driving forces to explain LULC transitions. Markov chains and European scenarios and projections have been used to quantify trends in the future. The cellular automata technique was applied for stochastic modeling future LULC maps. The results show the sensitivity of groundwater quantity and quality (nitrate pollution) to climate and land use changes, and the need to implement adaptation measures in order to prevent further groundwater level declines and increasing nitrate concentrations. The sequential modelling chain has been proved to be a valuable assessment and management tool for supporting the development of sustainable management strategies.

NCAR's Research Data Archive: OPeNDAP Access for Complex Datasets

NASA Astrophysics Data System (ADS)

Dattore, R.; Worley, S. J.

2014-12-01

Many datasets have complex structures including hundreds of parameters and numerous vertical levels, grid resolutions, and temporal products. Making these data accessible is a challenge for a data provider. OPeNDAP is powerful protocol for delivering in real-time multi-file datasets that can be ingested by many analysis and visualization tools, but for these datasets there are too many choices about how to aggregate. Simple aggregation schemes can fail to support, or at least make it very challenging, for many potential studies based on complex datasets. We address this issue by using a rich file content metadata collection to create a real-time customized OPeNDAP service to match the full suite of access possibilities for complex datasets. The Climate Forecast System Reanalysis (CFSR) and it's extension, the Climate Forecast System Version 2 (CFSv2) datasets produced by the National Centers for Environmental Prediction (NCEP) and hosted by the Research Data Archive (RDA) at the Computational and Information Systems Laboratory (CISL) at NCAR are examples of complex datasets that are difficult to aggregate with existing data server software. CFSR and CFSv2 contain 141 distinct parameters on 152 vertical levels, six grid resolutions and 36 products (analyses, n-hour forecasts, multi-hour averages, etc.) where not all parameter/level combinations are available at all grid resolution/product combinations. These data are archived in the RDA with the data structure provided by the producer; no additional re-organization or aggregation have been applied. Since 2011, users have been able to request customized subsets (e.g. - temporal, parameter, spatial) from the CFSR/CFSv2, which are processed in delayed-mode and then downloaded to a user's system. Until now, the complexity has made it difficult to provide real-time OPeNDAP access to the data. We have developed a service that leverages the already-existing subsetting interface and allows users to create a virtual dataset with its own structure (das, dds). The user receives a URL to the customized dataset that can be used by existing tools to ingest, analyze, and visualize the data. This presentation will detail the metadata system and OPeNDAP server that enable user-customized real-time access and show an example of how a visualization tool can access the data.

Global Climate Change: Using Field Studies to Prepare the Next Generation of Scientists

NASA Astrophysics Data System (ADS)

Arnold, T. C.; Hare, J.

2004-05-01

Global Climate Change is a new and invigorating concept in the pre-college classroom. To some it portends the altering of the Earth's climate by introducing anthropogenic influences and for others the natural progression of the Earth's systems. Regardless, climate change involves a plethora of environmental interactions and comprehension is a challenge for both teachers and students. This paper addresses a field studies program that prepares students to complete research projects associated with climate models affecting montane environments. It emphasizes a partnership between researchers from universities, government agencies, and public schools and their support of pre-college students in inquiry learning and research activities. Beginning in 1994 students from a Pennsylvania high school and schools in Scotland have engaged in biannual holistic studies of montane and glacial environments with the objective of completing investigations concerning the energy budgets of these environments. This paper will focus on 2000 and 2002, and the support and partnership of Dr. Jeff Hare and CIRES in designing, supporting, and providing professional interpretations,while assisting teachers and students toward the completion of recognized papers regarding climate studies. Introducing students to the employment and operation of complex field equipment will be discussed.

The Role of Artificial Atmospheric CO2 Removal in Stabilizing Earth's Climate

NASA Astrophysics Data System (ADS)

Tokarska, Katarzyna; Zickfeld, Kirsten

2014-05-01

Recent research showed that global mean temperature remains approximately constant for several centuries after complete cessation of CO2 emissions, while global mean thermosteric sea level continues to rise. This implies that a net artificial removal of CO2 from the atmosphere may be necessary to decrease the atmospheric CO2 concentrations more rapidly and bring the climate system components to their previous states on human timescales. The purpose of this study is to explore the reversibility of climate responses to a range of realistic CO2 emission scenarios, which follow a gradual transition from fossil-fuel driven economy to a zero-emission energy system with implementation of negative CO2 emissions, using the University of Victoria Earth System Climate Model of intermediate complexity (UVic ESCM 2.9). The CO2 emission pathways were designed to meet constraints related to the implementation of negative emission technologies derived from the integrated assessment literature. Our simulations show that while it is possible, in principle, to revert the global mean temperature after a phase of overshoot, the thermosteric sea level rise is not reversible on human timescales for the range of emission scenarios considered. During the negative emission phase, CO2 is released form the natural (terrestrial and marine) carbon sinks, which diminishes the efficiency of negative emissions implemented. In addition, spatial changes of vegetation distribution patterns are not entirely reversible on human timescales. We suggest that while negative emissions could potentially stabilize the global mean temperature at a desired level, such technology does not supersede reductions in fossil fuel emissions, as the artificial CO2 capture at large scale has many limitations and is unable to stabilize other climate system components (e.g. sea level) at desired levels.

The mineralogic evolution of the Martian surface through time: Implications from chemical reaction path modeling studies

NASA Technical Reports Server (NTRS)

Plumlee, G. S.; Ridley, W. I.; Debraal, J. D.; Reed, M. H.

1993-01-01

Chemical reaction path calculations were used to model the minerals that might have formed at or near the Martian surface as a result of volcano or meteorite impact driven hydrothermal systems; weathering at the Martian surface during an early warm, wet climate; and near-zero or sub-zero C brine-regolith reactions in the current cold climate. Although the chemical reaction path calculations carried out do not define the exact mineralogical evolution of the Martian surface over time, they do place valuable geochemical constraints on the types of minerals that formed from an aqueous phase under various surficial and geochemically complex conditions.

Mountain landscapes offer few opportunities for high-elevation tree species migration

USGS Publications Warehouse

Bell, David M.; Bradford, John B.; Lauenroth, William K.

2014-01-01

Climate change is anticipated to alter plant species distributions. Regional context, notably the spatial complexity of climatic gradients, may influence species migration potential. While high-elevation species may benefit from steep climate gradients in mountain regions, their persistence may be threatened by limited suitable habitat as land area decreases with elevation. To untangle these apparently contradictory predictions for mountainous regions, we evaluated the climatic suitability of four coniferous forest tree species of the western United States based on species distribution modeling (SDM) and examined changes in climatically suitable areas under predicted climate change. We used forest structural information relating to tree species dominance, productivity, and demography from an extensive forest inventory system to assess the strength of inferences made with a SDM approach. We found that tree species dominance, productivity, and recruitment were highest where climatic suitability (i.e., probability of species occurrence under certain climate conditions) was high, supporting the use of predicted climatic suitability in examining species risk to climate change. By predicting changes in climatic suitability over the next century, we found that climatic suitability will likely decline, both in areas currently occupied by each tree species and in nearby unoccupied areas to which species might migrate in the future. These trends were most dramatic for high elevation species. Climatic changes predicted over the next century will dramatically reduce climatically suitable areas for high-elevation tree species while a lower elevation species, Pinus ponderosa, will be well positioned to shift upslope across the region. Reductions in suitable area for high-elevation species imply that even unlimited migration would be insufficient to offset predicted habitat loss, underscoring the vulnerability of these high-elevation species to climatic changes.

Marble Deterioration and Climate: Examples from the Schlossbrücke Berlin

NASA Astrophysics Data System (ADS)

Pirskawetz, S.; Siegesmund, S.; Weise, F.; Rieffel, Y.; Plagge, R.

2012-04-01

Protective structures for works of art or antique artefacts have a long architectural tradition and have been known in Germany since the 19th century. The effect of such covers on the microclimate around artworks of natural stone, and hence, their protective capability are insufficiently documented and understood. In 2007, an inter-disciplinary model project and part of a pilot study coordinated by the Berlin State Office for the Protection of Monuments was planned with the aim of developing an innovative winter covering system for marble statuaries located on the Schlossbrücke in Berlin. Such a system would need to fulfil the various requirements for structural stability, aesthetics, climate and practical use. This applied research represents the first complex scientific study of the sustainability of a winter covering system. A climate monitoring system was designed to create a dense database for the numerical prediction of the effect of protective systems, and to compare the given climate conditions to the known factors influencing the marble deterioration. Based on these findings a prototype of an innovative shelter was designed and tested. The project shows, that beside a temporary covering regular inspection and maintenance combined with regular cleaning ensures an effective and sustainable protection of marble sculptures. Such a maintenance program is the precondition for preserving the sculptures of the Schlossbrücke as a historical ensemble. Important scientific results of the project are transferable to similar objects of Carrara marble. The results throw a new light on the conventional protection of such objects and leads to a discussion on the necessity of an all-season protection.